Text Mining in Cancer Gene and Pathway Prioritization

PubMed Central

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes. PMID:25392685

Text mining in cancer gene and pathway prioritization.

PubMed

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

Systematic analysis of signaling pathways using an integrative environment.

PubMed

Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

2007-01-01

Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis.

PubMed

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-11-07

To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

PubMed Central

Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu

2003-01-01

Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. Results We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. Conclusion PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). PMID:14604444

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

GARNET--gene set analysis with exploration of annotation relations.

PubMed

Rho, Kyoohyoung; Kim, Bumjin; Jang, Youngjun; Lee, Sanghyun; Bae, Taejeong; Seo, Jihae; Seo, Chaehwa; Lee, Jihyun; Kang, Hyunjung; Yu, Ungsik; Kim, Sunghoon; Lee, Sanghyuk; Kim, Wan Kyu

2011-02-15

Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information. GARNET (Gene Annotation Relationship NEtwork Tools) is an integrative platform for gene set analysis with many novel features. It includes tools for retrieval of genes from annotation database, statistical analysis & visualization of annotation relationships, and managing gene sets. In an effort to allow access to a full spectrum of amassed biological knowledge, we have integrated a variety of annotation data that include the GO, domain, disease, drug, chromosomal location, and custom-defined annotations. Diverse types of molecular networks (pathways, transcription and microRNA regulations, protein-protein interaction) are also included. The pair-wise relationship between annotation gene sets was calculated using kappa statistics. GARNET consists of three modules--gene set manager, gene set analysis and gene set retrieval, which are tightly integrated to provide virtually automatic analysis for gene sets. A dedicated viewer for annotation network has been developed to facilitate exploration of the related annotations. GARNET (gene annotation relationship network tools) is an integrative platform for diverse types of gene set analysis, where complex relationships among gene annotations can be easily explored with an intuitive network visualization tool (http://garnet.isysbio.org/ or http://ercsb.ewha.ac.kr/garnet/).

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources

PubMed Central

Waagmeester, Andra; Pico, Alexander R.

2016-01-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. PMID:27336457

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

PubMed

Waagmeester, Andra; Kutmon, Martina; Riutta, Anders; Miller, Ryan; Willighagen, Egon L; Evelo, Chris T; Pico, Alexander R

2016-06-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Integrative pathway knowledge bases as a tool for systems molecular medicine.

PubMed

Liang, Mingyu

2007-08-20

There exists a sense of urgency to begin to generate a cohesive assembly of biomedical knowledge as the pace of knowledge accumulation accelerates. The urgency is in part driven by the emergence of systems molecular medicine that emphasizes the combination of systems analysis and molecular dissection in the future of medical practice and research. A potentially powerful approach is to build integrative pathway knowledge bases that link organ systems function with molecules.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

PubMed

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

VitaPad: visualization tools for the analysis of pathway data.

PubMed

Holford, Matthew; Li, Naixin; Nadkarni, Prakash; Zhao, Hongyu

2005-04-15

Packages that support the creation of pathway diagrams are limited by their inability to be readily extended to new classes of pathway-related data. VitaPad is a cross-platform application that enables users to create and modify biological pathway diagrams and incorporate microarray data with them. It improves on existing software in the following areas: (i) It can create diagrams dynamically through graph layout algorithms. (ii) It is open-source and uses an open XML format to store data, allowing for easy extension or integration with other tools. (iii) It features a cutting-edge user interface with intuitive controls, high-resolution graphics and fully customizable appearance. http://bioinformatics.med.yale.edu matthew.holford@yale.edu; hongyu.zhao@yale.edu.

Modeling biochemical pathways in the gene ontology

DOE PAGES

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.; ...

2016-09-01

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

How Effective Are Clinical Pathways With and Without Online Peer-Review? An Analysis of Bone Metastases Pathway in a Large, Integrated National Cancer Institute-Designated Comprehensive Cancer Center Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beriwal, Sushil, E-mail: beriwals@upmc.edu; Rajagopalan, Malolan S.; Flickinger, John C.

2012-07-15

Purpose: Clinical pathways are an important tool used to manage the quality in health care by standardizing processes. This study evaluated the impact of the implementation of a peer-reviewed clinical pathway in a large, integrated National Cancer Institute-Designated Comprehensive Cancer Center Network. Methods: In 2003, we implemented a clinical pathway for the management of bone metastases with palliative radiation therapy. In 2009, we required the entry of management decisions into an online tool that records pathway choices. The pathway specified 1 or 5 fractions for symptomatic bone metastases with the option of 10-14 fractions for certain clinical situations. The datamore » were obtained from 13 integrated sites (3 central academic, 10 community locations) from 2003 through 2010. Results: In this study, 7905 sites were treated with 64% of courses delivered in community practice and 36% in academic locations. Academic practices were more likely than community practices to treat with 1-5 fractions (63% vs. 23%; p < 0.0001). The number of delivered fractions decreased gradually from 2003 to 2010 for both academic and community practices (p < 0.0001); however, greater numbers of fractions were selected more often in community practices (p < 0.0001). Using multivariate logistic regression, we found that a significantly greater selection of 1-5 fractions developed after implementation online pathway monitoring (2009) with an odds ratio of 1.2 (confidence interval, 1.1-1.4) for community and 1.3 (confidence interval, 1.1-1.6) for academic practices. The mean number of fractions also decreased after online peer review from 6.3 to 6.0 for academic (p = 0.07) and 9.4 to 9.0 for community practices (p < 0.0001). Conclusion: This is one of the first studies to examine the efficacy of a clinical pathway for radiation oncology in an integrated cancer network. Clinical pathway implementation appears to be effective in changing patterns of care, particularly with online clinical peer review as a valuable aid to encourage adherence to evidence-based practice.« less

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

Pathway Inspector: a pathway based web application for RNAseq analysis of model and non-model organisms.

PubMed

Bianco, Luca; Riccadonna, Samantha; Lavezzo, Enrico; Falda, Marco; Formentin, Elide; Cavalieri, Duccio; Toppo, Stefano; Fontana, Paolo

2017-02-01

Pathway Inspector is an easy-to-use web application helping researchers to find patterns of expression in complex RNAseq experiments. The tool combines two standard approaches for RNAseq analysis: the identification of differentially expressed genes and a topology-based analysis of enriched pathways. Pathway Inspector is equipped with ad hoc interactive graphical interfaces simplifying the discovery of modulated pathways and the integration of the differentially expressed genes in the corresponding pathway topology. Pathway Inspector is available at the website http://admiral.fmach.it/PI and has been developed in Python, making use of the Django Web Framework. Contact:paolo.fontana@fmach.it

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

PubMed Central

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

2018-01-01

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

PubMed

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

2018-02-22

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

Quantifying ubiquitin signaling.

PubMed

Ordureau, Alban; Münch, Christian; Harper, J Wade

2015-05-21

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), including phosphorylation. Flux through such pathways is dictated by the fractional stoichiometry of distinct modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events, illustrated with the PINK1/PARKIN pathway. A key feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

PubMed

Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

2009-06-29

One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at http://www.abcc.ncifcrf.gov/wps/wps_index.php.

PumpKin: A tool to find principal pathways in plasma chemical models

NASA Astrophysics Data System (ADS)

Markosyan, A. H.; Luque, A.; Gordillo-Vázquez, F. J.; Ebert, U.

2014-10-01

PumpKin is a software package to find all principal pathways, i.e. the dominant reaction sequences, in chemical reaction systems. Although many tools are available to integrate numerically arbitrarily complex chemical reaction systems, few tools exist in order to analyze the results and interpret them in relatively simple terms. In particular, due to the large disparity in the lifetimes of the interacting components, it is often useful to group reactions into pathways that recycle the fastest species. This allows a researcher to focus on the slow chemical dynamics, eliminating the shortest timescales. Based on the algorithm described by Lehmann (2004), PumpKin automates the process of finding such pathways, allowing the user to analyze complex kinetics and to understand the consumption and production of a certain species of interest. We designed PumpKin with an emphasis on plasma chemical systems but it can also be applied to atmospheric modeling and to industrial applications such as plasma medicine and plasma-assisted combustion.

Integration of Personalized Healthcare Pathways in an ICT Platform for Diabetes Managements: A Small-Scale Exploratory Study.

PubMed

Fico, Giuseppe; Fioravanti, Alessio; Arredondo, Maria Teresa; Gorman, Joe; Diazzi, Chiara; Arcuri, Giovanni; Conti, Claudio; Pirini, Giampiero

2016-01-01

The availability of new tools able to support patient monitoring and personalized care may substantially improve the quality of chronic disease management. A personalized healthcare pathway (PHP) has been developed for diabetes disease management and integrated into an information and communication technology system to accomplish a shift from organization-centered care to patient-centered care. A small-scale exploratory study was conducted to test the platform. Preliminary results are presented that shed light on how the PHP influences system usage and performance outcomes.

Prioritizing Contaminants for Monitoring and Management

EPA Pesticide Factsheets

EPA researcher presents work to develop methods and tools that integrate chemical monitoring with pathway-based bioactivity measurements, which will help provide screening-level assessments useful to identify and prioritize emerging contaminants.

A Web Tool for Generating High Quality Machine-readable Biological Pathways.

PubMed

Ramirez-Gaona, Miguel; Marcu, Ana; Pon, Allison; Grant, Jason; Wu, Anthony; Wishart, David S

2017-02-08

PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to generate over 2,000 pathway diagrams, which are now found in many online databases including HMDB, DrugBank, SMPDB, and ECMDB.

Integrative Metabolism: An Interactive Learning Tool for Nutrition, Biochemistry, and Physiology

ERIC Educational Resources Information Center

Carey, Gale

2010-01-01

Metabolism is a dynamic, simultaneous, and integrative science that cuts across nutrition, biochemistry, and physiology. Teaching this science can be a challenge. The use of a scenario-based, visually appealing, interactive, computer-animated CD may overcome the limitations of learning "one pathway at a time" and engage two- and…

Pathway Inspector: a pathway based web application for RNAseq analysis of model and non-model organisms

PubMed Central

Bianco, Luca; Riccadonna, Samantha; Lavezzo, Enrico; Falda, Marco; Formentin, Elide; Cavalieri, Duccio; Toppo, Stefano

2017-01-01

Abstract Summary: Pathway Inspector is an easy-to-use web application helping researchers to find patterns of expression in complex RNAseq experiments. The tool combines two standard approaches for RNAseq analysis: the identification of differentially expressed genes and a topology-based analysis of enriched pathways. Pathway Inspector is equipped with ad hoc interactive graphical interfaces simplifying the discovery of modulated pathways and the integration of the differentially expressed genes in the corresponding pathway topology. Availability and Implementation: Pathway Inspector is available at the website http://admiral.fmach.it/PI and has been developed in Python, making use of the Django Web Framework. Contact: paolo.fontana@fmach.it PMID:28158604

PathText: a text mining integrator for biological pathway visualizations

PubMed Central

Kemper, Brian; Matsuzaki, Takuya; Matsuoka, Yukiko; Tsuruoka, Yoshimasa; Kitano, Hiroaki; Ananiadou, Sophia; Tsujii, Jun'ichi

2010-01-01

Motivation: Metabolic and signaling pathways are an increasingly important part of organizing knowledge in systems biology. They serve to integrate collective interpretations of facts scattered throughout literature. Biologists construct a pathway by reading a large number of articles and interpreting them as a consistent network, but most of the models constructed currently lack direct links to those articles. Biologists who want to check the original articles have to spend substantial amounts of time to collect relevant articles and identify the sections relevant to the pathway. Furthermore, with the scientific literature expanding by several thousand papers per week, keeping a model relevant requires a continuous curation effort. In this article, we present a system designed to integrate a pathway visualizer, text mining systems and annotation tools into a seamless environment. This will enable biologists to freely move between parts of a pathway and relevant sections of articles, as well as identify relevant papers from large text bases. The system, PathText, is developed by Systems Biology Institute, Okinawa Institute of Science and Technology, National Centre for Text Mining (University of Manchester) and the University of Tokyo, and is being used by groups of biologists from these locations. Contact: brian@monrovian.com. PMID:20529930

Developing molecular tools for Chlamydomonas reinhardtii

NASA Astrophysics Data System (ADS)

Noor-Mohammadi, Samaneh

Microalgae have garnered increasing interest over the years for their ability to produce compounds ranging from biofuels to neutraceuticals. A main focus of researchers has been to use microalgae as a natural bioreactor for the production of valuable and complex compounds. Recombinant protein expression in the chloroplasts of green algae has recently become more routine; however, the heterologous expression of multiple proteins or complete biosynthetic pathways remains a significant challenge. To take full advantage of these organisms' natural abilities, sophisticated molecular tools are needed to be able to introduce and functionally express multiple gene biosynthetic pathways in its genome. To achieve the above objective, we have sought to establish a method to construct, integrate and express multigene operons in the chloroplast and nuclear genome of the model microalgae Chlamydomonas reinhardtii. Here we show that a modified DNA Assembler approach can be used to rapidly assemble multiple-gene biosynthetic pathways in yeast and then integrate these assembled pathways at a site-specific location in the chloroplast, or by random integration in the nuclear genome of C. reinhardtii. As a proof of concept, this method was used to successfully integrate and functionally express up to three reporter proteins (AphA6, AadA, and GFP) in the chloroplast of C. reinhardtii and up to three reporter proteins (Ble, AphVIII, and GFP) in its nuclear genome. An analysis of the relative gene expression of the engineered strains showed significant differences in the mRNA expression levels of the reporter genes and thus highlights the importance of proper promoter/untranslated-region selection when constructing a target pathway. In addition, this work focuses on expressing the cofactor regeneration enzyme phosphite dehydrogenase (PTDH) in the chloroplast and nuclear genomes of C. reinhardtii. The PTDH enzyme converts phosphite into phosphate and NAD(P)+ into NAD(P)H. The reduced nicotinamide cofactor NAD(P)H plays a pivotal role in many biochemical oxidation and reduction reactions, thus this enzyme would allow regeneration of NAD(P)H in a microalgae strain over-expressing a NAD(P)H-dependent oxidoreductase. A phosphite dehydrogenase gene was introduced into the chloroplast genome (codon optimized) and nuclear genome of C. reinhardtii by biolistic transformation and electroporation in separate events, respectively. Successful expression of the heterologous protein was confirmed by transcript analysis and protein analysis. In conclusion, this new method represents a useful genetic tool in the construction and integration of complex biochemical pathways into the chloroplast or nuclear genome of microalgae, and this should aid current efforts to engineer algae for recombinant protein expression, biofuels production and production of other desirable natural products.

High throughput gene expression profiling: a molecular approach to integrative physiology

PubMed Central

Liang, Mingyu; Cowley, Allen W; Greene, Andrew S

2004-01-01

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487

Sig2BioPAX: Java tool for converting flat files to BioPAX Level 3 format.

PubMed

Webb, Ryan L; Ma'ayan, Avi

2011-03-21

The World Wide Web plays a critical role in enabling molecular, cell, systems and computational biologists to exchange, search, visualize, integrate, and analyze experimental data. Such efforts can be further enhanced through the development of semantic web concepts. The semantic web idea is to enable machines to understand data through the development of protocol free data exchange formats such as Resource Description Framework (RDF) and the Web Ontology Language (OWL). These standards provide formal descriptors of objects, object properties and their relationships within a specific knowledge domain. However, the overhead of converting datasets typically stored in data tables such as Excel, text or PDF into RDF or OWL formats is not trivial for non-specialists and as such produces a barrier to seamless data exchange between researchers, databases and analysis tools. This problem is particularly of importance in the field of network systems biology where biochemical interactions between genes and their protein products are abstracted to networks. For the purpose of converting biochemical interactions into the BioPAX format, which is the leading standard developed by the computational systems biology community, we developed an open-source command line tool that takes as input tabular data describing different types of molecular biochemical interactions. The tool converts such interactions into the BioPAX level 3 OWL format. We used the tool to convert several existing and new mammalian networks of protein interactions, signalling pathways, and transcriptional regulatory networks into BioPAX. Some of these networks were deposited into PathwayCommons, a repository for consolidating and organizing biochemical networks. The software tool Sig2BioPAX is a resource that enables experimental and computational systems biologists to contribute their identified networks and pathways of molecular interactions for integration and reuse with the rest of the research community.

An integrated pathway system modeling of Saccharomyces cerevisiae HOG pathway: a Petri net based approach.

PubMed

Tomar, Namrata; Choudhury, Olivia; Chakrabarty, Ankush; De, Rajat K

2013-02-01

Biochemical networks comprise many diverse components and interactions between them. It has intracellular signaling, metabolic and gene regulatory pathways which are highly integrated and whose responses are elicited by extracellular actions. Previous modeling techniques mostly consider each pathway independently without focusing on the interrelation of these which actually functions as a single system. In this paper, we propose an approach of modeling an integrated pathway using an event-driven modeling tool, i.e., Petri nets (PNs). PNs have the ability to simulate the dynamics of the system with high levels of accuracy. The integrated set of signaling, regulatory and metabolic reactions involved in Saccharomyces cerevisiae's HOG pathway has been collected from the literature. The kinetic parameter values have been used for transition firings. The dynamics of the system has been simulated and the concentrations of major biological species over time have been observed. The phenotypic characteristics of the integrated system have been investigated under two conditions, viz., under the absence and presence of osmotic pressure. The results have been validated favorably with the existing experimental results. We have also compared our study with the study of idFBA (Lee et al., PLoS Comput Biol 4:e1000-e1086, 2008) and pointed out the differences between both studies. We have simulated and monitored concentrations of multiple biological entities over time and also incorporated feedback inhibition by Ptp2 which has not been included in the idFBA study. We have concluded that our study is the first to the best of our knowledge to model signaling, metabolic and regulatory events in an integrated form through PN model framework. This study is useful in computational simulation of system dynamics for integrated pathways as there are growing evidences that the malfunctioning of the interplay among these pathways is associated with disease.

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

Interpreter of maladies: redescription mining applied to biomedical data analysis.

PubMed

Waltman, Peter; Pearlman, Alex; Mishra, Bud

2006-04-01

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Tools for visually exploring biological networks.

PubMed

Suderman, Matthew; Hallett, Michael

2007-10-15

Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. Supplementary data are available at Bioinformatics online.

Systems for implementing best practice for a chronic disease: management of osteoarthritis of the hip and knee.

PubMed

Brand, C; Cox, S

2006-03-01

Effective implementation of evidence-based care has been associated with better health outcomes; however, evidence-based clinical practice guidelines have been used with varying success. This study aimed to develop integrative tools to support implementation of best practice recommendations for nonsurgical management of osteoarthritis (OA) of the hip and knee and to identify barriers to effective implementation. Published, peer reviewed clinical practice guidelines were updated and translated into an OA care pathway. Key decision nodes in the pathway were identified by a Multidisciplinary Working Group. Qualitative research methods were used to inform pathway development and to identify barriers and enablers for pathway implementation. Qualitative components included purposively selected stakeholder focus groups, key informant interviews and patient process mapping of 10 patient journeys in different settings over a 3-month period. All interviews, facilitated by a trained project officer, were semistructured, recorded, then thematically analysed and summarized. An OA care pathway, clinician and patient toolkits were developed that met the needs of multidisciplinary end-users. Several system- and setting-specific barriers to pathway implementation were identified. Opportunities to improve patient access, interprofessional communication, patient information and education and continuity of care processes were identified. Integrative tools for implementation of best evidence care for patients with OA of the hip and knee were tailored to end-user needs and preferences. Multiple barriers exist that potentially limit effective implementation of best evidence. Comprehensive assessment of barriers and enablers to effective guideline or pathway implementation is recommended before implementation and evaluation.

Comparative genome analysis in the integrated microbial genomes (IMG) system.

PubMed

Markowitz, Victor M; Kyrpides, Nikos C

2007-01-01

Comparative genome analysis is critical for the effective exploration of a rapidly growing number of complete and draft sequences for microbial genomes. The Integrated Microbial Genomes (IMG) system (img.jgi.doe.gov) has been developed as a community resource that provides support for comparative analysis of microbial genomes in an integrated context. IMG allows users to navigate the multidimensional microbial genome data space and focus their analysis on a subset of genes, genomes, and functions of interest. IMG provides graphical viewers, summaries, and occurrence profile tools for comparing genes, pathways, and functions (terms) across specific genomes. Genes can be further examined using gene neighborhoods and compared with sequence alignment tools.

EuPathDB: the eukaryotic pathogen genomics database resource

PubMed Central

Aurrecoechea, Cristina; Barreto, Ana; Basenko, Evelina Y.; Brestelli, John; Brunk, Brian P.; Cade, Shon; Crouch, Kathryn; Doherty, Ryan; Falke, Dave; Fischer, Steve; Gajria, Bindu; Harb, Omar S.; Heiges, Mark; Hertz-Fowler, Christiane; Hu, Sufen; Iodice, John; Kissinger, Jessica C.; Lawrence, Cris; Li, Wei; Pinney, Deborah F.; Pulman, Jane A.; Roos, David S.; Shanmugasundram, Achchuthan; Silva-Franco, Fatima; Steinbiss, Sascha; Stoeckert, Christian J.; Spruill, Drew; Wang, Haiming; Warrenfeltz, Susanne; Zheng, Jie

2017-01-01

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host–pathogen interactions. PMID:27903906

Integrating mass spectrometry and genomics for cyanobacterial metabolite discovery

PubMed Central

Bertin, Matthew J.; Kleigrewe, Karin; Leão, Tiago F.; Gerwick, Lena

2016-01-01

Filamentous marine cyanobacteria produce bioactive natural products with both potential therapeutic value and capacity to be harmful to human health. Genome sequencing has revealed that cyanobacteria have the capacity to produce many more secondary metabolites than have been characterized. The biosynthetic pathways that encode cyanobacterial natural products are mostly uncharacterized, and lack of cyanobacterial genetic tools has largely prevented their heterologous expression. Hence, a combination of cutting edge and traditional techniques has been required to elucidate their secondary metabolite biosynthetic pathways. Here, we review the discovery and refined biochemical understanding of the olefin synthase and fatty acid ACP reductase/aldehyde deformylating oxygenase pathways to hydrocarbons, and the curacin A, jamaicamide A, lyngbyabellin, columbamide, and a trans-acyltransferase macrolactone pathway encoding phormidolide. We integrate into this discussion the use of genomics, mass spectrometric networking, biochemical characterization, and isolation and structure elucidation techniques. PMID:26578313

Wound care clinical pathway: a conceptual model.

PubMed

Barr, J E; Cuzzell, J

1996-08-01

A clinical pathway is a written sequence of clinical processes or events that guides a patient with a defined problem toward an expected outcome. Clinical pathways are tools to assist with the cost-effective management of clinical outcomes related to specific problems or disease processes. The primary obstacles to developing clinical pathways for wound care are the chronic natures of some wounds and the many variables that can delay healing. The pathway introduced in this article was modeled upon the three phases of tissue repair: inflammatory, proliferative, and maturation. This physiology-based model allows clinicians to identify and monitor outcomes based on observable and measurable clinical parameters. The pathway design, which also includes educational and behavioral outcomes, allows the clinician to individualize the expected timeframe for outcome achievement based on individual patient criteria and expert judgement. Integral to the pathway are the "4P's" which help standardize the clinical processes by wound type: Protocols, Policies, Procedures, and Patient education tools. Four categories into which variances are categorized based on the cause of the deviation from the norm are patient, process/system, practitioner, and planning/discharge. Additional research is warranted to support the value of this clinical pathway in the clinical arena.

Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa.

PubMed

Nag, Ambarish; Karpinets, Tatiana V; Chang, Christopher H; Bar-Peled, Maor

2012-01-01

Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s). Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES.

Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa

PubMed Central

Nag, Ambarish; Karpinets, Tatiana V.; Chang, Christopher H.; Bar-Peled, Maor

2012-01-01

Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s). Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES. PMID:22465851

Integrative care for the management of low back pain: use of a clinical care pathway.

PubMed

Maiers, Michele J; Westrom, Kristine K; Legendre, Claire G; Bronfort, Gert

2010-10-29

For the treatment of chronic back pain, it has been theorized that integrative care plans can lead to better outcomes than those achieved by monodisciplinary care alone, especially when using a collaborative, interdisciplinary, and non-hierarchical team approach. This paper describes the use of a care pathway designed to guide treatment by an integrative group of providers within a randomized controlled trial. A clinical care pathway was used by a multidisciplinary group of providers, which included acupuncturists, chiropractors, cognitive behavioral therapists, exercise therapists, massage therapists and primary care physicians. Treatment recommendations were based on an evidence-informed practice model, and reached by group consensus. Research study participants were empowered to select one of the treatment recommendations proposed by the integrative group. Common principles and benchmarks were established to guide treatment management throughout the study. Thirteen providers representing 5 healthcare professions collaborated to provide integrative care to study participants. On average, 3 to 4 treatment plans, each consisting of 2 to 3 modalities, were recommended to study participants. Exercise, massage, and acupuncture were both most commonly recommended by the team and selected by study participants. Changes to care commonly incorporated cognitive behavioral therapy into treatment plans. This clinical care pathway was a useful tool for the consistent application of evidence-based care for low back pain in the context of an integrative setting. ClinicalTrials.gov NCT00567333.

LENS: web-based lens for enrichment and network studies of human proteins

PubMed Central

2015-01-01

Background Network analysis is a common approach for the study of genetic view of diseases and biological pathways. Typically, when a set of genes are identified to be of interest in relation to a disease, say through a genome wide association study (GWAS) or a different gene expression study, these genes are typically analyzed in the context of their protein-protein interaction (PPI) networks. Further analysis is carried out to compute the enrichment of known pathways and disease-associations in the network. Having tools for such analysis at the fingertips of biologists without the requirement for computer programming or curation of data would accelerate the characterization of genes of interest. Currently available tools do not integrate network and enrichment analysis and their visualizations, and most of them present results in formats not most conducive to human cognition. Results We developed the tool Lens for Enrichment and Network Studies of human proteins (LENS) that performs network and pathway and diseases enrichment analyses on genes of interest to users. The tool creates a visualization of the network, provides easy to read statistics on network connectivity, and displays Venn diagrams with statistical significance values of the network's association with drugs, diseases, pathways, and GWASs. We used the tool to analyze gene sets related to craniofacial development, autism, and schizophrenia. Conclusion LENS is a web-based tool that does not require and download or plugins to use. The tool is free and does not require login for use, and is available at http://severus.dbmi.pitt.edu/LENS. PMID:26680011

Lynx web services for annotations and systems analysis of multi-gene disorders.

PubMed

Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

2014-07-01

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

PubMed

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

Modelling the urban water cycle as an integrated part of the city: a review.

PubMed

Urich, Christian; Rauch, Wolfgang

2014-01-01

In contrast to common perceptions, the urban water infrastructure system is a complex and dynamic system that is constantly evolving and adapting to changes in the urban environment, to sustain existing services and provide additional ones. Instead of simplifying urban water infrastructure to a static system that is decoupled from its urban context, new management strategies use the complexity of the system to their advantage by integrating centralised with decentralised solutions and explicitly embedding water systems into their urban form. However, to understand and test possible adaptation strategies, urban water modelling tools are required to support exploration of their effectiveness as the human-technology-environment system coevolves under different future scenarios. The urban water modelling community has taken first steps to developing these new modelling tools. This paper critically reviews the historical development of urban water modelling tools and provides a summary of the current state of integrated modelling approaches. It reflects on the challenges that arise through the current practice of coupling urban water management tools with urban development models and discusses a potential pathway towards a new generation of modelling tools.

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

PubMed

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web at http://spirpro.sbi.kmutt.ac.th . SpirPro is an analysis platform containing an integrated proteome and PPI database that provides the most comprehensive data on this cyanobacterium at the systematic level. As an integrated database, SpirPro can be applied in various analyses, such as temperature stress response networking analysis in cyanobacterial models and interacting domain-domain analysis between proteins of interest.

MESSI: metabolic engineering target selection and best strain identification tool.

PubMed

Kang, Kang; Li, Jun; Lim, Boon Leong; Panagiotou, Gianni

2015-01-01

Metabolic engineering and synthetic biology are synergistically related fields for manipulating target pathways and designing microorganisms that can act as chemical factories. Saccharomyces cerevisiae's ideal bioprocessing traits make yeast a very attractive chemical factory for production of fuels, pharmaceuticals, nutraceuticals as well as a wide range of chemicals. However, future attempts of engineering S. cerevisiae's metabolism using synthetic biology need to move towards more integrative models that incorporate the high connectivity of metabolic pathways and regulatory processes and the interactions in genetic elements across those pathways and processes. To contribute in this direction, we have developed Metabolic Engineering target Selection and best Strain Identification tool (MESSI), a web server for predicting efficient chassis and regulatory components for yeast bio-based production. The server provides an integrative platform for users to analyse ready-to-use public high-throughput metabolomic data, which are transformed to metabolic pathway activities for identifying the most efficient S. cerevisiae strain for the production of a compound of interest. As input MESSI accepts metabolite KEGG IDs or pathway names. MESSI outputs a ranked list of S. cerevisiae strains based on aggregation algorithms. Furthermore, through a genome-wide association study of the metabolic pathway activities with the strains' natural variation, MESSI prioritizes genes and small variants as potential regulatory points and promising metabolic engineering targets. Users can choose various parameters in the whole process such as (i) weight and expectation of each metabolic pathway activity in the final ranking of the strains, (ii) Weighted AddScore Fuse or Weighted Borda Fuse aggregation algorithm, (iii) type of variants to be included, (iv) variant sets in different biological levels.Database URL: http://sbb.hku.hk/MESSI/. © The Author(s) 2015. Published by Oxford University Press.

SWITCH: a dynamic CRISPR tool for genome engineering and metabolic pathway control for cell factory construction in Saccharomyces cerevisiae.

PubMed

Vanegas, Katherina García; Lehka, Beata Joanna; Mortensen, Uffe Hasbro

2017-02-08

The yeast Saccharomyces cerevisiae is increasingly used as a cell factory. However, cell factory construction time is a major obstacle towards using yeast for bio-production. Hence, tools to speed up cell factory construction are desirable. In this study, we have developed a new Cas9/dCas9 based system, SWITCH, which allows Saccharomyces cerevisiae strains to iteratively alternate between a genetic engineering state and a pathway control state. Since Cas9 induced recombination events are crucial for SWITCH efficiency, we first developed a technique TAPE, which we have successfully used to address protospacer efficiency. As proof of concept of the use of SWITCH in cell factory construction, we have exploited the genetic engineering state of a SWITCH strain to insert the five genes necessary for naringenin production. Next, the naringenin cell factory was switched to the pathway control state where production was optimized by downregulating an essential gene TSC13, hence, reducing formation of a byproduct. We have successfully integrated two CRISPR tools, one for genetic engineering and one for pathway control, into one system and successfully used it for cell factory construction.

Integrated omics analysis of specialized metabolism in medicinal plants.

PubMed

Rai, Amit; Saito, Kazuki; Yamazaki, Mami

2017-05-01

Medicinal plants are a rich source of highly diverse specialized metabolites with important pharmacological properties. Until recently, plant biologists were limited in their ability to explore the biosynthetic pathways of these metabolites, mainly due to the scarcity of plant genomics resources. However, recent advances in high-throughput large-scale analytical methods have enabled plant biologists to discover biosynthetic pathways for important plant-based medicinal metabolites. The reduced cost of generating omics datasets and the development of computational tools for their analysis and integration have led to the elucidation of biosynthetic pathways of several bioactive metabolites of plant origin. These discoveries have inspired synthetic biology approaches to develop microbial systems to produce bioactive metabolites originating from plants, an alternative sustainable source of medicinally important chemicals. Since the demand for medicinal compounds are increasing with the world's population, understanding the complete biosynthesis of specialized metabolites becomes important to identify or develop reliable sources in the future. Here, we review the contributions of major omics approaches and their integration to our understanding of the biosynthetic pathways of bioactive metabolites. We briefly discuss different approaches for integrating omics datasets to extract biologically relevant knowledge and the application of omics datasets in the construction and reconstruction of metabolic models. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Multimedia-modeling integration development environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pelton, Mitchell A.; Hoopes, Bonnie L.

2002-09-02

There are many framework systems available; however, the purpose of the framework presented here is to capitalize on the successes of the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) and Multi-media Multi-pathway Multi-receptor Risk Assessment (3MRA) methodology as applied to the Hazardous Waste Identification Rule (HWIR) while focusing on the development of software tools to simplify the module developer?s effort of integrating a module into the framework.

Application of adverse outcome pathway-based tools to ambient water quality criteria development

EPA Science Inventory

Increasing numbers and diversity of chemical contaminants are being detected in ambient surface waters. States, regions, and communities across the US are faced with the issue of understanding which chemicals may warrant concern and at what concentrations. Integrating new scienti...

Biological interpretation of genome-wide association studies using predicted gene functions.

PubMed

Pers, Tune H; Karjalainen, Juha M; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R; Yang, Jian; Lui, Julian C; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S N; Hirschhorn, Joel N; Franke, Lude

2015-01-19

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

An integrated workflow for analysis of ChIP-chip data.

PubMed

Weigelt, Karin; Moehle, Christoph; Stempfl, Thomas; Weber, Bernhard; Langmann, Thomas

2008-08-01

Although ChIP-chip is a powerful tool for genome-wide discovery of transcription factor target genes, the steps involving raw data analysis, identification of promoters, and correlation with binding sites are still laborious processes. Therefore, we report an integrated workflow for the analysis of promoter tiling arrays with the Genomatix ChipInspector system. We compare this tool with open-source software packages to identify PU.1 regulated genes in mouse macrophages. Our results suggest that ChipInspector data analysis, comparative genomics for binding site prediction, and pathway/network modeling significantly facilitate and enhance whole-genome promoter profiling to reveal in vivo sites of transcription factor-DNA interactions.

Care pathways as boundary objects between primary and secondary care: Experiences from Norwegian home care services.

PubMed

Håland, Erna; Røsstad, Tove; Osmundsen, Tonje C

2015-11-01

The need for integration of healthcare services and collaboration across organisational boundaries is highlighted as a major challenge within healthcare in many countries. Care pathways are often presented as a solution to this challenge. In this article, we study a project of developing, introducing and using a care pathway across healthcare levels focusing on older home-dwelling patients in need of home care services after hospital discharge. In so doing, we use the concept of boundary object, as described by Star and Griesemer, to explore how care pathways can act as tools for translation between specialist healthcare services and home care services. Based on interviews with participants in the project, we find that response to existing needs, local tailoring, involvement and commitment are all crucial for the care pathway to function as a boundary object in this setting. Furthermore, the care pathway, as we argue, can be used to push boundaries just as much as it can be used as a tool for bridging across them, thus potentially contributing to a more equal relationship between specialist healthcare services and home care services. © The Author(s) 2015.

Challenges in horizontal model integration.

PubMed

Kolczyk, Katrin; Conradi, Carsten

2016-03-11

Systems Biology has motivated dynamic models of important intracellular processes at the pathway level, for example, in signal transduction and cell cycle control. To answer important biomedical questions, however, one has to go beyond the study of isolated pathways towards the joint study of interacting signaling pathways or the joint study of signal transduction and cell cycle control. Thereby the reuse of established models is preferable, as it will generally reduce the modeling effort and increase the acceptance of the combined model in the field. Obtaining a combined model can be challenging, especially if the submodels are large and/or come from different working groups (as is generally the case, when models stored in established repositories are used). To support this task, we describe a semi-automatic workflow based on established software tools. In particular, two frequent challenges are described: identification of the overlap and subsequent (re)parameterization of the integrated model. The reparameterization step is crucial, if the goal is to obtain a model that can reproduce the data explained by the individual models. For demonstration purposes we apply our workflow to integrate two signaling pathways (EGF and NGF) from the BioModels Database.

An economic evaluation of an integrated care pathway in geriatric rehabilitation for older patients with complex health problems

PubMed Central

van Haastregt, Jolanda C. M.; Evers, Silvia M. A. A.; Kempen, Gertrudis I. J. M.; Schols, Jos M. G. A.

2018-01-01

Background Integrated care pathways which cover multiple care settings are increasingly used as a tool to structure care, enhance coordination and improve transitions between care settings. However, little is known about their economic impact. The objective of this study is to determine the cost-effectiveness and cost-utility of an integrated care pathway designed for patients with complex health problems transferring from the hospital, a geriatric rehabilitation facility and primary care. Methods This economic evaluation was performed from a societal perspective alongside a prospective cohort study with two cohorts of patients. The care as usual cohort was included before implementation of the pathway and the care pathway cohort after implementation of the pathway. Both cohorts were measured over nine months, during which intervention costs, healthcare costs, patient and family costs were identified. The outcome measures were dependence in activities of daily living (measured with the KATZ-15) and quality adjusted life years (EQ-5D-3L). Costs and effects were bootstrapped and various sensitivity analyses were performed to assess robustness of the results. Results After nine months, the average societal costs were significantly lower for patients in the care pathway cohort (€50,791) versus patients in the care as usual cohort (€62,170; CI = -22,090, -988). Patients in the care pathway cohort had better scores on the KATZ-15 (1.04), indicating cost-effectiveness. No significant differences were found between the two groups on QALY scores (0.01). Conclusions The results of this study indicate that the integrated care pathway is a cost-effective intervention. Therefore, dissemination of the integrated care pathway on a wider scale could be considered. This would provide us the opportunity to confirm the findings of our study in larger economic evaluations. When looking at QALYs, no effects were found. Therefore, it is also recommended to explore if therapy in geriatric rehabilitation could also pay attention to other quality of life-related domains, such as mood and social participation. PMID:29489820

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.

Synthetic biology projects in vitro.

PubMed

Forster, Anthony C; Church, George M

2007-01-01

Advances in the in vitro synthesis and evolution of DNA, RNA, and polypeptides are accelerating the construction of biopolymers, pathways, and organisms with novel functions. Known functions are being integrated and debugged with the aim of synthesizing life-like systems. The goals are knowledge, tools, smart materials, and therapies.

Integrating Continuing Professional Development With Health System Reform: Building Pillars of Support.

PubMed

Davis, David A; Rayburn, William F

2016-01-01

Clinical failures sparked a widespread desire for health system reform at the beginning of the 21st century, but related efforts have resulted in changes that are either slow or nonexistent. In response, academic medicine has moved in two directions: (1) system-wide reform using electronic health records, practice networks, and widespread data applications (a macro pathway); and (2) professional development of individual clinicians through continuous performance improvement (a micro pathway). Both pathways exist to improve patient care and population health, yet each suffers from limitations in widespread implementation. The authors call for a better union between these two parallel pathways through four pillars of support: (1) an acknowledgment that both pathways are essential to each other and to the final outcome they intend to achieve, (2) a strong faculty commitment to educate about quality improvement and patient safety at all education levels, (3) a reengineering of tools for professional development to serve as effective change agents, and (4) the development of standards to sustain this alignment of pathways. With these pillars of support integrating continuing professional development with health system reform, the authors envision a better functioning system, with improved metrics and value to enhance patient care and population health.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example

PubMed Central

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F.; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C.

2017-01-01

Background Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Objective Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Methods Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson’s disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Results Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Conclusion Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation. PMID:28441410

Biological interpretation of genome-wide association studies using predicted gene functions

PubMed Central

Pers, Tune H.; Karjalainen, Juha M.; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R.; Yang, Jian; Lui, Julian C.; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K.; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S.N.; Hirschhorn, Joel N.; Franke, Lude

2015-01-01

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. PMID:25597830

Applying behavioral science to behavior change communication: the pathways to change tools.

PubMed

Petraglia, Joseph; Galavotti, Christine; Harford, Nicola; Pappas-DeLuca, Katina A; Mooki, Maungo

2007-10-01

Entertainment-education (EE) is a popular vehicle for behavior change communication (BCC) in many areas of public health, especially in the developing world where soap operas and other serial drama formats play a central role in encouraging people to avoid risky behavior. Yet BCC/EE developers have been largely unable to integrate behavioral theory and research systematically into storylines and scripts, depending instead on external, technical oversight of what should be an essentially local, creative process. This article describes how the Modeling and Reinforcement to Combat HIV/AIDS project at the Centers for Disease Control and Prevention has developed a set of tools through which creative writers can exercise greater control over the behavioral content of their stories. The Pathways to Change tools both guide scriptwriters as they write BCC/EE storylines and help project managers monitor BCC/EE products for theoretical fidelity and sensitivity to research.

Operational integration in primary health care: patient encounters and workflows.

PubMed

Sifaki-Pistolla, Dimitra; Chatzea, Vasiliki-Eirini; Markaki, Adelais; Kritikos, Kyriakos; Petelos, Elena; Lionis, Christos

2017-11-29

Despite several countrywide attempts to strengthen and standardise the primary healthcare (PHC) system, Greece is still lacking a sustainable, policy-based model of integrated services. The aim of our study was to identify operational integration levels through existing patient care pathways and to recommend an alternative PHC model for optimum integration. The study was part of a large state-funded project, which included 22 randomly selected PHC units located across two health regions of Greece. Dimensions of operational integration in PHC were selected based on the work of Kringos and colleagues. A five-point Likert-type scale, coupled with an algorithm, was used to capture and transform theoretical framework features into measurable attributes. PHC services were grouped under the main categories of chronic care, urgent/acute care, preventive care, and home care. A web-based platform was used to assess patient pathways, evaluate integration levels and propose improvement actions. Analysis relied on a comparison of actual pathways versus optimal, the latter ones having been identified through literature review. Overall integration varied among units. The majority (57%) of units corresponded to a basic level. Integration by type of PHC service ranged as follows: basic (86%) or poor (14%) for chronic care units, poor (78%) or basic (22%) for urgent/acute care units, basic (50%) for preventive care units, and partial or basic (50%) for home care units. The actual pathways across all four categories of PHC services differed from those captured in the optimum integration model. Certain similarities were observed in the operational flows between chronic care management and urgent/acute care management. Such similarities were present at the highest level of abstraction, but also in common steps along the operational flows. Existing patient care pathways were mapped and analysed, and recommendations for an optimum integration PHC model were made. The developed web platform, based on a strong theoretical framework, can serve as a robust integration evaluation tool. This could be a first step towards restructuring and improving PHC services within a financially restrained environment.

miRnalyze: an interactive database linking tool to unlock intuitive microRNA regulation of cell signaling pathways

PubMed Central

Subhra Das, Sankha; James, Mithun; Paul, Sandip

2017-01-01

Abstract The various pathophysiological processes occurring in living systems are known to be orchestrated by delicate interplays and cross-talks between different genes and their regulators. Among the various regulators of genes, there is a class of small non-coding RNA molecules known as microRNAs. Although, the relative simplicity of miRNAs and their ability to modulate cellular processes make them attractive therapeutic candidates, their presence in large numbers make it challenging for experimental researchers to interpret the intricacies of the molecular processes they regulate. Most of the existing bioinformatic tools fail to address these challenges. Here, we present a new web resource ‘miRnalyze’ that has been specifically designed to directly identify the putative regulation of cell signaling pathways by miRNAs. The tool integrates miRNA-target predictions with signaling cascade members by utilizing TargetScanHuman 7.1 miRNA-target prediction tool and the KEGG pathway database, and thus provides researchers with in-depth insights into modulation of signal transduction pathways by miRNAs. miRnalyze is capable of identifying common miRNAs targeting more than one gene in the same signaling pathway—a feature that further increases the probability of modulating the pathway and downstream reactions when using miRNA modulators. Additionally, miRnalyze can sort miRNAs according to the seed-match types and TargetScan Context ++ score, thus providing a hierarchical list of most valuable miRNAs. Furthermore, in order to provide users with comprehensive information regarding miRNAs, genes and pathways, miRnalyze also links to expression data of miRNAs (miRmine) and genes (TiGER) and proteome abundance (PaxDb) data. To validate the capability of the tool, we have documented the correlation of miRnalyze’s prediction with experimental confirmation studies. Database URL: http://www.mirnalyze.in PMID:28365733

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

PubMed

Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence–Function Space and Genome Context to Discover Novel Functions

PubMed Central

2017-01-01

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of “genomic enzymology” web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence–function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems. PMID:28826221

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

The Peroxide Pathway

NASA Technical Reports Server (NTRS)

McNeal, Curtis I., Jr.; Anderson, William

1999-01-01

NASA's current focus on technology roadmaps as a tool for guiding investment decisions leads naturally to a discussion of NASA's roadmap for peroxide propulsion system development. NASA's new Second Generation Space Transportation System roadmap calls for an integrated Reusable Upper-Stage (RUS) engine technology demonstration in the FY03/FY04 time period. Preceding this integrated demonstration are several years of component developments and subsystem technology demonstrations. NASA and the Air Force took the first steps at developing focused upper stage technologies with the initiation of the Upper Stage Flight Experiment with Orbital Sciences in December 1997. A review of this program's peroxide propulsion development is a useful first step in establishing the peroxide propulsion pathway that could lead to a RUS demonstration in 2004.

SPIKE – a database, visualization and analysis tool of cellular signaling pathways

PubMed Central

Elkon, Ran; Vesterman, Rita; Amit, Nira; Ulitsky, Igor; Zohar, Idan; Weisz, Mali; Mass, Gilad; Orlev, Nir; Sternberg, Giora; Blekhman, Ran; Assa, Jackie; Shiloh, Yosef; Shamir, Ron

2008-01-01

Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data. PMID:18289391

PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data.

PubMed

Hernández-de-Diego, Rafael; Tarazona, Sonia; Martínez-Mira, Carlos; Balzano-Nogueira, Leandro; Furió-Tarí, Pedro; Pappas, Georgios J; Conesa, Ana

2018-05-25

The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological discoveries. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a comprehensive pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, and more. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at www.paintomics.org.

The chloroplast signal recognition particle (CpSRP) pathway as a tool to minimize chlorophyll antenna size and maximize photosynthetic productivity.

PubMed

Kirst, Henning; Melis, Anastasios

2014-01-01

The concept of the Truncated Light-harvesting chlorophyll Antenna (TLA) size, as a tool by which to maximize sunlight utilization and photosynthetic productivity in microalgal mass cultures or high-density plant canopies, is discussed. TLA technology is known to improve sunlight-to-product energy conversion efficiencies and is hereby exemplified by photosynthetic productivity estimates of wild type and a TLA strain under simulated mass culture conditions. Recent advances in the generation of TLA-type mutants by targeting genes of the chloroplast signal-recognition particle (CpSRP) pathway, affecting the thylakoid membrane assembly of light-harvesting proteins, are also summarized. Two distinct CpSRP assembly pathways are recognized, one entailing post-translational, the other a co-translational mechanism. Differences between the post-translational and co-translational integration mechanisms are outlined, as these pertain to the CpSRP-mediated assembly of thylakoid membrane protein complexes in higher plants and green microalgae. The applicability of the CpSRP pathway genes in efforts to generate TLA-type strains with enhanced solar energy conversion efficiency in photosynthesis is evaluated. © 2013.

PathCase-SB architecture and database design

PubMed Central

2011-01-01

Background Integration of metabolic pathways resources and regulatory metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation in metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks. Description PathCase Systems Biology (PathCase-SB) is built and released. The PathCase-SB database provides data and API for multiple user interfaces and software tools. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate data of selected biological data sources on the web (currently, BioModels database and KEGG), and to provide more powerful and/or new capabilities via the new web-based integrative framework. This paper describes architecture and database design issues encountered in PathCase-SB's design and implementation, and presents the current design of PathCase-SB's architecture and database. Conclusions PathCase-SB architecture and database provide a highly extensible and scalable environment with easy and fast (real-time) access to the data in the database. PathCase-SB itself is already being used by researchers across the world. PMID:22070889

Ecological Models to Predict and Test the Effects of Chemical Stressors: Integration across 2 EPA STAR cooperative agreements

EPA Science Inventory

Accessible tools to quantify adverse outcomes pathways (AOPs) that can predict the ecological effects of chemicals and other stressors are a major goal of Chemical Safety and Sustainability research within US EPA’s Office of Research and Development. To address this goal, w...

A Microarray Tool Provides Pathway and GO Term Analysis.

PubMed

Koch, Martin; Royer, Hans-Dieter; Wiese, Michael

2011-12-01

Analysis of gene expression profiles is no longer exclusively a task for bioinformatic experts. However, gaining statistically significant results is challenging and requires both biological knowledge and computational know-how. Here we present a novel, user-friendly microarray reporting tool called maRt. The software provides access to bioinformatic resources, like gene ontology terms and biological pathways by use of the DAVID and the BioMart web-service. Results are summarized in structured HTML reports, each presenting a different layer of information. In these report, contents of diverse sources are integrated and interlinked. To speed up processing, maRt takes advantage of the multi-core technology of modern desktop computers by using parallel processing. Since the software is built upon a RCP infrastructure it might be an outset for developers aiming to integrate novel R based applications. Installer, documentation and various kinds of tutorials are available under LGPL license at the website of our institute http://www.pharma.uni-bonn.de/www/mart. This software is free for academic use. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Electronic Risk Assessment System as an Appropriate Tool for the Prevention of Cancer: a Qualitative Study.

PubMed

Javan Amoli, Amir Hossein; Maserat, Elham; Safdari, Reza; Zali, Mohammad Reza

2015-01-01

Decision making modalities for screening for many cancer conditions and different stages have become increasingly complex. Computer-based risk assessment systems facilitate scheduling and decision making and support the delivery of cancer screening services. The aim of this article was to survey electronic risk assessment system as an appropriate tool for the prevention of cancer. A qualitative design was used involving 21 face-to-face interviews. Interviewing involved asking questions and getting answers from exclusive managers of cancer screening. Of the participants 6 were female and 15 were male, and ages ranged from 32 to 78 years. The study was based on a grounded theory approach and the tool was a semi- structured interview. Researchers studied 5 dimensions, comprising electronic guideline standards of colorectal cancer screening, work flow of clinical and genetic activities, pathways of colorectal cancer screening and functionality of computer based guidelines and barriers. Electronic guideline standards of colorectal cancer screening were described in the s3 categories of content standard, telecommunications and technical standards and nomenclature and classification standards. According to the participations' views, workflow and genetic pathways of colorectal cancer screening were identified. The study demonstrated an effective role of computer-guided consultation for screening management. Electronic based systems facilitate real-time decision making during a clinical interaction. Electronic pathways have been applied for clinical and genetic decision support, workflow management, update recommendation and resource estimates. A suitable technical and clinical infrastructure is an integral part of clinical practice guidline of screening. As a conclusion, it is recommended to consider the necessity of architecture assessment and also integration standards.

Revealing pathways from payments for ecosystem services to socioeconomic outcomes

PubMed Central

Zhang, Jindong

2018-01-01

Payments for ecosystem services (PES) programs have been widely implemented as a promising tool to conserve ecosystems while facilitating socioeconomic development. However, the underlying pathways (or processes) through which PES programs affect socioeconomic outcomes remain elusive, and existing literature provides little guidance to quantify them. By integrating linkages among PES programs, livelihood activities, and socioeconomic outcomes, we develop a framework to reveal pathways from PES programs to socioeconomic outcomes. We empirically demonstrate the framework’s operationalization and uncover the pathways that lead to unexpected negative effects of two important PES programs on participating households’ income. With improved understanding of the pathways (for example, the programs decreased income through reducing crop production), we provide recommendations to enhance the PES programs’ outcomes in our demonstration site and beyond. Our study highlights the finding that elucidating the pathways from PES programs to their outcomes can help identify specific strategies to achieve ecosystem conservation and socioeconomic development simultaneously. PMID:29750187

Redesigning service delivery for hypertensive patients: a methodological guideline to improve the management of chronic diseases.

PubMed

Ippolito, Adelaide; Cannavacciuolo, Lorella; Ponsiglione, Cristina; De Luca, Nicola; Iaccarino, Guido; Illario, Maddalena

2014-04-01

Best care is not necessarily the most expensive, but the most appropriate, and prevention is the most powerful tool to promote health. A novel approach might envision the reduction of hospital admittance (thus meeting a requirement from long term condition patients: they would rather not being hospitalized!) and the enforcement of peripheral (both on the territory and at home) assistance. In this direction, experiences of reshaping new service deliveries towards an integrated disease management, namely clinical pathways, can be observed in Europe and in different parts of the world. Aim of this paper is to provide a methodological guideline to support the management in planning clinical pathways, also outlining the main barriers limiting the process. In particular, we present the results of planning a clinical pathway at the Centre for Hypertension of the Federico II University Hospital (Naples, Italy). The case study showed that the introduction of a similar service impacts on the organisation of the structure. An analysis of organizational processes "as are" and the re-design of processes "to be" are necessary to integrate the clinical pathway into the actual activities.

Computational Methods to Assess the Production Potential of Bio-Based Chemicals.

PubMed

Campodonico, Miguel A; Sukumara, Sumesh; Feist, Adam M; Herrgård, Markus J

2018-01-01

Elevated costs and long implementation times of bio-based processes for producing chemicals represent a bottleneck for moving to a bio-based economy. A prospective analysis able to elucidate economically and technically feasible product targets at early research phases is mandatory. Computational tools can be implemented to explore the biological and technical spectrum of feasibility, while constraining the operational space for desired chemicals. In this chapter, two different computational tools for assessing potential for bio-based production of chemicals from different perspectives are described in detail. The first tool is GEM-Path: an algorithm to compute all structurally possible pathways from one target molecule to the host metabolome. The second tool is a framework for Modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes, and economic impact assessment. Integrating GEM-Path and MuSIC will play a vital role in supporting early phases of research efforts and guide the policy makers with decisions, as we progress toward planning a sustainable chemical industry.

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens.

PubMed

Zhou, Hufeng; Jin, Jingjing; Zhang, Haojun; Yi, Bo; Wozniak, Michal; Wong, Limsoon

2012-01-01

Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and relationship errors in KEGG). We turn complicated and incompatible xml data formats and inconsistent gene and gene relationship representations from different source databases into normalized and unified pathway-gene and pathway-gene pair relationships neatly recorded in simple tab-delimited text format and MySQL tables, which facilitates convenient automatic computation and large-scale referencing in many related studies. IntPath data can be downloaded in text format or MySQL dump. IntPath data can also be retrieved and analyzed conveniently through web service by local programs or through web interface by mouse clicks. Several useful analysis tools are also provided in IntPath. We have overcome in IntPath the issues of compatibility, consistency, and comprehensiveness that often hamper effective use of pathway databases. We have included four organisms in the current release of IntPath. Our methodology and programs described in this work can be easily applied to other organisms; and we will include more model organisms and important pathogens in future releases of IntPath. IntPath maintains regular updates and is freely available at http://compbio.ddns.comp.nus.edu.sg:8080/IntPath.

DyNAMiC Workbench: an integrated development environment for dynamic DNA nanotechnology

PubMed Central

Grun, Casey; Werfel, Justin; Zhang, David Yu; Yin, Peng

2015-01-01

Dynamic DNA nanotechnology provides a promising avenue for implementing sophisticated assembly processes, mechanical behaviours, sensing and computation at the nanoscale. However, design of these systems is complex and error-prone, because the need to control the kinetic pathway of a system greatly increases the number of design constraints and possible failure modes for the system. Previous tools have automated some parts of the design workflow, but an integrated solution is lacking. Here, we present software implementing a three ‘tier’ design process: a high-level visual programming language is used to describe systems, a molecular compiler builds a DNA implementation and nucleotide sequences are generated and optimized. Additionally, our software includes tools for analysing and ‘debugging’ the designs in silico, and for importing/exporting designs to other commonly used software systems. The software we present is built on many existing pieces of software, but is integrated into a single package—accessible using a Web-based interface at http://molecular-systems.net/workbench. We hope that the deep integration between tools and the flexibility of this design process will lead to better experimental results, fewer experimental design iterations and the development of more complex DNA nanosystems. PMID:26423437

A computational platform to maintain and migrate manual functional annotations for BioCyc databases.

PubMed

Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A

2014-10-12

BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.

Integration of Nuclear- and Extranuclear-Initiated Estrogen Receptor Signaling in Breast Cancer Cells

ERIC Educational Resources Information Center

Madak Erdogan, Zeynep

2009-01-01

Estrogenic hormones exert their effects through binding to Estrogen Receptors (ERs), which work in concert with coregulators and extranuclear signaling pathways to control gene expression in normal as well as cancerous states, including breast tumors. In this thesis, we have used multiple genome-wide analysis tools to elucidate various ways that…

Systematically Studying Kinase Inhibitor Induced Signaling Network Signatures by Integrating Both Therapeutic and Side Effects

PubMed Central

Shao, Hongwei; Peng, Tao; Ji, Zhiwei; Su, Jing; Zhou, Xiaobo

2013-01-01

Substantial effort in recent years has been devoted to analyzing data based large-scale biological networks, which provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or compounds. In this work, we proposed a novel strategy to investigate kinase inhibitor induced pathway signatures by integrating multiplex data in Library of Integrated Network-based Cellular Signatures (LINCS), e.g. KINOMEscan data and cell proliferation/mitosis imaging data. Using this strategy, we first established a PC9 cell line specific pathway model to investigate the pathway signatures in PC9 cell line when perturbed by a small molecule kinase inhibitor GW843682. This specific pathway revealed the role of PI3K/AKT in modulating the cell proliferation process and the absence of two anti-proliferation links, which indicated a potential mechanism of abnormal expansion in PC9 cell number. Incorporating the pathway model for side effects on primary human hepatocytes, it was used to screen 27 kinase inhibitors in LINCS database and PF02341066, known as Crizotinib, was finally suggested with an optimal concentration 4.6 uM to suppress PC9 cancer cell expansion while avoiding severe damage to primary human hepatocytes. Drug combination analysis revealed that the synergistic effect region can be predicted straightforwardly based on a threshold which is an inherent property of each kinase inhibitor. Furthermore, this integration strategy can be easily extended to other specific cell lines to be a powerful tool for drug screen before clinical trials. PMID:24339888

Traversing the network: a user-led Care Pathway approach to the management of Parkinson's disease in the community.

PubMed

Holloway, Margaret

2006-01-01

This article reports on a pilot study to develop and implement a Care Pathway framework for people with Parkinson's disease (PD) and their carers, to facilitate more comprehensive and integrated health and social care, with a streamlining of the transfer of core information around the system. The pathway is user-led, conceptualising the user/carer as the 'communications centre', resourced and supported in the management of their situation by the professionals to achieve their own integrated package of care. The Care Pathway tools, comprising of a local information pack, a Problems/Needs form, a Clinic Summary and a service record sheet, were designed by a working party consisting of service providers, a service user and carer and the researchers. The use of the framework was evaluated by following the progress of a convenience sample of 22 people with PD over a 12-month period. Beginning and end-point data on patient characteristics, social circumstances, severity of illness, and recent/current use of services were collected. The separate tools and the contribution of the framework to the management of the illness were evaluated through semi-structured interviews with participants and their carers and focused interviews with the participating neurologist and specialist nurse, conducted at the end of the 12-month period. Participants' situations showed very little change overall. The people with PD and their carers were generally enthusiastic about the Care Pathway, particularly the problems/needs form which they felt facilitated their active engagement in their own care. Very few service record forms had been used. The neurologist and specialist nurse were equally enthusiastic, and envisaged that full use of the framework with all service providers participating would greatly improve the overall care of their patients. In conclusion the Care Pathway framework is feasible within normal clinic procedures and improves patients' care. However, its effectiveness in contributing to the better management of the illness overall requires further testing.

Teamwork Assessment Tools in Modern Surgical Practice: A Systematic Review

PubMed Central

Whittaker, George; Abboudi, Hamid; Khan, Muhammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

2015-01-01

Introduction. Deficiencies in teamwork skills have been shown to contribute to the occurrence of adverse events during surgery. Consequently, several teamwork assessment tools have been developed to evaluate trainee nontechnical performance. This paper aims to provide an overview of these instruments and review the validity of each tool. Furthermore, the present paper aims to review the deficiencies surrounding training and propose several recommendations to address these issues. Methods. A systematic literature search was conducted to identify teamwork assessment tools using MEDLINE (1946 to August 2015), EMBASE (1974 to August 2015), and PsycINFO (1806 to August 2015) databases. Results. Eight assessment tools which encompass aspects of teamwork were identified. The Nontechnical Skills for Surgeons (NOTSS) assessment was found to possess the highest level of validity from a variety of sources; reliability and acceptability have also been established for this tool. Conclusions. Deficits in current surgical training pathways have prompted several recommendations to meet the evolving requirements of surgeons. Recommendations from the current paper include integration of teamwork training and assessment into medical school curricula, standardised formal training of assessors to ensure accurate evaluation of nontechnical skill acquisition, and integration of concurrent technical and nontechnical skills training throughout training. PMID:26425732

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

IntPath--an integrated pathway gene relationship database for model organisms and important pathogens

PubMed Central

2012-01-01

Background Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. Results In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and relationship errors in KEGG). We turn complicated and incompatible xml data formats and inconsistent gene and gene relationship representations from different source databases into normalized and unified pathway-gene and pathway-gene pair relationships neatly recorded in simple tab-delimited text format and MySQL tables, which facilitates convenient automatic computation and large-scale referencing in many related studies. IntPath data can be downloaded in text format or MySQL dump. IntPath data can also be retrieved and analyzed conveniently through web service by local programs or through web interface by mouse clicks. Several useful analysis tools are also provided in IntPath. Conclusions We have overcome in IntPath the issues of compatibility, consistency, and comprehensiveness that often hamper effective use of pathway databases. We have included four organisms in the current release of IntPath. Our methodology and programs described in this work can be easily applied to other organisms; and we will include more model organisms and important pathogens in future releases of IntPath. IntPath maintains regular updates and is freely available at http://compbio.ddns.comp.nus.edu.sg:8080/IntPath. PMID:23282057

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology

PubMed Central

Latendresse, Mario; Paley, Suzanne M.; Krummenacker, Markus; Ong, Quang D.; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M.; Caspi, Ron

2016-01-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. PMID:26454094

Dynamic Visualization of Co-expression in Systems Genetics Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

2008-01-01

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

An Interactive, Integrated, Instructional Pathway to the LEAD Science Gateway

NASA Astrophysics Data System (ADS)

Yalda, S.; Clark, R.; Davis, L.; Wiziecki, E. N.

2008-12-01

Linked Environments for Atmospheric Discovery (LEAD) is a bold and revolutionary paradigm that through a Web-based Service Oriented Architecture (SOA) exposes the user to a rich environment of data, models, data mining and visualization and analysis tools, enabling the user to ask science questions of applications while the complexity of the software and middleware managing these applications is hidden from the user. From its inception in 2003, LEAD has championed goals that have context for the future of weather and related research and education. LEAD espouses to lowering the barrier for using complex end-to-end weather technologies by a) democratizing the availability of advanced weather technologies, b) empowering the user of these technologies to tackle a variety of problems, and c) facilitating learning and understanding. LEAD, as it exists today, is poised to enable a diverse community of scientists, educators, students, and operational practitioners. The project has been informed by atmospheric and computer scientists, educators, and educational consultants who, in search of new knowledge, understanding, ideas, and learning methodologies, seek easy access to new capabilities that allow for user-directed and interactive query and acquisition, simulation, assimilation, data mining, computational modeling, and visualization. As one component of the total LEAD effort, the LEAD education team has designed interactive, integrated, instructional pathways within a set of learning modules (LEAD-to-Learn) to facilitate, enhance, and enable the use of the LEAD gateway in the classroom. The LEAD education initiative focuses on the means to integrate data, tools, and services used by researchers into undergraduate meteorology education in order to provide an authentic and contextualized environment for teaching and learning. Educators, educational specialists, and students from meteorology and computer science backgrounds have collaborated on the design and development of learning materials, as well as new tools and features, to enhance the appearance and use of the LEAD portal gateway and its underlying cyberinfrastructure in an educational setting. The development of educational materials has centered on promoting the accessibility and use of meteorological data and analysis tools through the LEAD portal by providing instructional materials, additional custom designed tools that build off of Unidata's Integrated Data Viewer (IDV) (e.g. IDV Basic and NCDestroyer), and an interactive component that takes the user through specific tasks utilizing multiple tools. In fact, select improvements to parameter lists and domain subsetting have inspired IDV developers to incorporate changes in IDV revisions that are now available to the entire community. This collection of materials, demonstrations, interactive guides, student exercises, and customized tools, which are now available to the educator and student through the LEAD portal gateway, can serve as an instructional pathway for a set of guided, phenomenon-based exercises (e.g. fronts, lake-effect snows, etc.). This paper will provide an overview of the LEAD education and outreach efforts with a focus on the design of Web-based educational materials and instructional approaches for user interaction with the LEAD portal gateway and the underlying cyberinfrastructure, and will encourage educators, especially those involved in undergraduate meteorology education, to begin incorporating these capabilities into their course materials.

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system.

PubMed

Chen, I-Min A; Markowitz, Victor M; Palaniappan, Krishna; Szeto, Ernest; Chu, Ken; Huang, Jinghua; Ratner, Anna; Pillay, Manoj; Hadjithomas, Michalis; Huntemann, Marcel; Mikhailova, Natalia; Ovchinnikova, Galina; Ivanova, Natalia N; Kyrpides, Nikos C

2016-04-26

The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existing IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.

Exercise-driven metabolic pathways in healthy cartilage.

PubMed

Blazek, A D; Nam, J; Gupta, R; Pradhan, M; Perera, P; Weisleder, N L; Hewett, T E; Chaudhari, A M; Lee, B S; Leblebicioglu, B; Butterfield, T A; Agarwal, S

2016-07-01

Exercise is vital for maintaining cartilage integrity in healthy joints. Here we examined the exercise-driven transcriptional regulation of genes in healthy rat articular cartilage to dissect the metabolic pathways responsible for the potential benefits of exercise. Transcriptome-wide gene expression in the articular cartilage of healthy Sprague-Dawley female rats exercised daily (low intensity treadmill walking) for 2, 5, or 15 days was compared to that of non-exercised rats, using Affymetrix GeneChip arrays. Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for Gene Ontology (GO)-term enrichment and Functional Annotation analysis of differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genome (KEGG) pathway mapper was used to identify the metabolic pathways regulated by exercise. Microarray analysis revealed that exercise-induced 644 DEGs in healthy articular cartilage. The DAVID bioinformatics tool demonstrated high prevalence of functional annotation clusters with greater enrichment scores and GO-terms associated with extracellular matrix (ECM) biosynthesis/remodeling and inflammation/immune response. The KEGG database revealed that exercise regulates 147 metabolic pathways representing molecular interaction networks for Metabolism, Genetic Information Processing, Environmental Information Processing, Cellular Processes, Organismal Systems, and Diseases. These pathways collectively supported the complex regulation of the beneficial effects of exercise on the cartilage. Overall, the findings highlight that exercise is a robust transcriptional regulator of a wide array of metabolic pathways in healthy cartilage. The major actions of exercise involve ECM biosynthesis/cartilage strengthening and attenuation of inflammatory pathways to provide prophylaxis against onset of arthritic diseases in healthy cartilage. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology.

PubMed

Karp, Peter D; Latendresse, Mario; Paley, Suzanne M; Krummenacker, Markus; Ong, Quang D; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M; Caspi, Ron

2016-09-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single software environment with the added capability to interact with public data sources and visual analytic tools for HTP data analysis at a systems level. BRM is developed using Java™ and other open-source technologies for free distribution (http://www.sysbio.org/dataresources/brm.stm). PMID:23174015

Improving Microbial Genome Annotations in an Integrated Database Context

PubMed Central

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

Integrated Land-Water-Energy assessment using the Foreseer Tool

NASA Astrophysics Data System (ADS)

Allwood, Julian; Konadu, Dennis; Mourao, Zenaida; Lupton, Rick; Richards, Keith; Fenner, Richard; Skelton, Sandy; McMahon, Richard

2016-04-01

This study presents an integrated energy and resource modelling and visualisation approach, ForeseerTM, which characterises the interdependencies and evaluates the land and water requirement for energy system pathways. The Foreseer Tool maps linked energy, water and land resource futures by outputting a set of Sankey diagrams for energy, water and land, showing the flow from basic resource (e.g. coal, surface water, and forested land) through transformations (e.g. fuel refining and desalination) to final services (e.g. sustenance, hygiene and transportation). By 'mapping' resources in this way, policy-makers can more easily understand the competing uses through the identification of the services it delivers (e.g. food production, landscaping, energy), the potential opportunities for improving the management of the resource and the connections with other resources which are often overlooked in a traditional sector-based management strategy. This paper will present a case study of the UK Carbon Plan, and highlights the need for integrated resource planning and policy development.

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Serial analysis of gene expression in a rat lung model of asthma.

PubMed

Yin, Lei-Miao; Jiang, Gong-Hao; Wang, Yu; Wang, Yan; Liu, Yan-Yan; Jin, Wei-Rong; Zhang, Zen; Xu, Yu-Dong; Yang, Yong-Qing

2008-11-01

The pathogenesis and molecular mechanism underlying asthma remain undetermined. The purpose of this study was to identify genes and pathways involved in the early airway response (EAR) phase of asthma by using serial analysis of gene expression (SAGE). Two SAGE tag libraries of lung tissues derived from a rat model of asthma and controls were generated. Bioinformatic analyses were carried out using the Database for Annotation, Visualization and IntegratedDiscovery Functional Annotation Tool, Gene Ontology (GO) TreeMachine and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A total of 26 552 SAGE tags of asthmatic rat lung were obtained, of which 12 221 were unique tags. Of the unique tags, 55.5% were matched with known genes. By comparison of the two libraries, 186 differentially expressed tags (P < 0.05) were identified, of which 103 were upregulated and 83 were downregulated. Using the bioinformatic tools these genes were classified into 23 functional groups, 15 KEGG pathways and 37 enriched GO categories. The bioinformatic analyses of gene distribution, enriched categories and the involvement of specific pathways in the SAGE libraries have provided information on regulatory networks of the EAR phase of asthma. Analyses of the regulated genes of interest may inform new hypotheses, increase our understanding of the disease and provide a foundation for future research.

Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs

PubMed Central

Wessely, Frank; Bartl, Martin; Guthke, Reinhard; Li, Pu; Schuster, Stefan; Kaleta, Christoph

2011-01-01

While previous studies have shed light on the link between the structure of metabolism and its transcriptional regulation, the extent to which transcriptional regulation controls metabolism has not yet been fully explored. In this work, we address this problem by integrating a large number of experimental data sets with a model of the metabolism of Escherichia coli. Using a combination of computational tools including the concept of elementary flux patterns, methods from network inference and dynamic optimization, we find that transcriptional regulation of pathways reflects the protein investment into these pathways. While pathways that are associated to a high protein cost are controlled by fine-tuned transcriptional programs, pathways that only require a small protein cost are transcriptionally controlled in a few key reactions. As a reason for the occurrence of these different regulatory strategies, we identify an evolutionary trade-off between the conflicting requirements to reduce protein investment and the requirement to be able to respond rapidly to changes in environmental conditions. PMID:21772263

PANDA: pathway and annotation explorer for visualizing and interpreting gene-centric data.

PubMed

Hart, Steven N; Moore, Raymond M; Zimmermann, Michael T; Oliver, Gavin R; Egan, Jan B; Bryce, Alan H; Kocher, Jean-Pierre A

2015-01-01

Objective. Bringing together genomics, transcriptomics, proteomics, and other -omics technologies is an important step towards developing highly personalized medicine. However, instrumentation has advances far beyond expectations and now we are able to generate data faster than it can be interpreted. Materials and Methods. We have developed PANDA (Pathway AND Annotation) Explorer, a visualization tool that integrates gene-level annotation in the context of biological pathways to help interpret complex data from disparate sources. PANDA is a web-based application that displays data in the context of well-studied pathways like KEGG, BioCarta, and PharmGKB. PANDA represents data/annotations as icons in the graph while maintaining the other data elements (i.e., other columns for the table of annotations). Custom pathways from underrepresented diseases can be imported when existing data sources are inadequate. PANDA also allows sharing annotations among collaborators. Results. In our first use case, we show how easy it is to view supplemental data from a manuscript in the context of a user's own data. Another use-case is provided describing how PANDA was leveraged to design a treatment strategy from the somatic variants found in the tumor of a patient with metastatic sarcomatoid renal cell carcinoma. Conclusion. PANDA facilitates the interpretation of gene-centric annotations by visually integrating this information with context of biological pathways. The application can be downloaded or used directly from our website: http://bioinformaticstools.mayo.edu/research/panda-viewer/.

Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

PubMed

Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung

2012-12-01

What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC. • To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed. • To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.

Integrated care pathways for airway diseases (AIRWAYS-ICPs).

PubMed

Bousquet, J; Addis, A; Adcock, I; Agache, I; Agusti, A; Alonso, A; Annesi-Maesano, I; Anto, J M; Bachert, C; Baena-Cagnani, C E; Bai, C; Baigenzhin, A; Barbara, C; Barnes, P J; Bateman, E D; Beck, L; Bedbrook, A; Bel, E H; Benezet, O; Bennoor, K S; Benson, M; Bernabeu-Wittel, M; Bewick, M; Bindslev-Jensen, C; Blain, H; Blasi, F; Bonini, M; Bonini, S; Boulet, L P; Bourdin, A; Bourret, R; Bousquet, P J; Brightling, C E; Briggs, A; Brozek, J; Buhl, R; Bush, A; Caimmi, D; Calderon, M; Calverley, P; Camargos, P A; Camuzat, T; Canonica, G W; Carlsen, K H; Casale, T B; Cazzola, M; Cepeda Sarabia, A M; Cesario, A; Chen, Y Z; Chkhartishvili, E; Chavannes, N H; Chiron, R; Chuchalin, A; Chung, K F; Cox, L; Crooks, G; Crooks, M G; Cruz, A A; Custovic, A; Dahl, R; Dahlen, S E; De Blay, F; Dedeu, T; Deleanu, D; Demoly, P; Devillier, P; Didier, A; Dinh-Xuan, A T; Djukanovic, R; Dokic, D; Douagui, H; Dubakiene, R; Eglin, S; Elliot, F; Emuzyte, R; Fabbri, L; Fink Wagner, A; Fletcher, M; Fokkens, W J; Fonseca, J; Franco, A; Frith, P; Furber, A; Gaga, M; Garcés, J; Garcia-Aymerich, J; Gamkrelidze, A; Gonzales-Diaz, S; Gouzi, F; Guzmán, M A; Haahtela, T; Harrison, D; Hayot, M; Heaney, L G; Heinrich, J; Hellings, P W; Hooper, J; Humbert, M; Hyland, M; Iaccarino, G; Jakovenko, D; Jardim, J R; Jeandel, C; Jenkins, C; Johnston, S L; Jonquet, O; Joos, G; Jung, K S; Kalayci, O; Karunanithi, S; Keil, T; Khaltaev, N; Kolek, V; Kowalski, M L; Kull, I; Kuna, P; Kvedariene, V; Le, L T; Lodrup Carlsen, K C; Louis, R; MacNee, W; Mair, A; Majer, I; Manning, P; de Manuel Keenoy, E; Masjedi, M R; Melen, E; Melo-Gomes, E; Menzies-Gow, A; Mercier, G; Mercier, J; Michel, J P; Miculinic, N; Mihaltan, F; Milenkovic, B; Molimard, M; Momas, I; Montilla-Santana, A; Morais-Almeida, M; Morgan, M; N'Diaye, M; Nafti, S; Nekam, K; Neou, A; Nicod, L; O'Hehir, R; Ohta, K; Paggiaro, P; Palkonen, S; Palmer, S; Papadopoulos, N G; Papi, A; Passalacqua, G; Pavord, I; Pigearias, B; Plavec, D; Postma, D S; Price, D; Rabe, K F; Radier Pontal, F; Redon, J; Rennard, S; Roberts, J; Robine, J M; Roca, J; Roche, N; Rodenas, F; Roggeri, A; Rolland, C; Rosado-Pinto, J; Ryan, D; Samolinski, B; Sanchez-Borges, M; Schünemann, H J; Sheikh, A; Shields, M; Siafakas, N; Sibille, Y; Similowski, T; Small, I; Sola-Morales, O; Sooronbaev, T; Stelmach, R; Sterk, P J; Stiris, T; Sud, P; Tellier, V; To, T; Todo-Bom, A; Triggiani, M; Valenta, R; Valero, A L; Valiulis, A; Valovirta, E; Van Ganse, E; Vandenplas, O; Vasankari, T; Vestbo, J; Vezzani, G; Viegi, G; Visier, L; Vogelmeier, C; Vontetsianos, T; Wagstaff, R; Wahn, U; Wallaert, B; Whalley, B; Wickman, M; Williams, D M; Wilson, N; Yawn, B P; Yiallouros, P K; Yorgancioglu, A; Yusuf, O M; Zar, H J; Zhong, N; Zidarn, M; Zuberbier, T

2014-08-01

The objective of Integrated Care Pathways for Airway Diseases (AIRWAYS-ICPs) is to launch a collaboration to develop multi-sectoral care pathways for chronic respiratory diseases in European countries and regions. AIRWAYS-ICPs has strategic relevance to the European Union Health Strategy and will add value to existing public health knowledge by: 1) proposing a common framework of care pathways for chronic respiratory diseases, which will facilitate comparability and trans-national initiatives; 2) informing cost-effective policy development, strengthening in particular those on smoking and environmental exposure; 3) aiding risk stratification in chronic disease patients, using a common strategy; 4) having a significant impact on the health of citizens in the short term (reduction of morbidity, improvement of education in children and of work in adults) and in the long-term (healthy ageing); 5) proposing a common simulation tool to assist physicians; and 6) ultimately reducing the healthcare burden (emergency visits, avoidable hospitalisations, disability and costs) while improving quality of life. In the longer term, the incidence of disease may be reduced by innovative prevention strategies. AIRWAYSICPs was initiated by Area 5 of the Action Plan B3 of the European Innovation Partnership on Active and Healthy Ageing. All stakeholders are involved (health and social care, patients, and policy makers).

Functional genomics to assess biological responses to marine pollution at physiological and evolutionary timescales: toward a vision of predictive ecotoxicology.

PubMed

Reid, Noah M; Whitehead, Andrew

2016-09-01

Marine pollution is ubiquitous, and is one of the key factors influencing contemporary marine biodiversity worldwide. To protect marine biodiversity, how do we surveil, document and predict the short- and long-term impacts of pollutants on at-risk species? Modern genomics tools offer high-throughput, information-rich and increasingly cost-effective approaches for characterizing biological responses to environmental stress, and are important tools within an increasing sophisticated kit for surveiling and assessing impacts of pollutants on marine species. Through the lens of recent research in marine killifish, we illustrate how genomics tools may be useful for screening chemicals and pollutants for biological activity and to reveal specific mechanisms of action. The high dimensionality of transcriptomic responses enables their usage as highly specific fingerprints of exposure, and these fingerprints can be used to diagnose environmental problems. We also emphasize that molecular pathways recruited to respond at physiological timescales are the same pathways that may be targets for natural selection during chronic exposure to pollutants. Gene complement and sequence variation in those pathways can be related to variation in sensitivity to environmental pollutants within and among species. Furthermore, allelic variation associated with evolved tolerance in those pathways could be tracked to estimate the pace of environmental health decline and recovery. We finish by integrating these paradigms into a vision of how genomics approaches could anchor a modernized framework for advancing the predictive capacity of environmental and ecotoxicological science. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Improvement of Blood-Brain Barrier Integrity in Traumatic Brain Injury and Hemorrhagic Shock Following Treatment With Valproic Acid and Fresh Frozen Plasma.

PubMed

Nikolian, Vahagn C; Dekker, Simone E; Bambakidis, Ted; Higgins, Gerald A; Dennahy, Isabel S; Georgoff, Patrick E; Williams, Aaron M; Andjelkovic, Anuska V; Alam, Hasan B

2018-01-01

Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of proteins essential for blood-brain barrier integrity. The addition of valproic acid provides significant improvement to these protein expression profiles. This is likely secondary to activation of key pathways related to endothelial functions.

Role of the ceramide-signaling pathways in ionizing radiation-induced apoptosis.

PubMed

Vit, Jean-Philippe; Rosselli, Filippo

2003-11-27

Ionizing radiations (IR) exposure leads to damage on several cellular targets. How signals from different targets are integrated to determine the cell fate remains a controversial issue. Understanding the pathway(s) responsible(s) for the cell killing effect of the IR exposure is of prime importance in light of using radiations as anticancer agent or as diagnostic tool. In this study, we have established that IR-induced cell damage initiates two independent signaling pathways that lead to a biphasic intracellular ceramide increase. A transitory increase of ceramide is observed within minutes after IR exposure as a consequence of DNA damage-independent acid sphingomyelinase activation. Several hours after irradiation, a second wave of ceramide accumulation is observed depending on the DNA damage-dependent activation of ceramide synthase, which requires a signaling pathway involving ATM. Importantly, we have demonstrated that the late ceramide accumulation is also dependent on the first one and is rate limiting for the apoptotic process induced by IR. In conclusion, our observations suggest that ceramide is a major determinant of the IR-induced apoptotic process at the cross-point of different signal transduction pathways.

Integrating In Silico Resources to Map a Signaling Network

PubMed Central

Liu, Hanqing; Beck, Tim N.; Golemis, Erica A.; Serebriiskii, Ilya G.

2013-01-01

The abundance of publicly available life science databases offer a wealth of information that can support interpretation of experimentally derived data and greatly enhance hypothesis generation. Protein interaction and functional networks are not simply new renditions of existing data: they provide the opportunity to gain insights into the specific physical and functional role a protein plays as part of the biological system. In this chapter, we describe different in silico tools that can quickly and conveniently retrieve data from existing data repositories and discuss how the available tools are best utilized for different purposes. While emphasizing protein-protein interaction databases (e.g., BioGrid and IntAct), we also introduce metasearch platforms such as STRING and GeneMANIA, pathway databases (e.g., BioCarta and Pathway Commons), text mining approaches (e.g., PubMed and Chilibot), and resources for drug-protein interactions, genetic information for model organisms and gene expression information based on microarray data mining. Furthermore, we provide a simple step-by-step protocol to building customized protein-protein interaction networks in Cytoscape, a powerful network assembly and visualization program, integrating data retrieved from these various databases. As we illustrate, generation of composite interaction networks enables investigators to extract significantly more information about a given biological system than utilization of a single database or sole reliance on primary literature. PMID:24233784

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Network Analysis Tools: from biological networks to clusters and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system

DOE PAGES

Chen, I-Min A.; Markowitz, Victor M.; Palaniappan, Krishna; ...

2016-04-26

Background: The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Results: Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existingmore » IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. Conclusion: By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.« less

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, I-Min A.; Markowitz, Victor M.; Palaniappan, Krishna

Background: The exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a "Wiki-based" approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation. Results: Here, we present a different approach, relying on tightly integrated method rather than "Wiki-based" method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existingmore » IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review. Conclusion: By incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.« less

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations.

PubMed

Zhang, Han; Wheeler, William; Hyland, Paula L; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

2016-06-01

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations

PubMed Central

Zhang, Han; Wheeler, William; Hyland, Paula L.; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

2016-01-01

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs. PMID:27362418

Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

PubMed

Scorcioni, Ruggero; Wright, Susan N; Patrick Card, J; Ascoli, Giorgio A; Barrionuevo, Germán

2008-01-01

The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

Systems biology: a new tool for farm animal science.

PubMed

Hollung, Kristin; Timperio, Anna M; Olivan, Mamen; Kemp, Caroline; Coto-Montes, Ana; Sierra, Veronica; Zolla, Lello

2014-03-01

It is rapidly emerging that the tender meat phenotype is affected by an enormous amount of variables, not only tied to genetics (livestock breeding selection), but also to extrinsic factors, such as feeding conditions, physical activity, rearing environment, administration of hormonal growth promotants, pre-slaughter handling and stress. Proteomics has been widely accepted by meat scientists over the last years and is now commonly used to shed light on the postmortem processes involved in meat tenderization. This review discusses the latest findings with the use of proteomics and systems biology to study the different biochemical pathways postmortem aiming at understanding the concerted action of different molecular mechanisms responsible for meat quality. The conversion of muscle to meat postmortem can be described as a sequence of events involving molecular pathways controlled by a complex interplay of many factors. Among the different pathways emerging are the influence of apoptosis and lately also the role of autophagy in muscle postmortem development. This review thus, focus on how systems-wide integrated investigations (metabolomics, transcriptomics, interactomics, phosphoproteomics, mathematical modeling), which have emerged as complementary tools to proteomics, have helped establishing a few milestones in our understanding of the events leading from muscle to meat conversion.

Modular framework to assess the risk of African swine fever virus entry into the European Union.

PubMed

Mur, Lina; Martínez-López, Beatriz; Costard, Solenne; de la Torre, Ana; Jones, Bryony A; Martínez, Marta; Sánchez-Vizcaíno, Fernando; Muñoz, María Jesús; Pfeiffer, Dirk U; Sánchez-Vizcaíno, José Manuel; Wieland, Barbara

2014-07-03

The recent occurrence and spread of African swine fever (ASF) in Eastern Europe is perceived as a serious risk for the pig industry in the European Union (EU). In order to estimate the potential risk of ASF virus (ASFV) entering the EU, several pathways of introduction were previously assessed separately. The present work aimed to integrate five of these assessments (legal imports of pigs, legal imports of products, illegal imports of products, fomites associated with transport and wild boar movements) into a modular tool that facilitates the visualization and comprehension of the relative risk of ASFV introduction into the EU by each analyzed pathway. The framework's results indicate that 48% of EU countries are at relatively high risk (risk score 4 or 5 out of 5) for ASFV entry for at least one analyzed pathway. Four of these countries obtained the maximum risk score for one pathway: Bulgaria for legally imported products during the high risk period (HRP); Finland for wild boar; Slovenia and Sweden for legally imported pigs during the HRP. Distribution of risk considerably differed from one pathway to another; for some pathways, the risk was concentrated in a few countries (e.g., transport fomites), whereas other pathways incurred a high risk for 4 or 5 countries (legal pigs, illegal imports and wild boar). The modular framework, developed to estimate the risk of ASFV entry into the EU, is available in a public domain, and is a transparent, easy-to-interpret tool that can be updated and adapted if required. The model's results determine the EU countries at higher risk for each ASFV introduction route, and provide a useful basis to develop a global coordinated program to improve ASFV prevention in the EU.

Modular framework to assess the risk of African swine fever virus entry into the European Union

PubMed Central

2014-01-01

Background The recent occurrence and spread of African swine fever (ASF) in Eastern Europe is perceived as a serious risk for the pig industry in the European Union (EU). In order to estimate the potential risk of ASF virus (ASFV) entering the EU, several pathways of introduction were previously assessed separately. The present work aimed to integrate five of these assessments (legal imports of pigs, legal imports of products, illegal imports of products, fomites associated with transport and wild boar movements) into a modular tool that facilitates the visualization and comprehension of the relative risk of ASFV introduction into the EU by each analyzed pathway. Results The framework’s results indicate that 48% of EU countries are at relatively high risk (risk score 4 or 5 out of 5) for ASFV entry for at least one analyzed pathway. Four of these countries obtained the maximum risk score for one pathway: Bulgaria for legally imported products during the high risk period (HRP); Finland for wild boar; Slovenia and Sweden for legally imported pigs during the HRP. Distribution of risk considerably differed from one pathway to another; for some pathways, the risk was concentrated in a few countries (e.g., transport fomites), whereas other pathways incurred a high risk for 4 or 5 countries (legal pigs, illegal imports and wild boar). Conclusions The modular framework, developed to estimate the risk of ASFV entry into the EU, is available in a public domain, and is a transparent, easy-to-interpret tool that can be updated and adapted if required. The model’s results determine the EU countries at higher risk for each ASFV introduction route, and provide a useful basis to develop a global coordinated program to improve ASFV prevention in the EU. PMID:24992824

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

PubMed Central

Teeguarden, Justin. G.; Tan, Yu-Mei; Edwards, Stephen W.; Leonard, Jeremy A.; Anderson, Kim A.; Corley, Richard A.; Harding, Anna K; Kile, Molly L.; Simonich, Staci M; Stone, David; Tanguay, Robert L.; Waters, Katrina M.; Harper, Stacey L.; Williams, David E.

2016-01-01

Synopsis Driven by major scientific advances in analytical methods, biomonitoring, computational tools, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the Aggregate Exposure Pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the Adverse Outcome Pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more efficient integration of exposure assessment and hazard identification. Together, the two pathways form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making. PMID:26759916

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

PubMed

Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

2017-12-11

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer

PubMed Central

King, Carly J.; Woodward, Josha; Schwartzman, Jacob; Coleman, Daniel J.; Lisac, Robert; Wang, Nicholas J.; Van Hook, Kathryn; Gao, Lina; Urrutia, Joshua; Dane, Mark A.; Heiser, Laura M.; Alumkal, Joshi J.

2017-01-01

Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance. PMID:29340039

Informatics and computational strategies for the study of lipids.

PubMed

Yetukuri, Laxman; Ekroos, Kim; Vidal-Puig, Antonio; Oresic, Matej

2008-02-01

Recent advances in mass spectrometry (MS)-based techniques for lipidomic analysis have empowered us with the tools that afford studies of lipidomes at the systems level. However, these techniques pose a number of challenges for lipidomic raw data processing, lipid informatics, and the interpretation of lipidomic data in the context of lipid function and structure. Integration of lipidomic data with other systemic levels, such as genomic or proteomic, in the context of molecular pathways and biophysical processes provides a basis for the understanding of lipid function at the systems level. The present report, based on the limited literature, is an update on a young but rapidly emerging field of lipid informatics and related pathway reconstruction strategies.

Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis

PubMed Central

Lal, Aparna

2016-01-01

Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change. PMID:26848669

Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis.

PubMed

Lal, Aparna

2016-02-02

Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change.

Paper-based microreactor array for rapid screening of cell signaling cascades.

PubMed

Huang, Chia-Hao; Lei, Kin Fong; Tsang, Ngan-Ming

2016-08-07

Investigation of cell signaling pathways is important for the study of pathogenesis of cancer. However, the related operations used in these studies are time consuming and labor intensive. Thus, the development of effective therapeutic strategies may be hampered. In this work, gel-free cell culture and subsequent immunoassay has been successfully integrated and conducted in a paper-based microreactor array. Study of the activation level of different kinases of cells stimulated by different conditions, i.e., IL-6 stimulation, starvation, and hypoxia, was demonstrated. Moreover, rapid screening of cell signaling cascades after the stimulations of HGF, doxorubicin, and UVB irradiation was respectively conducted to simultaneously screen 40 kinases and transcription factors. Activation of multi-signaling pathways could be identified and the correlation between signaling pathways was discussed to provide further information to investigate the entire signaling network. The present technique integrates most of the tedious operations using a single paper substrate, reduces sample and reagent consumption, and shortens the time required by the entire process. Therefore, it provides a first-tier rapid screening tool for the study of complicated signaling cascades. It is expected that the technique can be developed for routine protocol in conventional biological research laboratories.

Integrative Functional Genomics for Systems Genetics in GeneWeaver.org.

PubMed

Bubier, Jason A; Langston, Michael A; Baker, Erich J; Chesler, Elissa J

2017-01-01

The abundance of existing functional genomics studies permits an integrative approach to interpreting and resolving the results of diverse systems genetics studies. However, a major challenge lies in assembling and harmonizing heterogeneous data sets across species for facile comparison to the positional candidate genes and coexpression networks that come from systems genetic studies. GeneWeaver is an online database and suite of tools at www.geneweaver.org that allows for fast aggregation and analysis of gene set-centric data. GeneWeaver contains curated experimental data together with resource-level data such as GO annotations, MP annotations, and KEGG pathways, along with persistent stores of user entered data sets. These can be entered directly into GeneWeaver or transferred from widely used resources such as GeneNetwork.org. Data are analyzed using statistical tools and advanced graph algorithms to discover new relations, prioritize candidate genes, and generate function hypotheses. Here we use GeneWeaver to find genes common to multiple gene sets, prioritize candidate genes from a quantitative trait locus, and characterize a set of differentially expressed genes. Coupling a large multispecies repository curated and empirical functional genomics data to fast computational tools allows for the rapid integrative analysis of heterogeneous data for interpreting and extrapolating systems genetics results.

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content

PubMed Central

Kling, Teresia; Johansson, Patrik; Sanchez, José; Marinescu, Voichita D.; Jörnsten, Rebecka; Nelander, Sven

2015-01-01

Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets. PMID:25953855

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

DOE PAGES

Brunk, Elizabeth; George, Kevin W.; Alonso-Gutierrez, Jorge; ...

2016-05-19

Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proofmore » of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.« less

Better informed in clinical practice - a brief overview of dental informatics.

PubMed

Reynolds, P A; Harper, J; Dunne, S

2008-03-22

Uptake of dental informatics has been hampered by technical and user issues. Innovative systems have been developed, but usability issues have affected many. Advances in technology and artificial intelligence are now producing clinically useful systems, although issues still remain with adapting computer interfaces to the dental practice working environment. A dental electronic health record has become a priority in many countries, including the UK. However, experience shows that any dental electronic health record (EHR) system cannot be subordinate to, or a subset of, a medical record. Such a future dental EHR is likely to incorporate integrated care pathways. Future best dental practice will increasingly depend on computer-based support tools, although disagreement remains about the effectiveness of current support tools. Over the longer term, future dental informatics tools will incorporate dynamic, online evidence-based medicine (EBM) tools, and promise more adaptive, patient-focused and efficient dental care with educational advantages in training.

Integrated microRNA and mRNA signatures in peripheral blood lymphocytes of familial epithelial ovarian cancer.

PubMed

Dou, Yun-De; Huang, Tao; Wang, Qun; Shu, Xin; Zhao, Shi-Gang; Li, Lei; Liu, Tao; Lu, Gang; Chan, Wai-Yee; Liu, Hong-Bin

2018-01-29

Characterization of the genetic landscapes of familial ovarian cancer through integrated analysis of microRNA and mRNA by partial least squares (PLS) and Monte Carlo technique based on genome-wide association studies (GWAS). The miRNA and mRNA transcriptional data in familial ovarian cancer were characterized from the Gene Expression Omnibus (GEO) database. The miRNA and mRNA expression profiles in peripheral blood lymphocytes (PBLs) of 74 familial ovarian cancer patients and 47 control subjects were analyzed with the integration of partial least squares (PLS) and Monte Carlo techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also performed. Total of 16 miRNA-mRNA pairs were identified with the target gene prediction results of miRNAs and mRNAs. An innovated miRNA-mRNA integrated network was constructed in which 6 downregulated miRNAs and 1 upregulated miRNAs were included. KEGG and GO pathway enrichment analysis revealed over-representation of dysregulated miRNAs in various biological processes especially in cancer pathology. Hsa-miR-34b played a pivotal role in this network and interacted with other miRNAs. Hsa-miR-136 and hsa-miR-335 were associated with p53 and Erk1/2 pathways and tumor suppressors, such as PTEN. The results from this research provide insights on miRNA-mRNA networks and offer new tools for studying transcriptional variants in familial ovarian cancer. Copyright © 2018 Elsevier Inc. All rights reserved.

Integrated care through disease-oriented clinical care pathways: experience from Japan’s regional health planning initiatives

PubMed Central

Okamoto, Etsuji; Miyamoto, Masaki; Hara, Kazuhiro; Yoshida, Jun; Muto, Masaki; Hirai, Aizan; Tatsumi, Haruyuki; Mizuno, Masaaki; Nagata, Hiroshi; Yamakata, Daisuke; Tanaka, Hiroshi

2011-01-01

Introduction In April 2008, Japan launched a radical reform in regional health planning that emphasized the development of disease-oriented clinical care pathways. These ‘inter-provider critical paths’ have sought to ensure effective integration of various providers ranging among primary care practitioners, acute care hospitals, rehabilitation hospitals, long-term care facilities and home care. Description of policy practice All 47 prefectures in Japan developed their Regional Health Plans pursuant to the guideline requiring that these should include at least four diseases: diabetes, acute myocardial infarction, cerebrovascular accident and cancer. To illustrate the care pathways developed, this paper describes the guideline referring to strokes and provides examples of the new Regional Health Plans as well as examples of disease-oriented inter-provider clinical paths. In particular, the paper examines the development of information sharing through electronic health records (EHR) to enhance effective integration among providers is discussed. Discussion and conclusion Japan’s reform in 2008 is unique in that the concept of ‘disease-oriented regional inter-provider critical paths’ was adopted as a national policy and all 47 prefectures developed their Regional Health Plans simultaneously. How much the new regional health planning policy has improved the quality and outcome of care remains to be seen and will be evaluated in 2013 after the five-year planned period of implementation has concluded. Whilst electronic health records appear to be a useful tool in supporting care integration they do not guarantee success in the application of an inter-provider critical path. PMID:22128281

[Methodological aspects of integrated care pathways].

PubMed

Gomis, R; Mata Cases, M; Mauricio Puente, D; Artola Menéndez, S; Ena Muñoz, J; Mediavilla Bravo, J J; Miranda Fernández-Santos, C; Orozco Beltrán, D; Rodríguez Mañas, L; Sánchez Villalba, C; Martínez, J A

An Integrated Healthcare Pathway (PAI) is a tool which has as its aim to increase the effectiveness of clinical performance through greater coordination and to ensure continuity of care. PAI places the patient as the central focus of the organisation of health services. It is defined as the set of activities carried out by the health care providers in order to increase the level of health and satisfaction of the population receiving services. The development of a PAI requires the analysis of the flow of activities, the inter-relationships between professionals and care teams, and patient expectations. The methodology for the development of a PAI is presented and discussed in this article, as well as the success factors for its definition and its effective implementation. It also explains, as an example, the recent PAI for Hypoglycaemia in patients with Type 2 Diabetes Mellitus developed by a multidisciplinary team and supported by several scientific societies. Copyright © 2017 SECA. Publicado por Elsevier España, S.L.U. All rights reserved.

CHRONOS: a time-varying method for microRNA-mediated subpathway enrichment analysis.

PubMed

Vrahatis, Aristidis G; Dimitrakopoulou, Konstantina; Balomenos, Panos; Tsakalidis, Athanasios K; Bezerianos, Anastasios

2016-03-15

In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific 'active parts' of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical 'themes'-in the form of enriched biologically relevant microRNA-mediated subpathways-that determine the functionality of signaling networks across time. To address these challenges, we developed time-vaRying enriCHment integrOmics Subpathway aNalysis tOol (CHRONOS) by integrating time series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions. Specifically, microRNA-mediated subpathway topologies are extracted and evaluated based on the temporal transition and the fold change activity of the linked genes/microRNAs. Further, we provide measures that capture the structural and functional features of subpathways in relation to the complete organism pathway atlas. Our application to synthetic and real data shows that CHRONOS outperforms current subpathway-based methods into unraveling the inherent dynamic properties of pathways. CHRONOS is freely available at http://biosignal.med.upatras.gr/chronos/ tassos.bezerianos@nus.edu.sg Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pathways and Mechanisms that Prevent Genome Instability in Saccharomyces cerevisiae

PubMed Central

Putnam, Christopher D.; Kolodner, Richard D.

2017-01-01

Genome rearrangements result in mutations that underlie many human diseases, and ongoing genome instability likely contributes to the development of many cancers. The tools for studying genome instability in mammalian cells are limited, whereas model organisms such as Saccharomyces cerevisiae are more amenable to these studies. Here, we discuss the many genetic assays developed to measure the rate of occurrence of Gross Chromosomal Rearrangements (called GCRs) in S. cerevisiae. These genetic assays have been used to identify many types of GCRs, including translocations, interstitial deletions, and broken chromosomes healed by de novo telomere addition, and have identified genes that act in the suppression and formation of GCRs. Insights from these studies have contributed to the understanding of pathways and mechanisms that suppress genome instability and how these pathways cooperate with each other. Integrated models for the formation and suppression of GCRs are discussed. PMID:28684602

Comparison of human cell signaling pathway databases—evolution, drawbacks and challenges

PubMed Central

Chowdhury, Saikat; Sarkar, Ram Rup

2015-01-01

Elucidating the complexities of cell signaling pathways is of immense importance to gain understanding about various biological phenomenon, such as dynamics of gene/protein expression regulation, cell fate determination, embryogenesis and disease progression. The successful completion of human genome project has also helped experimental and theoretical biologists to analyze various important pathways. To advance this study, during the past two decades, systematic collections of pathway data from experimental studies have been compiled and distributed freely by several databases, which also integrate various computational tools for further analysis. Despite significant advancements, there exist several drawbacks and challenges, such as pathway data heterogeneity, annotation, regular update and automated image reconstructions, which motivated us to perform a thorough review on popular and actively functioning 24 cell signaling databases. Based on two major characteristics, pathway information and technical details, freely accessible data from commercial and academic databases are examined to understand their evolution and enrichment. This review not only helps to identify some novel and useful features, which are not yet included in any of the databases but also highlights their current limitations and subsequently propose the reasonable solutions for future database development, which could be useful to the whole scientific community. PMID:25632107

Microscope-integrated optical coherence tomography for image-aided positioning of glaucoma surgery

NASA Astrophysics Data System (ADS)

Li, Xiqi; Wei, Ling; Dong, Xuechuan; Huang, Ping; Zhang, Chun; He, Yi; Shi, Guohua; Zhang, Yudong

2015-07-01

Most glaucoma surgeries involve creating new aqueous outflow pathways with the use of a small surgical instrument. This article reported a microscope-integrated, real-time, high-speed, swept-source optical coherence tomography system (SS-OCT) with a 1310-nm light source for glaucoma surgery. A special mechanism was designed to produce an adjustable system suitable for use in surgery. A two-graphic processing unit architecture was used to speed up the data processing and real-time volumetric rendering. The position of the surgical instrument can be monitored and measured using the microscope and a grid-inserted image of the SS-OCT. Finally, experiments were simulated to assess the effectiveness of this integrated system. Experimental results show that this system is a suitable positioning tool for glaucoma surgery.

Interactions of the polarization and the sun compass in path integration of desert ants.

PubMed

Lebhardt, Fleur; Ronacher, Bernhard

2014-08-01

Desert ants, Cataglyphis fortis, perform large-scale foraging trips in their featureless habitat using path integration as their main navigation tool. To determine their walking direction they use primarily celestial cues, the sky's polarization pattern and the sun position. To examine the relative importance of these two celestial cues, we performed cue conflict experiments. We manipulated the polarization pattern experienced by the ants during their outbound foraging excursions, reducing it to a single electric field (e-)vector direction with a linear polarization filter. The simultaneous view of the sun created situations in which the directional information of the sun and the polarization compass disagreed. The heading directions of the homebound runs recorded on a test field with full view of the natural sky demonstrate that none of both compasses completely dominated over the other. Rather the ants seemed to compute an intermediate homing direction to which both compass systems contributed roughly equally. Direct sunlight and polarized light are detected in different regions of the ant's compound eye, suggesting two separate pathways for obtaining directional information. In the experimental paradigm applied here, these two pathways seem to feed into the path integrator with similar weights.

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

PubMed Central

Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh

2015-01-01

Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978

Tracking Biocultural Pathways to Health Disparities: The Value of Biomarkers

PubMed Central

Worthman, Carol M.; Costello, E. Jane

2009-01-01

Background Cultural factors and biomarkers are emerging emphases in social epidemiology that readily ally with human biology and anthropology. Persistent health challenges and disparities have established biocultural roots, and environment plays an integral role in physical development and function that form the bases of population health. Biomarkers have proven to be valuable tools for investigating biocultural bases of health disparities. Aims We apply recent insights from biology to consider how culture gets under the skin and evaluate the construct of embodiment. We analyze contrasting biomarker models and applications, and propose an integrated model for biomarkers. Three examples from the Great Smoky Mountains Study (GSMS) illustrate these points. Subjects and methods The longitudinal developmental epidemiological GSMS comprises a population-based sample of 1420 children with repeated measures including mental and physical health, life events, household conditions, and biomarkers for pubertal development and allostatic load. Results Analyses using biomarkers resolved competing explanations for links between puberty and depression, identified gender differences in stress at puberty, and revealed interactive effects of birthweight and postnatal adversity on risk for depression at puberty in girls. Conclusion An integrated biomarker model can both enrich epidemiology and illuminate biocultural pathways in population health. PMID:19381986

Systems Genetics as a Tool to Identify Master Genetic Regulators in Complex Disease.

PubMed

Moreno-Moral, Aida; Pesce, Francesco; Behmoaras, Jacques; Petretto, Enrico

2017-01-01

Systems genetics stems from systems biology and similarly employs integrative modeling approaches to describe the perturbations and phenotypic effects observed in a complex system. However, in the case of systems genetics the main source of perturbation is naturally occurring genetic variation, which can be analyzed at the systems-level to explain the observed variation in phenotypic traits. In contrast with conventional single-variant association approaches, the success of systems genetics has been in the identification of gene networks and molecular pathways that underlie complex disease. In addition, systems genetics has proven useful in the discovery of master trans-acting genetic regulators of functional networks and pathways, which in many cases revealed unexpected gene targets for disease. Here we detail the central components of a fully integrated systems genetics approach to complex disease, starting from assessment of genetic and gene expression variation, linking DNA sequence variation to mRNA (expression QTL mapping), gene regulatory network analysis and mapping the genetic control of regulatory networks. By summarizing a few illustrative (and successful) examples, we highlight how different data-modeling strategies can be effectively integrated in a systems genetics study.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Neuroproteomics approach and neurosystems biology analysis: ROCK inhibitors as promising therapeutic targets in neurodegeneration and neurotrauma.

PubMed

Raad, Mohamad; El Tal, Tala; Gul, Rukhsana; Mondello, Stefania; Zhang, Zhiqun; Boustany, Rose-Mary; Guingab, Joy; Wang, Kevin K; Kobeissy, Firas

2012-12-01

Several common degenerative mechanisms and mediators underlying the neuronal injury pathways characterize several neurodegenerative diseases including Alzheimer's, Parkinson's, and Huntington's disease, as well as brain neurotrauma. Such common ground invites the emergence of new approaches and tools to study the altered pathways involved in neural injury alongside with neuritogenesis, an intricate process that commences with neuronal differentiation. Achieving a greater understanding of the impaired pathways of neuritogenesis would significantly help in uncovering detailed mechanisms of axonal regeneration. Among the several agents involved in neuritogenesis are the Rho and Rho kinases (ROCKs), which constitute key integral points in the Rho/ROCK pathway that is known to be disrupted in multiple neuropathologies such as spinal cord injury, traumatic brain injury, and Alzheimer's disease. This in turn renders ROCK inhibition as a promising candidate for therapeutic targets for treatment of neurodegenerative diseases. Among the novel tools to investigate the mechanisms involved in a specific disorder is the use of neuroproteomics/systems biology approach, a growing subfield of bioinformatics aiming to study and establishing a global assessment of the entire neuronal proteome, addressing the dynamic protein changes and interactions. This review aims to examine recent updates regarding how neuroproteomics aids in the understanding of molecular mechanisms of activation and inhibition in the area of neurogenesis and how Rho/ROCK pathway/ROCK inhibitors, primarily Y-27632 and Fasudil compounds, are applied in biological settings, promoting neuronal survival and neuroprotection that has direct future implications in neurotrauma. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

PubMed Central

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

PubMed

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

MACVIA-ARIA Sentinel NetworK for allergic rhinitis (MASK-rhinitis): the new generation guideline implementation.

PubMed

Bousquet, J; Schunemann, H J; Fonseca, J; Samolinski, B; Bachert, C; Canonica, G W; Casale, T; Cruz, A A; Demoly, P; Hellings, P; Valiulis, A; Wickman, M; Zuberbier, T; Bosnic-Anticevitch, S; Bedbrook, A; Bergmann, K C; Caimmi, D; Dahl, R; Fokkens, W J; Grisle, I; Lodrup Carlsen, K; Mullol, J; Muraro, A; Palkonen, S; Papadopoulos, N; Passalacqua, G; Ryan, D; Valovirta, E; Yorgancioglu, A; Aberer, W; Agache, I; Adachi, M; Akdis, C A; Akdis, M; Annesi-Maesano, I; Ansotegui, I J; Anto, J M; Arnavielhe, S; Arshad, H; Baiardini, I; Baigenzhin, A K; Barbara, C; Bateman, E D; Beghé, B; Bel, E H; Ben Kheder, A; Bennoor, K S; Benson, M; Bewick, M; Bieber, T; Bindslev-Jensen, C; Bjermer, L; Blain, H; Boner, A L; Boulet, L P; Bonini, M; Bonini, S; Bosse, I; Bourret, R; Bousquet, P J; Braido, F; Briggs, A H; Brightling, C E; Brozek, J; Buhl, R; Burney, P G; Bush, A; Caballero-Fonseca, F; Calderon, M A; Camargos, P A M; Camuzat, T; Carlsen, K H; Carr, W; Cepeda Sarabia, A M; Chavannes, N H; Chatzi, L; Chen, Y Z; Chiron, R; Chkhartishvili, E; Chuchalin, A G; Ciprandi, G; Cirule, I; Correia de Sousa, J; Cox, L; Crooks, G; Costa, D J; Custovic, A; Dahlen, S E; Darsow, U; De Carlo, G; De Blay, F; Dedeu, T; Deleanu, D; Denburg, J A; Devillier, P; Didier, A; Dinh-Xuan, A T; Dokic, D; Douagui, H; Dray, G; Dubakiene, R; Durham, S R; Dykewicz, M S; El-Gamal, Y; Emuzyte, R; Fink Wagner, A; Fletcher, M; Fiocchi, A; Forastiere, F; Gamkrelidze, A; Gemicioğlu, B; Gereda, J E; González Diaz, S; Gotua, M; Grouse, L; Guzmán, M A; Haahtela, T; Hellquist-Dahl, B; Heinrich, J; Horak, F; Hourihane, J O 'b; Howarth, P; Humbert, M; Hyland, M E; Ivancevich, J C; Jares, E J; Johnston, S L; Joos, G; Jonquet, O; Jung, K S; Just, J; Kaidashev, I; Kalayci, O; Kalyoncu, A F; Keil, T; Keith, P K; Khaltaev, N; Klimek, L; Koffi N'Goran, B; Kolek, V; Koppelman, G H; Kowalski, M L; Kull, I; Kuna, P; Kvedariene, V; Lambrecht, B; Lau, S; Larenas-Linnemann, D; Laune, D; Le, L T T; Lieberman, P; Lipworth, B; Li, J; Louis, R; Magard, Y; Magnan, A; Mahboub, B; Majer, I; Makela, M J; Manning, P; De Manuel Keenoy, E; Marshall, G D; Masjedi, M R; Maurer, M; Mavale-Manuel, S; Melén, E; Melo-Gomes, E; Meltzer, E O; Merk, H; Miculinic, N; Mihaltan, F; Milenkovic, B; Mohammad, Y; Molimard, M; Momas, I; Montilla-Santana, A; Morais-Almeida, M; Mösges, R; Namazova-Baranova, L; Naclerio, R; Neou, A; Neffen, H; Nekam, K; Niggemann, B; Nyembue, T D; O'Hehir, R E; Ohta, K; Okamoto, Y; Okubo, K; Ouedraogo, S; Paggiaro, P; Pali-Schöll, I; Palmer, S; Panzner, P; Papi, A; Park, H S; Pavord, I; Pawankar, R; Pfaar, O; Picard, R; Pigearias, B; Pin, I; Plavec, D; Pohl, W; Popov, T A; Portejoie, F; Postma, D; Potter, P; Price, D; Rabe, K F; Raciborski, F; Radier Pontal, F; Repka-Ramirez, S; Robalo-Cordeiro, C; Rolland, C; Rosado-Pinto, J; Reitamo, S; Rodenas, F; Roman Rodriguez, M; Romano, A; Rosario, N; Rosenwasser, L; Rottem, M; Sanchez-Borges, M; Scadding, G K; Serrano, E; Schmid-Grendelmeier, P; Sheikh, A; Simons, F E R; Sisul, J C; Skrindo, I; Smit, H A; Solé, D; Sooronbaev, T; Spranger, O; Stelmach, R; Strandberg, T; Sunyer, J; Thijs, C; Todo-Bom, A; Triggiani, M; Valenta, R; Valero, A L; van Hage, M; Vandenplas, O; Vezzani, G; Vichyanond, P; Viegi, G; Wagenmann, M; Walker, S; Wang, D Y; Wahn, U; Williams, D M; Wright, J; Yawn, B P; Yiallouros, P K; Yusuf, O M; Zar, H J; Zernotti, M E; Zhang, L; Zhong, N; Zidarn, M; Mercier, J

2015-11-01

Several unmet needs have been identified in allergic rhinitis: identification of the time of onset of the pollen season, optimal control of rhinitis and comorbidities, patient stratification, multidisciplinary team for integrated care pathways, innovation in clinical trials and, above all, patient empowerment. MASK-rhinitis (MACVIA-ARIA Sentinel NetworK for allergic rhinitis) is a simple system centred around the patient which was devised to fill many of these gaps using Information and Communications Technology (ICT) tools and a clinical decision support system (CDSS) based on the most widely used guideline in allergic rhinitis and its asthma comorbidity (ARIA 2015 revision). It is one of the implementation systems of Action Plan B3 of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA). Three tools are used for the electronic monitoring of allergic diseases: a cell phone-based daily visual analogue scale (VAS) assessment of disease control, CARAT (Control of Allergic Rhinitis and Asthma Test) and e-Allergy screening (premedical system of early diagnosis of allergy and asthma based on online tools). These tools are combined with a clinical decision support system (CDSS) and are available in many languages. An e-CRF and an e-learning tool complete MASK. MASK is flexible and other tools can be added. It appears to be an advanced, global and integrated ICT answer for many unmet needs in allergic diseases which will improve policies and standards. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Floral pathway integrator gene expression mediates gradual transmission of environmental and endogenous cues to flowering time.

PubMed

van Dijk, Aalt D J; Molenaar, Jaap

2017-01-01

The appropriate timing of flowering is crucial for the reproductive success of plants. Hence, intricate genetic networks integrate various environmental and endogenous cues such as temperature or hormonal statues. These signals integrate into a network of floral pathway integrator genes. At a quantitative level, it is currently unclear how the impact of genetic variation in signaling pathways on flowering time is mediated by floral pathway integrator genes. Here, using datasets available from literature, we connect Arabidopsis thaliana flowering time in genetic backgrounds varying in upstream signalling components with the expression levels of floral pathway integrator genes in these genetic backgrounds. Our modelling results indicate that flowering time depends in a quite linear way on expression levels of floral pathway integrator genes. This gradual, proportional response of flowering time to upstream changes enables a gradual adaptation to changing environmental factors such as temperature and light.

PREPARE: innovative integrated tools and platforms for radiological emergency preparedness and post-accident response in Europe.

PubMed

Raskob, Wolfgang; Schneider, Thierry; Gering, Florian; Charron, Sylvie; Zhelezniak, Mark; Andronopoulos, Spyros; Heriard-Dubreuil, Gilles; Camps, Johan

2015-04-01

The PREPARE project that started in February 2013 and will end at the beginning of 2016 aims to close gaps that have been identified in nuclear and radiological preparedness in Europe following the first evaluation of the Fukushima disaster. Among others, the project will address the review of existing operational procedures for dealing with long-lasting releases and cross-border problems in radiation monitoring and food safety and further develop missing functionalities in decision support systems (DSS) ranging from improved source-term estimation and dispersion modelling to the inclusion of hydrological pathways for European water bodies. In addition, a so-called Analytical Platform will be developed exploring the scientific and operational means to improve information collection, information exchange and the evaluation of such types of disasters. The tools developed within the project will be partly integrated into the two DSS ARGOS and RODOS. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Web-based hybrid-dimensional Visualization and Exploration of Cytological Localization Scenarios.

PubMed

Kovanci, Gökhan; Ghaffar, Mehmood; Sommer, Björn

2016-12-21

The CELLmicrocosmos 4.2 PathwayIntegration (CmPI) is a tool which provides hybrid-dimensional visualization and analysis of intracellular protein and gene localizations in the context of a virtual 3D environment. This tool is developed based on Java/Java3D/JOGL and provides a standalone application compatible to all relevant operating systems. However, it requires Java and the local installation of the software. Here we present the prototype of an alternative web-based visualization approach, using Three.js and D3.js. In this way it is possible to visualize and explore CmPI-generated localization scenarios including networks mapped to 3D cell components by just providing a URL to a collaboration partner. This publication describes the integration of the different technologies – Three.js, D3.js and PHP – as well as an application case: a localization scenario of the citrate cycle. The CmPI web viewer is available at: http://CmPIweb.CELLmicrocosmos.org.

Web-based hybrid-dimensional Visualization and Exploration of Cytological Localization Scenarios.

PubMed

Kovanci, Gökhan; Ghaffar, Mehmood; Sommer, Björn

2016-10-01

The CELLmicrocosmos 4.2 PathwayIntegration (CmPI) is a tool which provides hybriddimensional visualization and analysis of intracellular protein and gene localizations in the context of a virtual 3D environment. This tool is developed based on Java/Java3D/JOGL and provides a standalone application compatible to all relevant operating systems. However, it requires Java and the local installation of the software. Here we present the prototype of an alternative web-based visualization approach, using Three.js and D3.js. In this way it is possible to visualize and explore CmPI-generated localization scenarios including networks mapped to 3D cell components by just providing a URL to a collaboration partner. This publication describes the integration of the different technologies - Three.js, D3.js and PHP - as well as an application case: a localization scenario of the citrate cycle. The CmPI web viewer is available at: http://CmPIweb.CELLmicrocosmos.org.

Metabolomics: beyond biomarkers and towards mechanisms

PubMed Central

Johnson, Caroline H.; Ivanisevic, Julijana; Siuzdak, Gary

2017-01-01

Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases. PMID:26979502

Querying and Computing with BioCyc Databases

PubMed Central

Krummenacker, Markus; Paley, Suzanne; Mueller, Lukas; Yan, Thomas; Karp, Peter D.

2006-01-01

Summary We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database. Availability The Pathway Tools software and 20 BioCyc DBs in Tiers 1 and 2 are freely available to academic users; fees apply to some types of commercial use. For download instructions see http://BioCyc.org/download.shtml PMID:15961440

Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

PubMed Central

Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

2017-01-01

Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

Prioritizing biological pathways by recognizing context in time-series gene expression data.

PubMed

Lee, Jusang; Jo, Kyuri; Lee, Sunwon; Kang, Jaewoo; Kim, Sun

2016-12-23

The primary goal of pathway analysis using transcriptome data is to find significantly perturbed pathways. However, pathway analysis is not always successful in identifying pathways that are truly relevant to the context under study. A major reason for this difficulty is that a single gene is involved in multiple pathways. In the KEGG pathway database, there are 146 genes, each of which is involved in more than 20 pathways. Thus activation of even a single gene will result in activation of many pathways. This complex relationship often makes the pathway analysis very difficult. While we need much more powerful pathway analysis methods, a readily available alternative way is to incorporate the literature information. In this study, we propose a novel approach for prioritizing pathways by combining results from both pathway analysis tools and literature information. The basic idea is as follows. Whenever there are enough articles that provide evidence on which pathways are relevant to the context, we can be assured that the pathways are indeed related to the context, which is termed as relevance in this paper. However, if there are few or no articles reported, then we should rely on the results from the pathway analysis tools, which is termed as significance in this paper. We realized this concept as an algorithm by introducing Context Score and Impact Score and then combining the two into a single score. Our method ranked truly relevant pathways significantly higher than existing pathway analysis tools in experiments with two data sets. Our novel framework was implemented as ContextTRAP by utilizing two existing tools, TRAP and BEST. ContextTRAP will be a useful tool for the pathway based analysis of gene expression data since the user can specify the context of the biological experiment in a set of keywords. The web version of ContextTRAP is available at http://biohealth.snu.ac.kr/software/contextTRAP .

Rational confederation of genes and diseases: NGS interpretation via GeneCards, MalaCards and VarElect.

PubMed

Rappaport, Noa; Fishilevich, Simon; Nudel, Ron; Twik, Michal; Belinky, Frida; Plaschkes, Inbar; Stein, Tsippi Iny; Cohen, Dana; Oz-Levi, Danit; Safran, Marilyn; Lancet, Doron

2017-08-18

A key challenge in the realm of human disease research is next generation sequencing (NGS) interpretation, whereby identified filtered variant-harboring genes are associated with a patient's disease phenotypes. This necessitates bioinformatics tools linked to comprehensive knowledgebases. The GeneCards suite databases, which include GeneCards (human genes), MalaCards (human diseases) and PathCards (human pathways) together with additional tools, are presented with the focus on MalaCards utility for NGS interpretation as well as for large scale bioinformatic analyses. VarElect, our NGS interpretation tool, leverages the broad information in the GeneCards suite databases. MalaCards algorithms unify disease-related terms and annotations from 69 sources. Further, MalaCards defines hierarchical relatedness-aliases, disease families, a related diseases network, categories and ontological classifications. GeneCards and MalaCards delineate and share a multi-tiered, scored gene-disease network, with stringency levels, including the definition of elite status-high quality gene-disease pairs, coming from manually curated trustworthy sources, that includes 4500 genes for 8000 diseases. This unique resource is key to NGS interpretation by VarElect. VarElect, a comprehensive search tool that helps infer both direct and indirect links between genes and user-supplied disease/phenotype terms, is robustly strengthened by the information found in MalaCards. The indirect mode benefits from GeneCards' diverse gene-to-gene relationships, including SuperPaths-integrated biological pathways from 12 information sources. We are currently adding an important information layer in the form of "disease SuperPaths", generated from the gene-disease matrix by an algorithm similar to that previously employed for biological pathway unification. This allows the discovery of novel gene-disease and disease-disease relationships. The advent of whole genome sequencing necessitates capacities to go beyond protein coding genes. GeneCards is highly useful in this respect, as it also addresses 101,976 non-protein-coding RNA genes. In a more recent development, we are currently adding an inclusive map of regulatory elements and their inferred target genes, generated by integration from 4 resources. MalaCards provides a rich big-data scaffold for in silico biomedical discovery within the gene-disease universe. VarElect, which depends significantly on both GeneCards and MalaCards power, is a potent tool for supporting the interpretation of wet-lab experiments, notably NGS analyses of disease. The GeneCards suite has thus transcended its 2-decade role in biomedical research, maturing into a key player in clinical investigation.

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies

PubMed Central

Brito, Rory C. F.; Guimarães, Frederico G.; Velloso, João P. L.; Corrêa-Oliveira, Rodrigo; Ruiz, Jeronimo C.; Reis, Alexandre B.; Resende, Daniela M.

2017-01-01

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4+ and CD8+ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4+ and T CD8+ epitopes, compared with protective ones. T CD4+ and T CD8+ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism. PMID:28208616

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies.

PubMed

Brito, Rory C F; Guimarães, Frederico G; Velloso, João P L; Corrêa-Oliveira, Rodrigo; Ruiz, Jeronimo C; Reis, Alexandre B; Resende, Daniela M

2017-02-10

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4⁺ and CD8⁺ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4⁺ and T CD8⁺ epitopes, compared with protective ones. T CD4⁺ and T CD8⁺ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism.

Accelerating Adverse Outcome Pathway (AOP) development ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework is increasingly being adopted as a tool for organizing and summarizing the mechanistic information connecting molecular perturbations by environmental stressors with adverse outcomes relevant for ecological and human health outcomes. However, the conventional process for assembly of these AOPs is time and resource intensive, and has been a rate limiting step for AOP use and development. Therefore computational approaches to accelerate the process need to be developed. We previously developed a method for generating computationally predicted AOPs (cpAOPs) by association mining and integration of data from publicly available databases. In this work, a cpAOP network of ~21,000 associations was established between 105 phenotypes from TG-GATEs rat liver data from different time points (including microarray, pathological effects and clinical chemistry data), 994 REACTOME pathways, 688 High-throughput assays from ToxCast and 194 chemicals. A second network of 128,536 associations was generated by connecting 255 biological target genes from ToxCast to 4,980 diseases from CTD using either HT screening activity from ToxCast for 286 chemicals or CTD gene expression changes in response to 2,330 chemicals. Both networks were separately evaluated through manual extraction of disease-specific cpAOPs and comparison with expert curation of the relevant literature. By employing data integration strategies that involve the weighting of n

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M.; Palchak, Joseph D; McBennett, Brendan

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinatedmore » operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.« less

BioWarehouse: a bioinformatics database warehouse toolkit

PubMed Central

Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David WJ; Tenenbaum, Jessica D; Karp, Peter D

2006-01-01

Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the database integration problem for bioinformatics. PMID:16556315

BioWarehouse: a bioinformatics database warehouse toolkit.

PubMed

Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D

2006-03-23

This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

Preparedness for emerging infectious diseases: pathways from anticipation to action.

PubMed

Brookes, V J; Hernández-Jover, M; Black, P F; Ward, M P

2015-07-01

Emerging and re-emerging infectious disease (EID) events can have devastating human, animal and environmental health impacts. The emergence of EIDs has been associated with interconnected economic, social and environmental changes. Understanding these changes is crucial for EID preparedness and subsequent prevention and control of EID events. The aim of this review is to describe tools currently available for identification, prioritization and investigation of EIDs impacting human and animal health, and how these might be integrated into a systematic approach for directing EID preparedness. Environmental scanning, foresight programmes, horizon scanning and surveillance are used to collect and assess information for rapidly responding to EIDs and to anticipate drivers of emergence for mitigating future EID impacts. Prioritization of EIDs - using transparent and repeatable methods - based on disease impacts and the importance of those impacts to decision-makers can then be used for more efficient resource allocation for prevention and control. Risk assessment and simulation modelling methods assess the likelihood of EIDs occurring, define impact and identify mitigation strategies. Each of these tools has a role to play individually; however, we propose integration of these tools into a framework that enhances the development of tactical and strategic plans for emerging risk preparedness.

Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

PubMed Central

Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia

2018-01-01

Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways can be potential targets and predictors of therapeutic resistance and prognosis in bevacizumab-treated patients with mCRC. PMID:29342159

Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.

PubMed

Chabiniok, Radomir; Wang, Vicky Y; Hadjicharalambous, Myrianthi; Asner, Liya; Lee, Jack; Sermesant, Maxime; Kuhl, Ellen; Young, Alistair A; Moireau, Philippe; Nash, Martyn P; Chapelle, Dominique; Nordsletten, David A

2016-04-06

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

1-CMDb: A Curated Database of Genomic Variations of the One-Carbon Metabolism Pathway.

PubMed

Bhat, Manoj K; Gadekar, Veerendra P; Jain, Aditya; Paul, Bobby; Rai, Padmalatha S; Satyamoorthy, Kapaettu

2017-01-01

The one-carbon metabolism pathway is vital in maintaining tissue homeostasis by driving the critical reactions of folate and methionine cycles. A myriad of genetic and epigenetic events mark the rate of reactions in a tissue-specific manner. Integration of these to predict and provide personalized health management requires robust computational tools that can process multiomics data. The DNA sequences that may determine the chain of biological events and the endpoint reactions within one-carbon metabolism genes remain to be comprehensively recorded. Hence, we designed the one-carbon metabolism database (1-CMDb) as a platform to interrogate its association with a host of human disorders. DNA sequence and network information of a total of 48 genes were extracted from a literature survey and KEGG pathway that are involved in the one-carbon folate-mediated pathway. The information generated, collected, and compiled for all these genes from the UCSC genome browser included the single nucleotide polymorphisms (SNPs), CpGs, copy number variations (CNVs), and miRNAs, and a comprehensive database was created. Furthermore, a significant correlation analysis was performed for SNPs in the pathway genes. Detailed data of SNPs, CNVs, CpG islands, and miRNAs for 48 folate pathway genes were compiled. The SNPs in CNVs (9670), CpGs (984), and miRNAs (14) were also compiled for all pathway genes. The SIFT score, the prediction and PolyPhen score, as well as the prediction for each of the SNPs were tabulated and represented for folate pathway genes. Also included in the database for folate pathway genes were the links to 124 various phenotypes and disease associations as reported in the literature and from publicly available information. A comprehensive database was generated consisting of genomic elements within and among SNPs, CNVs, CpGs, and miRNAs of one-carbon metabolism pathways to facilitate (a) single source of information and (b) integration into large-genome scale network analysis to be developed in the future by the scientific community. The database can be accessed at http://slsdb.manipal.edu/ocm/. © 2017 S. Karger AG, Basel.

Gramene 2013: comparative plant genomics resources.

PubMed

Monaco, Marcela K; Stein, Joshua; Naithani, Sushma; Wei, Sharon; Dharmawardhana, Palitha; Kumari, Sunita; Amarasinghe, Vindhya; Youens-Clark, Ken; Thomason, James; Preece, Justin; Pasternak, Shiran; Olson, Andrew; Jiao, Yinping; Lu, Zhenyuan; Bolser, Dan; Kerhornou, Arnaud; Staines, Dan; Walts, Brandon; Wu, Guanming; D'Eustachio, Peter; Haw, Robin; Croft, David; Kersey, Paul J; Stein, Lincoln; Jaiswal, Pankaj; Ware, Doreen

2014-01-01

Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology.

FMM: a web server for metabolic pathway reconstruction and comparative analysis.

PubMed

Chou, Chih-Hung; Chang, Wen-Chi; Chiu, Chih-Min; Huang, Chih-Chang; Huang, Hsien-Da

2009-07-01

Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.

Social molecular pathways and the evolution of bee societies

PubMed Central

Bloch, Guy; Grozinger, Christina M.

2011-01-01

Bees provide an excellent model with which to study the neuronal and molecular modifications associated with the evolution of sociality because relatively closely related species differ profoundly in social behaviour, from solitary to highly social. The recent development of powerful genomic tools and resources has set the stage for studying the social behaviour of bees in molecular terms. We review ‘ground plan’ and ‘genetic toolkit’ models which hypothesize that discrete pathways or sets of genes that regulate fundamental behavioural and physiological processes in solitary species have been co-opted to regulate complex social behaviours in social species. We further develop these models and propose that these conserved pathways and genes may be incorporated into ‘social pathways’, which consist of relatively independent modules involved in social signal detection, integration and processing within the nervous and endocrine systems, and subsequent behavioural outputs. Modifications within modules or in their connections result in the evolution of novel behavioural patterns. We describe how the evolution of pheromonal regulation of social pathways may lead to the expression of behaviour under new social contexts, and review plasticity in circadian rhythms as an example for a social pathway with a modular structure. PMID:21690132

Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.).

PubMed

Moschen, Sebastián; Di Rienzo, Julio A; Higgins, Janet; Tohge, Takayuki; Watanabe, Mutsumi; González, Sergio; Rivarola, Máximo; García-García, Francisco; Dopazo, Joaquin; Hopp, H Esteban; Hoefgen, Rainer; Fernie, Alisdair R; Paniego, Norma; Fernández, Paula; Heinz, Ruth A

2017-07-01

By integration of transcriptional and metabolic profiles we identified pathways and hubs transcription factors regulated during drought conditions in sunflower, useful for applications in molecular and/or biotechnological breeding. Drought is one of the most important environmental stresses that effects crop productivity in many agricultural regions. Sunflower is tolerant to drought conditions but the mechanisms involved in this tolerance remain unclear at the molecular level. The aim of this study was to characterize and integrate transcriptional and metabolic pathways related to drought stress in sunflower plants, by using a system biology approach. Our results showed a delay in plant senescence with an increase in the expression level of photosynthesis related genes as well as higher levels of sugars, osmoprotectant amino acids and ionic nutrients under drought conditions. In addition, we identified transcription factors that were upregulated during drought conditions and that may act as hubs in the transcriptional network. Many of these transcription factors belong to families implicated in the drought response in model species. The integration of transcriptomic and metabolomic data in this study, together with physiological measurements, has improved our understanding of the biological responses during droughts and contributes to elucidate the molecular mechanisms involved under this environmental condition. These findings will provide useful biotechnological tools to improve stress tolerance while maintaining crop yield under restricted water availability.

Xenopus egg extract: A powerful tool to study genome maintenance mechanisms.

PubMed

Hoogenboom, Wouter S; Klein Douwel, Daisy; Knipscheer, Puck

2017-08-15

DNA repair pathways are crucial to maintain the integrity of our genome and prevent genetic diseases such as cancer. There are many different types of DNA damage and specific DNA repair mechanisms have evolved to deal with these lesions. In addition to these repair pathways there is an extensive signaling network that regulates processes important for repair, such as cell cycle control and transcription. Despite extensive research, DNA damage repair and signaling are not fully understood. In vitro systems such as the Xenopus egg extract system, have played, and still play, an important role in deciphering the molecular details of these processes. Xenopus laevis egg extracts contain all factors required to efficiently perform DNA repair outside a cell, using mechanisms conserved in humans. These extracts have been used to study several genome maintenance pathways, including mismatch repair, non-homologous end joining, ICL repair, DNA damage checkpoint activation, and replication fork stability. Here we describe how the Xenopus egg extract system, in combination with specifically designed DNA templates, contributed to our detailed understanding of these pathways. Copyright © 2017. Published by Elsevier Inc.

Interactive Electronic Decision Trees for the Integrated Primary Care Management of Febrile Children in Low Resource Settings - Review of existing tools.

PubMed

Keitel, Kristina; D'Acremont, Valérie

2018-04-20

The lack of effective, integrated diagnostic tools pose a major challenge to the primary care management of febrile childhood illnesses. These limitations are especially evident in low-resource settings and are often inappropriately compensated by antimicrobial over-prescription. Interactive electronic decision trees (IEDTs) have the potential to close these gaps: guiding antibiotic use and better identifying serious disease. This narrative review summarizes existing IEDTs, to provide an overview of their degree of validation, as well as to identify gaps in current knowledge and prospects for future innovation. Structured literature review in PubMed and Embase complemented by google search and contact with developers. Six integrated IEDTs were identified: three (eIMCI, REC, and Bangladesh digital IMCI) based on Integrated Management of Childhood Illnesses (IMCI); four (SL eCCM, MEDSINC, e-iCCM, and D-Tree eCCM) on Integrated Community Case Management (iCCM); two (ALMANACH, MSFeCARE) with a modified IMCI content; and one (ePOCT) that integrates novel content with biomarker testing. The types of publications and evaluation studies varied greatly: the content and evidence-base was published for two (ALMANACH and ePOCT), ALMANACH and ePOCT were validated in efficacy studies. Other types of evaluations, such as compliance, acceptability were available for D-Tree eCCM, eIMCI, ALMANACH. Several evaluations are still ongoing. Future prospects include conducting effectiveness and impact studies using data gathered through larger studies to adapt the medical content to local epidemiology, improving the software and sensors, and Assessing factors that influence compliance and scale-up. IEDTs are valuable tools that have the potential to improve management of febrile children in primary care and increase the rational use of diagnostics and antimicrobials. Next steps in the evidence pathway should be larger effectiveness and impact studies (including cost analysis) and continuous integration of clinically useful diagnostic and treatment innovations. Copyright © 2018. Published by Elsevier Ltd.

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Programmable genetic circuits for pathway engineering.

PubMed

Hoynes-O'Connor, Allison; Moon, Tae Seok

2015-12-01

Synthetic biology has the potential to provide decisive advances in genetic control of metabolic pathways. However, there are several challenges that synthetic biologists must overcome before this vision becomes a reality. First, a library of diverse and well-characterized sensors, such as metabolite-sensing or condition-sensing promoters, must be constructed. Second, robust programmable circuits that link input conditions with a specific gene regulation response must be developed. Finally, multi-gene targeting strategies must be integrated with metabolically relevant sensors and complex, robust logic. Achievements in each of these areas, which employ the CRISPR/Cas system, in silico modeling, and dynamic sensor-regulators, among other tools, provide a strong basis for future research. Overall, the future for synthetic biology approaches in metabolic engineering holds immense promise. Copyright © 2015 Elsevier Ltd. All rights reserved.

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Daniel D.; Department of Biomedical Engineering, University of California Davis, Davis, CA; Villarreal, Fernando D.

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with amore » special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.« less

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

PubMed Central

Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems. PMID:25538941

Synthetic biology outside the cell: linking computational tools to cell-free systems.

PubMed

Lewis, Daniel D; Villarreal, Fernando D; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

In pursuit of excellence: an integrated care pathway for C1 inhibitor deficiency

PubMed Central

Manson, A L; Price, A; Dempster, J; Clinton-Tarestad, P; Greening, C; Enti, R; Hill, S; Grigoriadou, S; Buckland, M S; Longhurst, H J

2013-01-01

There are estimated to be approximately 1500 people in the United Kingdom with C1 inhibitor (C1INH) deficiency. At BartsHealth National Health Service (NHS) Trust we manage 133 patients with this condition and we believe that this represents one of the largest cohorts in the United Kingdom. C1INH deficiency may be hereditary or acquired. It is characterized by unpredictable episodic swellings, which may affect any part of the body, but are potentially fatal if they involve the larynx and cause significant morbidity if they involve the viscera. The last few years have seen a revolution in the treatment options that are available for C1 inhibitor deficiency. However, this occurs at a time when there are increased spending restraints in the NHS and the commissioning structure is being overhauled. Integrated care pathways (ICP) are a tool for disseminating best practice, for facilitating clinical audit, enabling multi-disciplinary working and for reducing health-care costs. Here we present an ICP for managing C1 inhibitor deficiency. PMID:23607500

Commentary on: "An integrated metabolic atlas of clear cell renal cell carcinoma." Hakimi AA, Reznik E, Lee CH, Creighton CJ, Brannon AR, Luna A, Aksoy BA, Liu EM, Shen R, Lee W, Chen Y, Stirdivant SM, Russo P, Chen YB, Tickoo SK, Reuter VE, Cheng EH, Sander C, Hsieh JJ.: Cancer Cell. 2016 Jan 11;29(1):104-16.

PubMed

Lee, Byron H

2017-09-01

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort. Copyright © 2017 Elsevier Inc. All rights reserved.

Lessons from Toxicology: Developing a 21st-Century Paradigm for Medical Research

PubMed Central

Austin, Christopher P.; Balapure, Anil K.; Birnbaum, Linda S.; Bucher, John R.; Fentem, Julia; Fitzpatrick, Suzanne C.; Fowle, John R.; Kavlock, Robert J.; Kitano, Hiroaki; Lidbury, Brett A.; Muotri, Alysson R.; Peng, Shuang-Qing; Sakharov, Dmitry; Seidle, Troy; Trez, Thales; Tonevitsky, Alexander; van de Stolpe, Anja; Whelan, Maurice; Willett, Catherine

2015-01-01

Summary Biomedical developments in the 21st century provide an unprecedented opportunity to gain a dynamic systems-level and human-specific understanding of the causes and pathophysiologies of disease. This understanding is a vital need, in view of continuing failures in health research, drug discovery, and clinical translation. The full potential of advanced approaches may not be achieved within a 20th-century conceptual framework dominated by animal models. Novel technologies are being integrated into environmental health research and are also applicable to disease research, but these advances need a new medical research and drug discovery paradigm to gain maximal benefits. We suggest a new conceptual framework that repurposes the 21st-century transition underway in toxicology. Human disease should be conceived as resulting from integrated extrinsic and intrinsic causes, with research focused on modern human-specific models to understand disease pathways at multiple biological levels that are analogous to adverse outcome pathways in toxicology. Systems biology tools should be used to integrate and interpret data about disease causation and pathophysiology. Such an approach promises progress in overcoming the current roadblocks to understanding human disease and successful drug discovery and translation. A discourse should begin now to identify and consider the many challenges and questions that need to be solved. PMID:26523530

Construction, characterization and application of molecular tools for metabolic engineering of Synechocystis sp.

PubMed

Qi, Fengxia; Yao, Lun; Tan, Xiaoming; Lu, Xuefeng

2013-10-01

An integrative gene expression system has been constructed for the directional assembly of biological components in Synechocystis PCC6803. We have characterized 11 promoter parts with various expression efficiencies for genetic engineering of Synechocystis for the production of fatty alcohols. This was achieved by integrating several genetic modifications including the expression of multiple-copies of fatty acyl-CoA reductase (FAR) under the control of strong promoters, disruption of the competing pathways for poly-β-hydroxybutyrate and glycogen synthesis, and for peptide truncation of the FAR. In shake-flask cultures, the production of fatty alcohols was significantly improved with a yield of 761 ± 216 μg/g cell dry weight in Synechocystis, which is the highest reported to date.

Molecular basis of embryonic stem cell self-renewal: from signaling pathways to pluripotency network

PubMed Central

Huang, Guanyi; Ye, Shoudong; Zhou, Xingliang; Liu, Dahai

2016-01-01

Embryonic stem cells (ESCs) can be maintained in culture indefinitely while retaining the capacity to generate any type of cell in the body, and therefore not only hold great promise for tissue repair and regeneration, but also provide a powerful tool for modeling human disease and understanding biological development. In order to fulfill the full potential of ESCs, it is critical to understand how ESC fate, whether to self-renew or to differentiate into specialized cells, is regulated. On the molecular level, ESC fate is controlled by the intracellular transcriptional regulatory networks that respond to various extrinsic signaling stimuli. In this review, we discuss and compare important signaling pathways in the self-renewal and differentiation of mouse, rat, and human ESCs with an emphasis on how these pathways integrate into ESC-specific transcription circuitries. This will be beneficial for understanding the common and conserved mechanisms that govern self-renewal, and for developing novel culture conditions that support ESC derivation and maintenance. PMID:25595304

Model Checking of a Diabetes-Cancer Model

NASA Astrophysics Data System (ADS)

Gong, Haijun; Zuliani, Paolo; Clarke, Edmund M.

2011-06-01

Accumulating evidence suggests that cancer incidence might be associated with diabetes mellitus, especially Type II diabetes which is characterized by hyperinsulinaemia, hyperglycaemia, obesity, and overexpression of multiple WNT pathway components. These diabetes risk factors can activate a number of signaling pathways that are important in the development of different cancers. To systematically understand the signaling components that link diabetes and cancer risk, we have constructed a single-cell, Boolean network model by integrating the signaling pathways that are influenced by these risk factors to study insulin resistance, cancer cell proliferation and apoptosis. Then, we introduce and apply the Symbolic Model Verifier (SMV), a formal verification tool, to qualitatively study some temporal logic properties of our diabetes-cancer model. The verification results show that the diabetes risk factors might not increase cancer risk in normal cells, but they will promote cell proliferation if the cell is in a precancerous or cancerous stage characterized by losses of the tumor-suppressor proteins ARF and INK4a.

Pathview Web: user friendly pathway visualization and data integration

PubMed Central

Pant, Gaurav; Bhavnasi, Yeshvant K.; Blanchard, Steven G.; Brouwer, Cory

2017-01-01

Abstract Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. PMID:28482075

Research Project Evaluation-Learnings from the PATHWAYS Project Experience.

PubMed

Galas, Aleksander; Pilat, Aleksandra; Leonardi, Matilde; Tobiasz-Adamczyk, Beata

2018-05-25

Every research project faces challenges regarding how to achieve its goals in a timely and effective manner. The purpose of this paper is to present a project evaluation methodology gathered during the implementation of the Participation to Healthy Workplaces and Inclusive Strategies in the Work Sector (the EU PATHWAYS Project). The PATHWAYS project involved multiple countries and multi-cultural aspects of re/integrating chronically ill patients into labor markets in different countries. This paper describes key project's evaluation issues including: (1) purposes, (2) advisability, (3) tools, (4) implementation, and (5) possible benefits and presents the advantages of a continuous monitoring. Project evaluation tool to assess structure and resources, process, management and communication, achievements, and outcomes. The project used a mixed evaluation approach and included Strengths (S), Weaknesses (W), Opportunities (O), and Threats (SWOT) analysis. A methodology for longitudinal EU projects' evaluation is described. The evaluation process allowed to highlight strengths and weaknesses and highlighted good coordination and communication between project partners as well as some key issues such as: the need for a shared glossary covering areas investigated by the project, problematic issues related to the involvement of stakeholders from outside the project, and issues with timing. Numerical SWOT analysis showed improvement in project performance over time. The proportion of participating project partners in the evaluation varied from 100% to 83.3%. There is a need for the implementation of a structured evaluation process in multidisciplinary projects involving different stakeholders in diverse socio-environmental and political conditions. Based on the PATHWAYS experience, a clear monitoring methodology is suggested as essential in every multidisciplinary research projects.

[Challenges in geriatric rehabilitation: the development of an integrated care pathway].

PubMed

Everink, Irma Helga Johanna; van Haastregt, Jolanda C M; Kempen, Gertrudis I J M; Dielis, Leen M J; Maessen, José M C; Schols, Jos M G A

2015-04-01

Coordination and continuity of care within geriatric rehabilitation is challenging. To tackle these challenges, an integrated care pathway within geriatric rehabilitation care (hospital, geriatric rehabilitation and follow-up care in the home situation) has been developed. The aim of this article is to expound the process of developing the integrated care pathway, and to describe and discuss the results of this process (which is the integrated care pathway). Developing the integrated care pathway was done by the guidance of the first four steps of the theoretical framework for implementation of change from Grol and Wensing: (1) development of a specific proposal for change in practice; (2) analysis of current care practice; (3) analysis of the target group and setting; and (4) development and selection of interventions/strategies for change. The organizations involved in geriatric rehabilitation argued that the integrated care pathway should focus on improving the process of care, including transfer of patients, handovers and communication between care organizations. Current practice, barriers and incentives for change were analyzed through literature research, expert consultation, and interviews with the involved caregivers and by establishing working groups of health care professionals, patients and informal caregivers. This resulted in valuable proposals for improvement of the care process, which were gathered and combined in the integrated care pathway. The integrated care pathway entails agreements on (a) the triage process in the hospital; (b) active engagement of patients and informal caregivers in the care process; (c) timely and high quality handovers; and (d) improved communication between caregivers.

Nutritional metabolomics: Progress in addressing complexity in diet and health

PubMed Central

Jones, Dean P.; Park, Youngja; Ziegler, Thomas R.

2013-01-01

Nutritional metabolomics is rapidly maturing to use small molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health and complex pathobiology, serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and non-targeted metabolic profiling, along with bioinformatics, pathway mapping and computational modeling, are now used for nutrition research on diet, metabolism, microbiome and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics and health phenotyping, to support integrated models required for personalized diet and nutrition forecasting. PMID:22540256

Integrative analysis of environmental sequences using MEGAN4.

PubMed

Huson, Daniel H; Mitra, Suparna; Ruscheweyh, Hans-Joachim; Weber, Nico; Schuster, Stephan C

2011-09-01

A major challenge in the analysis of environmental sequences is data integration. The question is how to analyze different types of data in a unified approach, addressing both the taxonomic and functional aspects. To facilitate such analyses, we have substantially extended MEGAN, a widely used taxonomic analysis program. The new program, MEGAN4, provides an integrated approach to the taxonomic and functional analysis of metagenomic, metatranscriptomic, metaproteomic, and rRNA data. While taxonomic analysis is performed based on the NCBI taxonomy, functional analysis is performed using the SEED classification of subsystems and functional roles or the KEGG classification of pathways and enzymes. A number of examples illustrate how such analyses can be performed, and show that one can also import and compare classification results obtained using others' tools. MEGAN4 is freely available for academic purposes, and installers for all three major operating systems can be downloaded from www-ab.informatik.uni-tuebingen.de/software/megan.

Integrative Medicine as a Bridge to Physician Wellness.

PubMed

Nguyen, Chau T

2018-03-01

Burnout is increasingly recognized as an issue of major importance affecting physicians of all ages and disciplines and thereby patients, systems, and health care in general. At the 2017 American Academy of Otolaryngology-Head and Neck Surgery Foundation Annual Meeting, the scope of burnout in medicine was addressed, along with systematic issues that remain. While changing the culture of medicine and health systems to address this is needed, what strategies can health care providers use in their everyday lives to lessen the impact of burnout? Integrative medicine with its focus on wholeness of patient care, including the emotional, mental, social, and spiritual domains of health, is uniquely positioned in arming physicians with sets of tools to help them navigate patients to better health and healing. These very same methods are invaluable for personal self-care, as we are all potential patients. Integrative medicine is a pathway to improving one's own self-care and, thereby, improving patient care.

Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

PubMed Central

Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

2010-01-01

Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845

Transcriptomics study of neurodegenerative disease: emphasis on synaptic dysfunction mechanism in Alzheimer's disease.

PubMed

Karim, Sajjad; Mirza, Zeenat; Ansari, Shakeel A; Rasool, Mahmood; Iqbal, Zafar; Sohrab, Sayed S; Kamal, Mohammad A; Abuzenadah, Adel M; Al-Qahtani, Mohammed H

2014-01-01

Alzheimer's disease (AD) is a common neurodegenerative disorder primarily affecting memory and thinking ability; caused by progressive degeneration and death of nerve cells. In this study, we integrated multiple dataset retrieved from the National Center for Biotechnology Information's Gene Expression Omnibus database, and took a systems-biology approach to compare and distinguish the molecular network based synaptic dysregulation associated with AD in particular and neurodegenerative diseases in general. We first identified 832 differentially expressed genes using cut off P value <0.5 and fold change > 2, followed by gene ontology study to identify genes associated with synapse (n=95) [membrane associated guanylate kinase, 2, amyloid beta precursor protein, neurotrophic tyrosine kinase, receptor, type 2], synapse part [γ-aminobutyric acid A receptor, γ1], synaptic vesicle [glutamate receptor, ionotropic, α-amino-3-hydroxy-5- methyl-4-isoxazole propionic acid receptor 2, synaptoporin], pre- and post-synaptic density [neuronal calcium sensor 1, glutamate receptor, metabotropic 3]. We integrated these data with known pathways using Ingenuity Pathway Analysis tool and found following synapse associated pathways to be most affected; γ-aminobutyric acid receptor signaling, synaptic long term potentiation/depression, nuclear factor-erythroid 2-related factor 2-mediated oxidative stress response, huntington's disease signaling and Reelin signaling in neurons. In conclusion, synaptic dysfunction is tightly associated with the development and progression of neurodegenerative diseases like AD.

Role of TGF Beta and PPAR Alpha Signaling Pathways in Radiation Response of Locally Exposed Heart: Integrated Global Transcriptomics and Proteomics Analysis.

PubMed

Subramanian, Vikram; Seemann, Ingar; Merl-Pham, Juliane; Hauck, Stefanie M; Stewart, Fiona A; Atkinson, Michael J; Tapio, Soile; Azimzadeh, Omid

2017-01-06

Epidemiological data from patients undergoing radiotherapy for thoracic tumors clearly show the damaging effect of ionizing radiation on cardiovascular system. The long-term impairment of heart function and structure after local high-dose irradiation is associated with systemic inflammatory response, contraction impairment, microvascular damage, and cardiac fibrosis. The goal of the present study was to investigate molecular mechanisms involved in this process. C57BL/6J mice received a single X-ray dose of 16 Gy given locally to the heart at the age of 8 weeks. Radiation-induced changes in the heart transcriptome and proteome were investigated 40 weeks after the exposure. The omics data were analyzed by bioinformatics tools and validated by immunoblotting. Integrated network analysis of transcriptomics and proteomics data elucidated the signaling pathways that were similarly affected at gene and protein level. Analysis showed induction of transforming growth factor (TGF) beta signaling but inactivation of peroxisome proliferator-activated receptor (PPAR) alpha signaling in irradiated heart. The putative mediator role of mitogen-activated protein kinase cascade linking PPAR alpha and TGF beta signaling was supported by data from immunoblotting and ELISA. This study indicates that both signaling pathways are involved in radiation-induced heart fibrosis, metabolic disordering, and impaired contractility, a pathophysiological condition that is often observed in patients that received high radiation doses in thorax.

Integrative Genomic Analysis Identifies Isoleucine and CodY as Regulators of Listeria monocytogenes Virulence

PubMed Central

Lobel, Lior; Sigal, Nadejda; Borovok, Ilya; Ruppin, Eytan; Herskovits, Anat A.

2012-01-01

Intracellular bacterial pathogens are metabolically adapted to grow within mammalian cells. While these adaptations are fundamental to the ability to cause disease, we know little about the relationship between the pathogen's metabolism and virulence. Here we used an integrative Metabolic Analysis Tool that combines transcriptome data with genome-scale metabolic models to define the metabolic requirements of Listeria monocytogenes during infection. Twelve metabolic pathways were identified as differentially active during L. monocytogenes growth in macrophage cells. Intracellular replication requires de novo synthesis of histidine, arginine, purine, and branch chain amino acids (BCAAs), as well as catabolism of L-rhamnose and glycerol. The importance of each metabolic pathway during infection was confirmed by generation of gene knockout mutants in the respective pathways. Next, we investigated the association of these metabolic requirements in the regulation of L. monocytogenes virulence. Here we show that limiting BCAA concentrations, primarily isoleucine, results in robust induction of the master virulence activator gene, prfA, and the PrfA-regulated genes. This response was specific and required the nutrient responsive regulator CodY, which is known to bind isoleucine. Further analysis demonstrated that CodY is involved in prfA regulation, playing a role in prfA activation under limiting conditions of BCAAs. This study evidences an additional regulatory mechanism underlying L. monocytogenes virulence, placing CodY at the crossroads of metabolism and virulence. PMID:22969433

SZDB: A Database for Schizophrenia Genetic Research

PubMed Central

Wu, Yong; Yao, Yong-Gang

2017-01-01

Abstract Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein–protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses. PMID:27451428

Integrated platform for genome-wide screening and construction of high-density genetic interaction maps in mammalian cells

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2013-01-01

A major challenge of the postgenomic era is to understand how human genes function together in normal and disease states. In microorganisms, high-density genetic interaction (GI) maps are a powerful tool to elucidate gene functions and pathways. We have developed an integrated methodology based on pooled shRNA screening in mammalian cells for genome-wide identification of genes with relevant phenotypes and systematic mapping of all GIs among them. We recently demonstrated the potential of this approach in an application to pathways controlling the susceptibility of human cells to the toxin ricin. Here we present the complete quantitative framework underlying our strategy, including experimental design, derivation of quantitative phenotypes from pooled screens, robust identification of hit genes using ultra-complex shRNA libraries, parallel measurement of tens of thousands of GIs from a single double-shRNA experiment, and construction of GI maps. We describe the general applicability of our strategy. Our pooled approach enables rapid screening of the same shRNA library in different cell lines and under different conditions to determine a range of different phenotypes. We illustrate this strategy here for single- and double-shRNA libraries. We compare the roles of genes for susceptibility to ricin and Shiga toxin in different human cell lines and reveal both toxin-specific and cell line-specific pathways. We also present GI maps based on growth and ricin-resistance phenotypes, and we demonstrate how such a comparative GI mapping strategy enables functional dissection of physical complexes and context-dependent pathways. PMID:23739767

Modeled aerosol nitrate formation pathways during wintertime in the Great Lakes region of North America

NASA Astrophysics Data System (ADS)

Kim, Yoo Jung; Spak, Scott N.; Carmichael, Gregory R.; Riemer, Nicole; Stanier, Charles O.

2014-11-01

Episodic wintertime particle pollution by ammonium nitrate is an important air quality concern across the Midwest U.S. Understanding and accurately forecasting PM2.5 episodes are complicated by multiple pathways for aerosol nitrate formation, each with uncertain rate parameters. Here, the Community Multiscale Air Quality model (CMAQ) simulated regional atmospheric nitrate budgets during the 2009 LADCO Winter Nitrate Study, using integrated process rate (IPR) and integrated reaction rate (IRR) tools to quantify relevant processes. Total nitrate production contributing to PM2.5 episodes is a regional phenomenon, with peak production over the Ohio River Valley and southern Great Lakes. Total nitrate production in the lower troposphere is attributed to three pathways, with 57% from heterogeneous conversion of N2O5, 28% from the reaction of OH and NO2, and 15% from homogeneous conversion of N2O5. TNO3 formation rates varied day-to-day and on synoptic timescales. Rate-limited production does not follow urban-rural gradients and NOx emissions due, to counterbalancing of urban enhancement in daytime HNO3 production with nocturnal reductions. Concentrations of HNO3 and N2O5 and nighttime TNO3 formation rates have maxima aloft (100-500 m), leading to net total nitrate vertical flux during episodes, with substantial vertical gradients in nitrate partitioning. Uncertainties in all three pathways are relevant to wintertime aerosol modeling and highlight the importance of interacting transport and chemistry processes during ammonium nitrate episodes, as well as the need for additional constraint on the system through field and laboratory experiments.

[Personalised health services: Suggestions for their effective implementation].

PubMed

Töpfer, Armin; Brabänder, Georg

2018-02-01

A strategy of customisation, and its subsequent practical implementation as part of personalised treatment pathways, is an appropriate approach to increase benefits for patients and to strengthen the competitive position of the provider of health services. This requires restructuring and/or reorganising measures to enable variants within the treatment pathway as a value creation process to be adapted to each individual patient and his illness, living conditions and preferences. This 'mass customisation' approach allows us to achieve the objective of a constructive interconnection of customisation and standardisation of health services. Major, rapid progress in information and communication technology plays a key part in this process. Focused design tools for mass customisation are the integration of patients into the service delivery process and the modularisation of processes and organisation. By taking into account the specificities of health services as a confidence good these design tools are featured and supported by operational and organisational tools in order to develop variants. This approach allows for high-quality health services that are perfectly tailored to individual patients' needs and, at the same time, delivered in an economic way. On this basis, customised approaches for personalised health diagnosis and therapy provide patient-focused health services that manage to apply the concept of value-based healthcare in a sophisticated and effective form. Copyright © 2018. Published by Elsevier GmbH.

DIDEM - An integrated model for comparative health damage costs calculation of air pollution

NASA Astrophysics Data System (ADS)

Ravina, Marco; Panepinto, Deborah; Zanetti, Maria Chiara

2018-01-01

Air pollution represents a continuous hazard to human health. Administration, companies and population need efficient indicators of the possible effects given by a change in decision, strategy or habit. The monetary quantification of health effects of air pollution through the definition of external costs is increasingly recognized as a useful indicator to support decision and information at all levels. The development of modelling tools for the calculation of external costs can provide support to analysts in the development of consistent and comparable assessments. In this paper, the DIATI Dispersion and Externalities Model (DIDEM) is presented. The DIDEM model calculates the delta-external costs of air pollution comparing two alternative emission scenarios. This tool integrates CALPUFF's advanced dispersion modelling with the latest WHO recommendations on concentration-response functions. The model is based on the impact pathway method. It was designed to work with a fine spatial resolution and a local or national geographic scope. The modular structure allows users to input their own data sets. The DIDEM model was tested on a real case study, represented by a comparative analysis of the district heating system in Turin, Italy. Additional advantages and drawbacks of the tool are discussed in the paper. A comparison with other existing models worldwide is reported.

Performance on a Surgical In-Training Examination Varies by Training Year and Pathway.

PubMed

Silvestre, Jason; Levin, L Scott; Serletti, Joseph M; Chang, Benjamin

2016-08-01

Few studies in surgery have addressed medical knowledge competency training as defined by the Accreditation Council for Graduate Medical Education. As in-training examinations are ubiquitous educational tools for surgical residents in the United States, insights into examination performance may help fill this void. The purpose of this study was to determine the relationship between In-Service Examination performance and training characteristics in plastic surgery. This retrospective cohort study reviewed performance data for the Plastic Surgery In-Service Training Examination for the years 2012 to 2015. Comparisons were made both within and between training pathways by means of Kruskal-Wallis and Mann-Whitney U tests. Data were available for 1367 independent (37.9 percent) and 2240 integrated residents (62.1 percent). Among integrated residents, performance increased with additional years of training (p < 0.001), but no difference existed between postgraduate year-5 and postgraduate year-6 residents (p > 0.05). Similarly, independent resident examination performance increased by year of training (p < 0.001), with no difference between postgraduate year-2 and postgraduate year-3 residents (p > 0.05). At each level of training (postgraduate years 4 to 6), integrated residents outperformed their independent resident colleagues (postgraduate years 1 to 3) (p < 0.001). Performance on the Plastic Surgery In-Service Training Examination increases during residency, with integrated residents outperforming independent residents. These findings may have implications for medical knowledge competency training as defined by the Accreditation Council for Graduate Medical Education.

Extending the Shared Socioeconomic Pathways for sub-national impacts, adaptation, and vulnerability studies

DOE PAGES

Absar, Syeda Mariya; Preston, Benjamin L.

2015-05-25

The exploration of alternative socioeconomic futures is an important aspect of understanding the potential consequences of climate change. While socioeconomic scenarios are common and, at times essential, tools for the impact, adaptation and vulnerability and integrated assessment modeling research communities, their approaches to scenario development have historically been quite distinct. However, increasing convergence of impact, adaptation and vulnerability and integrated assessment modeling research in terms of scales of analysis suggests there may be value in the development of a common framework for socioeconomic scenarios. The Shared Socioeconomic Pathways represents an opportunity for the development of such a common framework. However,more » the scales at which these global storylines have been developed are largely incommensurate with the sub-national scales at which impact, adaptation and vulnerability, and increasingly integrated assessment modeling, studies are conducted. Our objective for this study was to develop sub-national and sectoral extensions of the global SSP storylines in order to identify future socioeconomic challenges for adaptation for the U.S. Southeast. A set of nested qualitative socioeconomic storyline elements, integrated storylines, and accompanying quantitative indicators were developed through an application of the Factor-Actor-Sector framework. Finally, in addition to revealing challenges and opportunities associated with the use of the SSPs as a basis for more refined scenario development, this study generated sub-national storyline elements and storylines that can subsequently be used to explore the implications of alternative subnational socioeconomic futures for the assessment of climate change impacts and adaptation.« less

Analyzing and interpreting genome data at the network level with ConsensusPathDB.

PubMed

Herwig, Ralf; Hardt, Christopher; Lienhard, Matthias; Kamburov, Atanas

2016-10-01

ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq. The tool reports interaction network modules, biochemical pathways and functional information that are significantly enriched by the user's input, applying computational methods for statistical over-representation, enrichment and graph analysis. The results of this protocol can be observed within a few minutes, even with genome-wide data. The resulting network associations can be used to interpret high-throughput data mechanistically, to characterize and prioritize biomarkers, to integrate different omics levels, to design follow-up functional assay experiments and to generate topology for kinetic models at different scales.

Aggregate Exposure and Cumulative Risk Assessment—Integrating Occupational and Non-occupational Risk Factors

PubMed Central

Lentz, T. J.; Dotson, G. S.; Williams, P. R.D.; Maier, A.; Gadagbui, B.; Pandalai, S. P.; Lamba, A.; Hearl, F.; Mumtaz, M.

2015-01-01

Occupational exposure limits have traditionally focused on preventing morbidity and mortality arising from inhalation exposures to individual chemical stressors in the workplace. While central to occupational risk assessment, occupational exposure limits have limited application as a refined disease prevention tool because they do not account for all of the complexities of the work and non-occupational environments and are based on varying health endpoints. To be of greater utility, occupational exposure limits and other risk management tools could integrate broader consideration of risks from multiple exposure pathways and routes (aggregate risk) as well as the combined risk from exposure to both chemical and non-chemical stressors, within and beyond the workplace, including the possibility that such exposures may cause interactions or modify the toxic effects observed (cumulative risk). Although still at a rudimentary stage in many cases, a variety of methods and tools have been developed or are being used in allied risk assessment fields to incorporate such considerations in the risk assessment process. These approaches, which are collectively referred to as cumulative risk assessment, have potential to be adapted or modified for occupational scenarios and provide a tangible path forward for occupational risk assessment. Accounting for complex exposures in the workplace and the broader risks faced by the individual also requires a more complete consideration of the composite effects of occupational and non-occupational risk factors to fully assess and manage worker health problems. Barriers to integrating these different factors remain, but new and ongoing community-based and worker health-related initiatives may provide mechanisms for identifying and integrating risk from aggregate exposures and cumulative risks from all relevant sources, be they occupational or non-occupational. PMID:26583907

Aggregate Exposure and Cumulative Risk Assessment--Integrating Occupational and Non-occupational Risk Factors.

PubMed

Lentz, T J; Dotson, G S; Williams, P R D; Maier, A; Gadagbui, B; Pandalai, S P; Lamba, A; Hearl, F; Mumtaz, M

2015-01-01

Occupational exposure limits have traditionally focused on preventing morbidity and mortality arising from inhalation exposures to individual chemical stressors in the workplace. While central to occupational risk assessment, occupational exposure limits have limited application as a refined disease prevention tool because they do not account for all of the complexities of the work and non-occupational environments and are based on varying health endpoints. To be of greater utility, occupational exposure limits and other risk management tools could integrate broader consideration of risks from multiple exposure pathways and routes (aggregate risk) as well as the combined risk from exposure to both chemical and non-chemical stressors, within and beyond the workplace, including the possibility that such exposures may cause interactions or modify the toxic effects observed (cumulative risk). Although still at a rudimentary stage in many cases, a variety of methods and tools have been developed or are being used in allied risk assessment fields to incorporate such considerations in the risk assessment process. These approaches, which are collectively referred to as cumulative risk assessment, have potential to be adapted or modified for occupational scenarios and provide a tangible path forward for occupational risk assessment. Accounting for complex exposures in the workplace and the broader risks faced by the individual also requires a more complete consideration of the composite effects of occupational and non-occupational risk factors to fully assess and manage worker health problems. Barriers to integrating these different factors remain, but new and ongoing community-based and worker health-related initiatives may provide mechanisms for identifying and integrating risk from aggregate exposures and cumulative risks from all relevant sources, be they occupational or non-occupational.

A systems biology pipeline identifies new immune and disease related molecular signatures and networks in human cells during microgravity exposure

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sayak; Saha, Rohini; Palanisamy, Anbarasi; Ghosh, Madhurima; Biswas, Anupriya; Roy, Saheli; Pal, Arijit; Sarkar, Kathakali; Bagh, Sangram

2016-05-01

Microgravity is a prominent health hazard for astronauts, yet we understand little about its effect at the molecular systems level. In this study, we have integrated a set of systems-biology tools and databases and have analysed more than 8000 molecular pathways on published global gene expression datasets of human cells in microgravity. Hundreds of new pathways have been identified with statistical confidence for each dataset and despite the difference in cell types and experiments, around 100 of the new pathways are appeared common across the datasets. They are related to reduced inflammation, autoimmunity, diabetes and asthma. We have identified downregulation of NfκB pathway via Notch1 signalling as new pathway for reduced immunity in microgravity. Induction of few cancer types including liver cancer and leukaemia and increased drug response to cancer in microgravity are also found. Increase in olfactory signal transduction is also identified. Genes, based on their expression pattern, are clustered and mathematically stable clusters are identified. The network mapping of genes within a cluster indicates the plausible functional connections in microgravity. This pipeline gives a new systems level picture of human cells under microgravity, generates testable hypothesis and may help estimating risk and developing medicine for space missions.

A systems biology pipeline identifies new immune and disease related molecular signatures and networks in human cells during microgravity exposure.

PubMed

Mukhopadhyay, Sayak; Saha, Rohini; Palanisamy, Anbarasi; Ghosh, Madhurima; Biswas, Anupriya; Roy, Saheli; Pal, Arijit; Sarkar, Kathakali; Bagh, Sangram

2016-05-17

Microgravity is a prominent health hazard for astronauts, yet we understand little about its effect at the molecular systems level. In this study, we have integrated a set of systems-biology tools and databases and have analysed more than 8000 molecular pathways on published global gene expression datasets of human cells in microgravity. Hundreds of new pathways have been identified with statistical confidence for each dataset and despite the difference in cell types and experiments, around 100 of the new pathways are appeared common across the datasets. They are related to reduced inflammation, autoimmunity, diabetes and asthma. We have identified downregulation of NfκB pathway via Notch1 signalling as new pathway for reduced immunity in microgravity. Induction of few cancer types including liver cancer and leukaemia and increased drug response to cancer in microgravity are also found. Increase in olfactory signal transduction is also identified. Genes, based on their expression pattern, are clustered and mathematically stable clusters are identified. The network mapping of genes within a cluster indicates the plausible functional connections in microgravity. This pipeline gives a new systems level picture of human cells under microgravity, generates testable hypothesis and may help estimating risk and developing medicine for space missions.

Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism

PubMed Central

Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

2016-01-01

Motivation Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. Results In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models. PMID:26812499

Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism.

PubMed

Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

2016-01-01

Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In these simulations, the iMT1026 model has shown a better performance than the previous existing models.

Pathview Web: user friendly pathway visualization and data integration.

PubMed

Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K; Blanchard, Steven G; Brouwer, Cory

2017-07-03

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

PubMed

Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane

2017-09-13

The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

PubMed

Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

2015-02-01

To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'.

PubMed

Faust, Karoline; Croes, Didier; van Helden, Jacques

2009-12-01

In their article entitled 'Can sugars be produced from fatty acids? A test case for pathway analysis tools' de Figueiredo and co-authors assess the performance of three pathway prediction tools (METATOOL, PathFinding and Pathway Hunter Tool) using the synthesis of glucose-6-phosphate (G6P) from acetyl-CoA in humans as a test case. We think that this article is biased for three reasons: (i) the metabolic networks used as input for the respective tools were of very different sizes; (ii) the 'assessment' is restricted to two study cases; (iii) developers are inherently more skilled to use their own tools than those developed by other people. We extended the analyses led by de Figueiredo and clearly show that the apparent superior performance of their tool (METATOOL) is partly due to the differences in input network sizes. We also see a conceptual problem in the comparison of tools that serve different purposes. In our opinion, metabolic path finding and elementary mode analysis are answering different biological questions, and should be considered as complementary rather than competitive approaches. Supplementary data are available at Bioinformatics online.

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond

PubMed Central

Gama-Castro, Socorro; Salgado, Heladia; Santos-Zavaleta, Alberto; Ledezma-Tejeida, Daniela; Muñiz-Rascado, Luis; García-Sotelo, Jair Santiago; Alquicira-Hernández, Kevin; Martínez-Flores, Irma; Pannier, Lucia; Castro-Mondragón, Jaime Abraham; Medina-Rivera, Alejandra; Solano-Lira, Hilda; Bonavides-Martínez, César; Pérez-Rueda, Ernesto; Alquicira-Hernández, Shirley; Porrón-Sotelo, Liliana; López-Fuentes, Alejandra; Hernández-Koutoucheva, Anastasia; Moral-Chávez, Víctor Del; Rinaldi, Fabio; Collado-Vides, Julio

2016-01-01

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for ‘neighborhood’ genes to known operons and regulons, and computational developments. PMID:26527724

Homology-integrated CRISPR-Cas (HI-CRISPR) system for one-step multigene disruption in Saccharomyces cerevisiae.

PubMed

Bao, Zehua; Xiao, Han; Liang, Jing; Zhang, Lu; Xiong, Xiong; Sun, Ning; Si, Tong; Zhao, Huimin

2015-05-15

One-step multiple gene disruption in the model organism Saccharomyces cerevisiae is a highly useful tool for both basic and applied research, but it remains a challenge. Here, we report a rapid, efficient, and potentially scalable strategy based on the type II Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR associated proteins (Cas) system to generate multiple gene disruptions simultaneously in S. cerevisiae. A 100 bp dsDNA mutagenizing homologous recombination donor is inserted between two direct repeats for each target gene in a CRISPR array consisting of multiple donor and guide sequence pairs. An ultrahigh copy number plasmid carrying iCas9, a variant of wild-type Cas9, trans-encoded RNA (tracrRNA), and a homology-integrated crRNA cassette is designed to greatly increase the gene disruption efficiency. As proof of concept, three genes, CAN1, ADE2, and LYP1, were simultaneously disrupted in 4 days with an efficiency ranging from 27 to 87%. Another three genes involved in an artificial hydrocortisone biosynthetic pathway, ATF2, GCY1, and YPR1, were simultaneously disrupted in 6 days with 100% efficiency. This homology-integrated CRISPR (HI-CRISPR) strategy represents a powerful tool for creating yeast strains with multiple gene knockouts.

Rat aorta as a pharmacological tool for in vitro and in vivo studies.

PubMed

Rameshrad, Maryam; Babaei, Hossein; Azarmi, Yadollah; Fouladi, Daniel Fadaei

2016-01-15

Rat aorta assay provides a low cost and rapid platform, especially for preclinical in vivo models. The signaling pathways of the analog on the vessels could be evaluated separately on the endothelium or smooth muscle cells by rings of the rat aorta in vitro. The rat aorta is used for angiogenesis modeling to integrate the benefits of the both in vivo and in vitro models. These explain the importance and usage of rat aorta in researches. Furthermore, about 4503 articles have been published with the key word "rat aorta" in title or abstract from 1955 until the end of 2013 in Medline. In this review, these articles were organized into two main categories: in vivo and in vitro studies. The in vitro section focused on the rat aorta model, as a tool for evaluate the mechanism of vasodilation, vasoconstriction and angiogenesis. In the in vivo section, the most important usage of this tissue was evaluated. Also, the vasotonic signaling pathways in the vessel are explained briefly and some rat aorta applications in vitro and in vivo have been discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Innovative computational tools for reducing exploration risk through integration of water-rock interactions and magnetotelluric surveys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Joseph

2017-04-20

Mapping permeability distributions in geothermal reservoirs is essential for reducing the cost of geothermal development. To avoid the cost and sampling bias of measuring permeability directly through drilling, we require remote methods of imaging permeability such as geophysics. Electrical resistivity (or its inverse, conductivity) is one of the most sensitive geophysical properties known to reflect long range fluid interconnection and thus the likelihood of permeability. Perhaps the most widely applied geophysical methods for imaging subsurface resistivity is magnetotellurics (MT) due to its relatively great penetration depths. A primary goal of this project is to confirm through ground truthing at existingmore » geothermal systems that MT resistivity structure interpreted integratively is capable of revealing permeable fluid pathways into geothermal systems.« less

Systems Biology for Organotypic Cell Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis J.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

A Systems Biology Approach to Reveal Putative Host-Derived Biomarkers of Periodontitis by Network Topology Characterization of MMP-REDOX/NO and Apoptosis Integrated Pathways.

PubMed

Zeidán-Chuliá, Fares; Gürsoy, Mervi; Neves de Oliveira, Ben-Hur; Özdemir, Vural; Könönen, Eija; Gürsoy, Ulvi K

2015-01-01

Periodontitis, a formidable global health burden, is a common chronic disease that destroys tooth-supporting tissues. Biomarkers of the early phase of this progressive disease are of utmost importance for global health. In this context, saliva represents a non-invasive biosample. By using systems biology tools, we aimed to (1) identify an integrated interactome between matrix metalloproteinase (MMP)-REDOX/nitric oxide (NO) and apoptosis upstream pathways of periodontal inflammation, and (2) characterize the attendant topological network properties to uncover putative biomarkers to be tested in saliva from patients with periodontitis. Hence, we first generated a protein-protein network model of interactions ("BIOMARK" interactome) by using the STRING 10 database, a search tool for the retrieval of interacting genes/proteins, with "Experiments" and "Databases" as input options and a confidence score of 0.400. Second, we determined the centrality values (closeness, stress, degree or connectivity, and betweenness) for the "BIOMARK" members by using the Cytoscape software. We found Ubiquitin C (UBC), Jun proto-oncogene (JUN), and matrix metalloproteinase-14 (MMP14) as the most central hub- and non-hub-bottlenecks among the 211 genes/proteins of the whole interactome. We conclude that UBC, JUN, and MMP14 are likely an optimal candidate group of host-derived biomarkers, in combination with oral pathogenic bacteria-derived proteins, for detecting periodontitis at its early phase by using salivary samples from patients. These findings therefore have broader relevance for systems medicine in global health as well.

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE PAGES

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph; ...

2016-11-14

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Systems biology for organotypic cell cultures.

PubMed

Grego, Sonia; Dougherty, Edward R; Alexander, Francis J; Auerbach, Scott S; Berridge, Brian R; Bittner, Michael L; Casey, Warren; Cooley, Philip C; Dash, Ajit; Ferguson, Stephen S; Fennell, Timothy R; Hawkins, Brian T; Hickey, Anthony J; Kleensang, Andre; Liebman, Michael N J; Martin, Florian; Maull, Elizabeth A; Paragas, Jason; Qiao, Guilin Gary; Ramaiahgari, Sreenivasa; Sumner, Susan J; Yoon, Miyoung

2017-01-01

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications

PubMed Central

2011-01-01

Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework. PMID:21806842

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications.

PubMed

Katayama, Toshiaki; Wilkinson, Mark D; Vos, Rutger; Kawashima, Takeshi; Kawashima, Shuichi; Nakao, Mitsuteru; Yamamoto, Yasunori; Chun, Hong-Woo; Yamaguchi, Atsuko; Kawano, Shin; Aerts, Jan; Aoki-Kinoshita, Kiyoko F; Arakawa, Kazuharu; Aranda, Bruno; Bonnal, Raoul Jp; Fernández, José M; Fujisawa, Takatomo; Gordon, Paul Mk; Goto, Naohisa; Haider, Syed; Harris, Todd; Hatakeyama, Takashi; Ho, Isaac; Itoh, Masumi; Kasprzyk, Arek; Kido, Nobuhiro; Kim, Young-Joo; Kinjo, Akira R; Konishi, Fumikazu; Kovarskaya, Yulia; von Kuster, Greg; Labarga, Alberto; Limviphuvadh, Vachiranee; McCarthy, Luke; Nakamura, Yasukazu; Nam, Yunsun; Nishida, Kozo; Nishimura, Kunihiro; Nishizawa, Tatsuya; Ogishima, Soichi; Oinn, Tom; Okamoto, Shinobu; Okuda, Shujiro; Ono, Keiichiro; Oshita, Kazuki; Park, Keun-Joon; Putnam, Nicholas; Senger, Martin; Severin, Jessica; Shigemoto, Yasumasa; Sugawara, Hideaki; Taylor, James; Trelles, Oswaldo; Yamasaki, Chisato; Yamashita, Riu; Satoh, Noriyuki; Takagi, Toshihisa

2011-08-02

The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.

Supportive Care: Time to Change Our Prognostic Tools and Their Use in CKD

PubMed Central

Hemmelgarn, Brenda; Kotanko, Peter; Germain, Michael J.; Moranne, Olivier; Davison, Sara N.

2016-01-01

In using a patient-centered approach, neither a clinician nor a prognostic score can predict with absolute certainty how well a patient will do or how long he will live; however, validated prognostic scores may improve accuracy of prognostic estimates, thereby enhancing the ability of the clinicians to appreciate the individual burden of disease and the prognosis of their patients and inform them accordingly. They may also facilitate nephrologist’s recommendation of dialysis services to those who may benefit and proposal of alternative care pathways that might better respect patients’ values and goals to those who are unlikely to benefit. The purpose of this article is to discuss the use as well as the limits and deficiencies of currently available prognostic tools. It will describe new predictors that could be integrated in future scores and the role of patients’ priorities in development of new scores. Delivering patient-centered care requires an understanding of patients’ priorities that are important and relevant to them. Because of limits of available scores, the contribution of new prognostic tools with specific markers of the trajectories for patients with CKD and patients’ health reports should be evaluated in relation to their transportability to different clinical and cultural contexts and their potential for integration into the decision-making processes. The benefit of their use then needs to be quantified in clinical practice by outcome studies including health–related quality of life, patient and caregiver satisfaction, or utility for improving clinical management pathways and tailoring individualized patient–centered strategies of care. Future research also needs to incorporate qualitative methods involving patients and their caregivers to better understand the barriers and facilitators to use of these tools in the clinical setting. Information given to patients should be supported by a more realistic approach to what dialysis is likely to entail for the individual patient in terms of likely quality and quantity of life according to the patient’s values and goals and not just the possibility of life prolongation. PMID:27510452

Application of a New Integrated Decision Support Tool (i-DST) for Urban Water Infrastructure: Analyzing Water Quality Compliance Pathways for Three Los Angeles Watersheds

NASA Astrophysics Data System (ADS)

Gallo, E. M.; Hogue, T. S.; Bell, C. D.; Spahr, K.; McCray, J. E.

2017-12-01

The water quality of receiving streams and waterbodies in urban watersheds are increasingly polluted from stormwater runoff. The implementation of Green Infrastructure (GI), which includes Low Impact Developments (LIDs) and Best Management Practices (BMPs), within a watershed aim to mitigate the effects of urbanization by reducing pollutant loads, runoff volume, and storm peak flow. Stormwater modeling is generally used to assess the impact of GIs implemented within a watershed. These modeling tools are useful for determining the optimal suite of GIs to maximize pollutant load reduction and minimize cost. However, stormwater management for most resource managers and communities also includes the implementation of grey and hybrid stormwater infrastructure. An integrated decision support tool, called i-DST, that allows for the optimization and comprehensive life-cycle cost assessment of grey, green, and hybrid stormwater infrastructure, is currently being developed. The i-DST tool will evaluate optimal stormwater runoff management by taking into account the diverse economic, environmental, and societal needs associated with watersheds across the United States. Three watersheds from southern California will act as a test site and assist in the development and initial application of the i-DST tool. The Ballona Creek, Dominguez Channel, and Los Angeles River Watersheds are located in highly urbanized Los Angeles County. The water quality of the river channels flowing through each are impaired by heavy metals, including copper, lead, and zinc. However, despite being adjacent to one another within the same county, modeling results, using EPA System for Urban Stormwater Treatment and Analysis INtegration (SUSTAIN), found that the optimal path to compliance in each watershed differs significantly. The differences include varied costs, suites of BMPs, and ancillary benefits. This research analyzes how the economic, physical, and hydrological differences between the three watersheds shape the optimal plan for stormwater management.

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, Zachary A.; Drager, Andreas; Ebrahim, Ali

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

PubMed Central

King, Zachary A.; Dräger, Andreas; Ebrahim, Ali; Sonnenschein, Nikolaus; Lewis, Nathan E.; Palsson, Bernhard O.

2015-01-01

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools. PMID:26313928

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

DOE PAGES

King, Zachary A.; Drager, Andreas; Ebrahim, Ali; ...

2015-08-27

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics).more » Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.« less

CycADS: an annotation database system to ease the development and update of BioCyc databases

PubMed Central

Vellozo, Augusto F.; Véron, Amélie S.; Baa-Puyoulet, Patrice; Huerta-Cepas, Jaime; Cottret, Ludovic; Febvay, Gérard; Calevro, Federica; Rahbé, Yvan; Douglas, Angela E.; Gabaldón, Toni; Sagot, Marie-France; Charles, Hubert; Colella, Stefano

2011-01-01

In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org PMID:21474551

Dissecting Cell-Fate Determination Through Integrated Mathematical Modeling of the ERK/MAPK Signaling Pathway.

PubMed

Shin, Sung-Young; Nguyen, Lan K

2017-01-01

The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three examples of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

PubMed

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

NRF2-ome: an integrated web resource to discover protein interaction and regulatory networks of NRF2.

PubMed

Türei, Dénes; Papp, Diána; Fazekas, Dávid; Földvári-Nagy, László; Módos, Dezső; Lenti, Katalin; Csermely, Péter; Korcsmáros, Tamás

2013-01-01

NRF2 is the master transcriptional regulator of oxidative and xenobiotic stress responses. NRF2 has important roles in carcinogenesis, inflammation, and neurodegenerative diseases. We developed an online resource, NRF2-ome, to provide an integrated and systems-level database for NRF2. The database contains manually curated and predicted interactions of NRF2 as well as data from external interaction databases. We integrated NRF2 interactome with NRF2 target genes, NRF2 regulating TFs, and miRNAs. We connected NRF2-ome to signaling pathways to allow mapping upstream NRF2 regulatory components that could directly or indirectly influence NRF2 activity totaling 35,967 protein-protein and signaling interactions. The user-friendly website allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. We illustrated the applicability of the website by suggesting a posttranscriptional negative feedback of NRF2 by MAFG protein and raised the possibility of a connection between NRF2 and the JAK/STAT pathway through STAT1 and STAT3. NRF2-ome can also be used as an evaluation tool to help researchers and drug developers to understand the hidden regulatory mechanisms in the complex network of NRF2.

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Preliminary Results from an Integrated Airborne EM and Aeromagnetic Survey in Yellowstone National Park

NASA Astrophysics Data System (ADS)

Dickey, K.; Holbrook, W. S.; Finn, C.; Auken, E.; Carr, B.; Sims, K. W. W.; Bedrosian, P.; Lowenstern, J. B.; Hurwitz, S.; Pedersen, J. B. B.

2017-12-01

Yellowstone National Park hosts over 10,000 thermal features (e.g. geysers, fumaroles, mud pots, and hot springs), yet little is known about the circulation depth of meteoric water feeding these features, nor the lithological and structural bounds on the pathways that guide deep, hot fluids to the surface. Previous near-surface geophysical studies have been effective in imaging shallow hydrothermal pathways in some areas of the park, but these methods are difficult to conduct over the large areas needed to characterize entire hydrothermal systems. Transient electromagnetic (TEM) soundings and 2D direct current (DC) resistivity profiles show that hydrothermal fluids at active sites have a higher electrical conductivity than the surrounding hydrothermally inactive areas. For that reason, airborne TEM is an effective method to characterize large areas and identify hydrothermally active and inactive zones using electrical conductivity. Aeromagnetic data have been useful in mapping faults that localize hot springs, making the integration of aeromagnetic and EM data effective for structurally characterizing fluid pathways. Here we present the preliminary results from an airborne transient electromagnetic (TEM) and magnetic survey acquired jointly by the U.S. Geological Survey (USGS) and the University of Wyoming (UW) in November 2016. We integrate the EM and magnetic data for the purpose of edge detection of rhyolite flow boundaries as well as source depth of hydrothermal features. The maximum horizontal gradient technique applied on magnetic data is a useful tool that used to estimate source depth as well as indicate faults and fractures. The integration of EM with magnetics allows us to distinguish hydrothermally altered fault systems that guide fluids in the subsurface. We have used preliminary 2D inversions of EM from Aarhus Workbench to delineate rhyolite flow edges in the upper 300-600 meters and cross-checked those boundaries with the aeromagnetic map.

An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

PubMed Central

Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

2008-01-01

Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

PubMed

Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

2008-10-01

This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.

A method and software framework for enriching private biomedical sources with data from public online repositories.

PubMed

Anguita, Alberto; García-Remesal, Miguel; Graf, Norbert; Maojo, Victor

2016-04-01

Modern biomedical research relies on the semantic integration of heterogeneous data sources to find data correlations. Researchers access multiple datasets of disparate origin, and identify elements-e.g. genes, compounds, pathways-that lead to interesting correlations. Normally, they must refer to additional public databases in order to enrich the information about the identified entities-e.g. scientific literature, published clinical trial results, etc. While semantic integration techniques have traditionally focused on providing homogeneous access to private datasets-thus helping automate the first part of the research, and there exist different solutions for browsing public data, there is still a need for tools that facilitate merging public repositories with private datasets. This paper presents a framework that automatically locates public data of interest to the researcher and semantically integrates it with existing private datasets. The framework has been designed as an extension of traditional data integration systems, and has been validated with an existing data integration platform from a European research project by integrating a private biological dataset with data from the National Center for Biotechnology Information (NCBI). Copyright © 2016 Elsevier Inc. All rights reserved.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

PubMed Central

Caspi, Ron; Altman, Tomer; Dale, Joseph M.; Dreher, Kate; Fulcher, Carol A.; Gilham, Fred; Kaipa, Pallavi; Karthikeyan, Athikkattuvalasu S.; Kothari, Anamika; Krummenacker, Markus; Latendresse, Mario; Mueller, Lukas A.; Paley, Suzanne; Popescu, Liviu; Pujar, Anuradha; Shearer, Alexander G.; Zhang, Peifen; Karp, Peter D.

2010-01-01

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism. PMID:19850718

SATRAT: Staphylococcus aureus transcript regulatory network analysis tool.

PubMed

Gopal, Tamilselvi; Nagarajan, Vijayaraj; Elasri, Mohamed O

2015-01-01

Staphylococcus aureus is a commensal organism that primarily colonizes the nose of healthy individuals. S. aureus causes a spectrum of infections that range from skin and soft-tissue infections to fatal invasive diseases. S. aureus uses a large number of virulence factors that are regulated in a coordinated fashion. The complex regulatory mechanisms have been investigated in numerous high-throughput experiments. Access to this data is critical to studying this pathogen. Previously, we developed a compilation of microarray experimental data to enable researchers to search, browse, compare, and contrast transcript profiles. We have substantially updated this database and have built a novel exploratory tool-SATRAT-the S. aureus transcript regulatory network analysis tool, based on the updated database. This tool is capable of performing deep searches using a query and generating an interactive regulatory network based on associations among the regulators of any query gene. We believe this integrated regulatory network analysis tool would help researchers explore the missing links and identify novel pathways that regulate virulence in S. aureus. Also, the data model and the network generation code used to build this resource is open sourced, enabling researchers to build similar resources for other bacterial systems.

Toward industrial production of isoprenoids in Escherichia coli: Lessons learned from CRISPR-Cas9 based optimization of a chromosomally integrated mevalonate pathway.

PubMed

Alonso-Gutierrez, Jorge; Koma, Daisuke; Hu, Qijun; Yang, Yuchen; Chan, Leanne J G; Petzold, Christopher J; Adams, Paul D; Vickers, Claudia E; Nielsen, Lars K; Keasling, Jay D; Lee, Taek S

2018-04-01

Escherichia coli has been the organism of choice for the production of different chemicals by engineering native and heterologous pathways. In the present study, we simultaneously address some of the main issues associated with E. coli as an industrial platform for isoprenoids, including an inability to grow on sucrose, a lack of endogenous control over toxic mevalonate (MVA) pathway intermediates, and the limited pathway engineering into the chromosome. As a proof of concept, we generated an E. coli DH1 strain able to produce the isoprenoid bisabolene from sucrose by integrating the cscAKB operon into the chromosome and by expressing a heterologous MVA pathway under stress-responsive control. Production levels dropped dramatically relative to plasmid-mediated expression when the entire pathway was integrated into the chromosome. In order to optimize the chromosomally integrated MVA pathway, we established a CRISPR-Cas9 system to rapidly and systematically replace promoter sequences. This strategy led to higher pathway expression and a fivefold improvement in bisabolene production. More interestingly, we analyzed proteomics data sets to understand and address some of the challenges associated with metabolic engineering of the chromosomally integrated pathway. This report shows that integrating plasmid-optimized operons into the genome and making them work optimally is not a straightforward task and any poor engineering choices on the chromosome may lead to cell death rather than just resulting in low titers. Based on these results, we also propose directions for chromosomal metabolic engineering. © 2017 Wiley Periodicals, Inc.

Integrated palliative care in the Spanish context: a systematic review of the literature.

PubMed

Garralda, Eduardo; Hasselaar, Jeroen; Carrasco, José Miguel; Van Beek, Karen; Siouta, Naouma; Csikos, Agnes; Menten, Johan; Centeno, Carlos

2016-05-13

Integrated palliative care (IPC) involves bringing together administrative, organisational, clinical and service aspects in order to achieve continuity of care between all actors involved in the care network of patients receiving palliative care (PC) services. The purpose of this study is to identify literature on IPC in the Spanish context, either in cancer or other advanced chronic diseases. Systematic review of the literature about IPC published in Spain between 1995 and 2013. Sources searched included PubMed, Cochrane Library, Cinahl, the national palliative care Journal (Medicina Paliativa), and Google. Evidence on IPC in care models, pathways, guidelines and other relevant documents were searched. Additionally, data were included from expert sources. Elements of IPC were considered based on the definition of IPC and the Emmanuel´s IPC tool. The main inclusion criterion was a comprehensive description of PC integration. Out of a total of 2,416 titles screened, 49 were included. We found two models describing IPC interventions achieving continuity and appropriateness of care as a result, 12 guidelines or pathways (most of them with a general approach including cancer and non-cancer and showing a theoretical IPC inclusion as measured by Emmanuel's tool) and 35 other significant documents as for their context relevance (17 health strategy documents, 14 analytical studies and 4 descriptive documents). These last documents comprised respectively: regional and national plans with an IPC inclusion evidence, studies focused on IPC into primary care and resource utilisation; and descriptions of fruitful collaboration programmes between PC teams and oncology departments. The results show that explications of IPC in the Spanish literature exist, but that there is insufficient evidence of its impact in clinical practice. This review may be of interest for Spanish-speaking countries and for others seeking to know the status of IPC in the literature in their home nations.

Metabolic pathways for the whole community.

PubMed

Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

2014-07-22

A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

Synthetic biology: applying biological circuits beyond novel therapies.

PubMed

Dobrin, Anton; Saxena, Pratik; Fussenegger, Martin

2016-04-18

Synthetic biology, an engineering, circuit-driven approach to biology, has developed whole new classes of therapeutics. Unfortunately, these advances have thus far been undercapitalized upon by basic researchers. As discussed herein, using synthetic circuits, one can undertake exhaustive investigations of the endogenous circuitry found in nature, develop novel detectors and better temporally and spatially controlled inducers. One could detect changes in DNA, RNA, protein or even transient signaling events, in cell-based systems, in live mice, and in humans. Synthetic biology has also developed inducible systems that can be induced chemically, optically or using radio waves. This induction has been re-wired to lead to changes in gene expression, RNA stability and splicing, protein stability and splicing, and signaling via endogenous pathways. Beyond simple detectors and inducible systems, one can combine these modalities and develop novel signal integration circuits that can react to a very precise pre-programmed set of conditions or even to multiple sets of precise conditions. In this review, we highlight some tools that were developed in which these circuits were combined such that the detection of a particular event automatically triggered a specific output. Furthermore, using novel circuit-design strategies, circuits have been developed that can integrate multiple inputs together in Boolean logic gates composed of up to 6 inputs. We highlight the tools available and what has been developed thus far, and highlight how some clinical tools can be very useful in basic science. Most of the systems that are presented can be integrated together; and the possibilities far exceed the number of currently developed strategies.

Catchment Models and Management Tools for diffuse Contaminants (Sediment, Phosphorus and Pesticides): DIFFUSE Project

NASA Astrophysics Data System (ADS)

Mockler, Eva; Reaney, Simeon; Mellander, Per-Erik; Wade, Andrew; Collins, Adrian; Arheimer, Berit; Bruen, Michael

2017-04-01

The agricultural sector is the most common suspected source of nutrient pollution in Irish rivers. However, it is also often the most difficult source to characterise due to its predominantly diffuse nature. Particulate phosphorus in surface water and dissolved phosphorus in groundwater are of particular concern in Irish water bodies. Hence the further development of models and indices to assess diffuse sources of contaminants are required for use by the Irish Environmental Protection Agency (EPA) to provide support for river basin planning. Understanding connectivity in the landscape is a vital component of characterising the source-pathway-receptor relationships for water-borne contaminants, and hence is a priority in this research. The DIFFUSE Project will focus on connectivity modelling and incorporation of connectivity into sediment, nutrient and pesticide risk mapping. The Irish approach to understanding and managing natural water bodies has developed substantially in recent years assisted by outputs from multiple research projects, including modelling and analysis tools developed during the Pathways and CatchmentTools projects. These include the Pollution Impact Potential (PIP) maps, which are an example of research output that is used by the EPA to support catchment management. The PIP maps integrate an understanding of the pollution pressures and mobilisation pathways and, using the source-pathways-receptor model, provide a scientific basis for evaluation of mitigation measures. These maps indicate the potential risk posed by nitrate and phosphate from diffuse agricultural sources to surface and groundwater receptors and delineate critical source areas (CSAs) as a means of facilitating the targeting of mitigation measures. Building on this previous research, the DIFFUSE Project will develop revised and new catchment managements tools focused on connectivity, sediment, phosphorus and pesticides. The DIFFUSE project will strive to identify the state-of-the-art methods and models that are most applicable to Irish conditions and management challenges. All styles of modelling considered useful for water resources management are relevant to this project and a balance of technical sophistication, data availability and operational practicalities is the ultimate goal. Achievement of this objective will be measured by comparing the performance of the new models developed in the project with models used in other countries. The models and tools developed in the course of the project will be evaluated by comparison with Irish catchment data and with other state-of-the-art models in a model-inter-comparison workshop which will be open to other models and the wider research community.

A practical guide to diagnostic transcranial magnetic stimulation: Report of an IFCN committee

PubMed Central

Groppa, S.; Oliviero, A.; Eisen, A.; Quartarone, A.; Cohen, L.G.; Mall, V.; Kaelin-Lang, A.; Mima, T.; Rossi, S.; Thickbroom, G.W.; Rossini, P.M.; Ziemann, U.; Valls-Solé, J.; Siebner, H.R.

2016-01-01

Transcranial magnetic stimulation (TMS) is an established neurophysiological tool to examine the integrity of the fast-conducting corticomotor pathways in a wide range of diseases associated with motor dysfunction. This includes but is not limited to patients with multiple sclerosis, amyotrophic lateral sclerosis, stroke, movement disorders, disorders affecting the spinal cord, facial and other cranial nerves. These guidelines cover practical aspects of TMS in a clinical setting. We first discuss the technical and physiological aspects of TMS that are relevant for the diagnostic use of TMS. We then lay out the general principles that apply to a standardized clinical examination of the fast-conducting corticomotor pathways with single-pulse TMS. This is followed by a detailed description of how to examine corticomotor conduction to the hand, leg, trunk and facial muscles in patients. Additional sections cover safety issues, the triple stimulation technique, and neuropediatric aspects of TMS. PMID:22349304

Protein design in systems metabolic engineering for industrial strain development.

PubMed

Chen, Zhen; Zeng, An-Ping

2013-05-01

Accelerating the process of industrial bacterial host strain development, aimed at increasing productivity, generating new bio-products or utilizing alternative feedstocks, requires the integration of complementary approaches to manipulate cellular metabolism and regulatory networks. Systems metabolic engineering extends the concept of classical metabolic engineering to the systems level by incorporating the techniques used in systems biology and synthetic biology, and offers a framework for the development of the next generation of industrial strains. As one of the most useful tools of systems metabolic engineering, protein design allows us to design and optimize cellular metabolism at a molecular level. Here, we review the current strategies of protein design for engineering cellular synthetic pathways, metabolic control systems and signaling pathways, and highlight the challenges of this subfield within the context of systems metabolic engineering. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Engineering plant metabolism into microbes: from systems biology to synthetic biology.

PubMed

Xu, Peng; Bhan, Namita; Koffas, Mattheos A G

2013-04-01

Plant metabolism represents an enormous repository of compounds that are of pharmaceutical and biotechnological importance. Engineering plant metabolism into microbes will provide sustainable solutions to produce pharmaceutical and fuel molecules that could one day replace substantial portions of the current fossil-fuel based economy. Metabolic engineering entails targeted manipulation of biosynthetic pathways to maximize yields of desired products. Recent advances in Systems Biology and the emergence of Synthetic Biology have accelerated our ability to design, construct and optimize cell factories for metabolic engineering applications. Progress in predicting and modeling genome-scale metabolic networks, versatile gene assembly platforms and delicate synthetic pathway optimization strategies has provided us exciting opportunities to exploit the full potential of cell metabolism. In this review, we will discuss how systems and synthetic biology tools can be integrated to create tailor-made cell factories for efficient production of natural products and fuel molecules in microorganisms. Copyright © 2012 Elsevier Ltd. All rights reserved.

Emerging Imaging and Genomic Tools for Developmental Systems Biology.

PubMed

Liu, Zhe; Keller, Philipp J

2016-03-21

Animal development is a complex and dynamic process orchestrated by exquisitely timed cell lineage commitment, divisions, migration, and morphological changes at the single-cell level. In the past decade, extensive genetic, stem cell, and genomic studies provided crucial insights into molecular underpinnings and the functional importance of genetic pathways governing various cellular differentiation processes. However, it is still largely unknown how the precise coordination of these pathways is achieved at the whole-organism level and how the highly regulated spatiotemporal choreography of development is established in turn. Here, we discuss the latest technological advances in imaging and single-cell genomics that hold great promise for advancing our understanding of this intricate process. We propose an integrated approach that combines such methods to quantitatively decipher in vivo cellular dynamic behaviors and their underlying molecular mechanisms at the systems level with single-cell, single-molecule resolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Prospects for engineering dynamic CRISPR-Cas transcriptional circuits to improve bioproduction.

PubMed

Fontana, Jason; Voje, William E; Zalatan, Jesse G; Carothers, James M

2018-05-08

Dynamic control of gene expression is emerging as an important strategy for controlling flux in metabolic pathways and improving bioproduction of valuable compounds. Integrating dynamic genetic control tools with CRISPR-Cas transcriptional regulation could significantly improve our ability to fine-tune the expression of multiple endogenous and heterologous genes according to the state of the cell. In this mini-review, we combine an analysis of recent literature with examples from our own work to discuss the prospects and challenges of developing dynamically regulated CRISPR-Cas transcriptional control systems for applications in synthetic biology and metabolic engineering.

Prediction of enzymatic pathways by integrative pathway mapping

PubMed Central

Wichelecki, Daniel J; San Francisco, Brian; Zhao, Suwen; Rodionov, Dmitry A; Vetting, Matthew W; Al-Obaidi, Nawar F; Lin, Henry; O'Meara, Matthew J; Scott, David A; Morris, John H; Russel, Daniel; Almo, Steven C; Osterman, Andrei L

2018-01-01

The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology. PMID:29377793

Tools and Models for Integrating Multiple Cellular Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerstein, Mark

2015-11-06

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novelmore » algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].« less

Development and Evaluation of an Educational E-Tool to Help Patients With Non-Hodgkin's Lymphoma Manage Their Personal Care Pathway.

PubMed

Stienen, Jozette Jc; Ottevanger, Petronella B; Wennekes, Lianne; Dekker, Helena M; van der Maazen, Richard Wm; Mandigers, Caroline Mpw; van Krieken, Johan Hjm; Blijlevens, Nicole Ma; Hermens, Rosella Pmg

2015-01-09

An overload of health-related information is available for patients on numerous websites, guidelines, and information leaflets. However, the increasing need for personalized health-related information is currently unmet. This study evaluates an educational e-tool for patients with non-Hodgkin's lymphoma (NHL) designed to meet patient needs with respect to personalized and complete health-related information provision. The e-tool aims to help NHL patients manage and understand their personal care pathway, by providing them with insight into their own care pathway, the possibility to keep a diary, and structured health-related information. Together with a multidisciplinary NHL expert panel, we developed an e-tool consisting of two sections: (1) a personal section for patients' own care pathway and their experiences, and (2) an informative section including information on NHL. We developed an ideal NHL care pathway based on the available (inter)national guidelines. The ideal care pathway, including date of first consultation, diagnosis, and therapy start, was used to set up the personal care pathway. The informative section was developed in collaboration with the patient association, Hematon. Regarding participants, 14 patients and 6 laymen were asked to evaluate the e-tool. The 24-item questionnaire used discussed issues concerning layout (6 questions), user convenience (3 questions), menu clarity (3 questions), information clarity (5 questions), and general impression (7 questions). In addition, the panel members were asked to give their feedback by email. A comprehensive overview of diagnostics, treatments, and aftercare can be established by patients completing the questions from the personal section. The informative section consisted of NHL information regarding NHL in general, diagnostics, therapy, aftercare, and waiting times. Regarding participants, 6 patients and 6 laymen completed the questionnaire. Overall, the feedback was positive, with at least 75% satisfaction on each feedback item. Important strengths mentioned were the use of a low health-literacy level, the opportunity to document the personal care pathway and experiences, and the clear overview of the information provided. The added value of the e-tool in general was pointed out as very useful for preparing the consultation with one's doctor and for providing all information on one website, including the opportunity for a personalized care pathway and diary. The majority of the revisions concerned wording and clarity. In addition, more explicit information on immunotherapy, experimental therapy, and psychosocial support was added. We have developed a personal care management e-tool for NHL patients. This tool contains a unique way to help patients manage their personal care pathway and give them insight into their NHL by providing health-related information and a personal diary. This evaluation showed that our e-tool meets patients' needs concerning personalized health-related information, which might serve as a good example for other oncologic diseases. Future research should focus on the possible impact of the e-tool on doctor-patient communication during consultations.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.

PubMed

Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí

2014-11-28

The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

PubMed Central

2014-01-01

Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Southern Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinatedmore » operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: to better anticipate, understand, and mitigate system constraints that could affect RE integration; and to provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.« less

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Western Region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinatedmore » operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.« less

Application of the critical pathway and integrated case teaching method to nursing orientation.

PubMed

Goodman, D

1997-01-01

Nursing staff development programs must be responsive to current changes in healthcare. New nursing staff must be prepared to manage continuous change and to function competently in clinical practice. The orientation pathway, based on a case management model, is used as a structure for the orientation phase of staff development. The integrated case is incorporated as a teaching strategy in orientation. The integrated case method is based on discussion and analysis of patient situations with emphasis on role modeling and integration of theory and skill. The orientation pathway and integrated case teaching method provide a useful framework for orientation of new staff. Educators, preceptors and orientees find the structure provided by the orientation pathway very useful. Orientation that is developed, implemented and evaluated based on a case management model with the use of an orientation pathway and incorporation of an integrated case teaching method provides a standardized structure for orientation of new staff. This approach is designed for the adult learner, promotes conceptual reasoning, and encourages the social and contextual basis for continued learning.

Indicators and Measurement Tools for Health Systems Integration: A Knowledge Synthesis.

PubMed

Suter, Esther; Oelke, Nelly D; da Silva Lima, Maria Alice Dias; Stiphout, Michelle; Janke, Robert; Witt, Regina Rigatto; Van Vliet-Brown, Cheryl; Schill, Kaela; Rostami, Mahnoush; Hepp, Shelanne; Birney, Arden; Al-Roubaiai, Fatima; Marques, Giselda Quintana

2017-11-13

Despite far reaching support for integrated care, conceptualizing and measuring integrated care remains challenging. This knowledge synthesis aimed to identify indicator domains and tools to measure progress towards integrated care. We used an established framework and a Delphi survey with integration experts to identify relevant measurement domains. For each domain, we searched and reviewed the literature for relevant tools. From 7,133 abstracts, we retrieved 114 unique tools. We found many quality tools to measure care coordination, patient engagement and team effectiveness/performance. In contrast, there were few tools in the domains of performance measurement and information systems, alignment of organizational goals and resource allocation. The search yielded 12 tools that measure overall integration or three or more indicator domains. Our findings highlight a continued gap in tools to measure foundational components that support integrated care. In the absence of such targeted tools, "overall integration" tools may be useful for a broad assessment of the overall state of a system. Continued progress towards integrated care depends on our ability to evaluate the success of strategies across different levels and context. This study has identified 114 tools that measure integrated care across 16 domains, supporting efforts towards a unified measurement framework.

An integrated Biophysical CGE model to provide Sustainable Development Goal insights

NASA Astrophysics Data System (ADS)

Sanchez, Marko; Cicowiez, Martin; Howells, Mark; Zepeda, Eduardo

2016-04-01

Future projected changes in the energy system will inevitably result in changes to the level of appropriation of environmental resources, particularly land and water, and this will have wider implications for environmental sustainability, and may affect other sectors of the economy. An integrated climate, land, energy and water (CLEW) system will provide useful insights, particularly with regard to the environmental sustainability. However, it will require adequate integration with other tools to detect economic impacts and broaden the scope for policy analysis. A computable general equilibrium (CGE) model is a well suited tool to channel impacts, as detected in a CLEW analysis, onto all sectors of the economy, and evaluate trade-offs and synergies, including those of possible policy responses. This paper will show an application of such integration in a single-country CGE model with the following key characteristics. Climate is partly exogenous (as proxied by temperature and rainfall) and partly endogenous (as proxied by emissions generated by different sectors) and has an impact on endogenous variables such as land productivity and labor productivity. Land is a factor of production used in agricultural and forestry activities which can be of various types if land use alternatives (e.g., deforestation) are to be considered. Energy is an input to the production process of all economic sectors and a consumption good for households. Because it is possible to allow for substitution among different energy sources (e.g. renewable vs non-renewable) in the generation of electricity, the production process of energy products can consider the use of natural resources such as oil and water. Water, data permitting, can be considered as an input into the production process of agricultural sectors, which is particularly relevant in case of irrigation. It can also be considered as a determinant of total factor productivity in hydro-power generation. The integration of a CLEW system and a CGE model can be critical to inform analyses on different climate impacts and ways to "secure" pathways of sustainable natural resource use and energy generation. Cost and benefits for establishing sustainable pathways through different investments and their macroeconomic feasibility and impacts on economic growth and employment are also captured. This information is critical to inform strategies to achieve sustainable development goals.

TabPath: interactive tables for metabolic pathway analysis.

PubMed

Moraes, Lauro Ângelo Gonçalves de; Felestrino, Érica Barbosa; Assis, Renata de Almeida Barbosa; Matos, Diogo; Lima, Joubert de Castro; Lima, Leandro de Araújo; Almeida, Nalvo Franco; Setubal, João Carlos; Garcia, Camila Carrião Machado; Moreira, Leandro Marcio

2018-03-15

Information about metabolic pathways in a comparative context is one of the most powerful tool to help the understanding of genome-based differences in phenotypes among organisms. Although several platforms exist that provide a wealth of information on metabolic pathways of diverse organisms, the comparison among organisms using metabolic pathways is still a difficult task. We present TabPath (Tables for Metabolic Pathway), a web-based tool to facilitate comparison of metabolic pathways in genomes based on KEGG. From a selection of pathways and genomes of interest on the menu, TabPath generates user-friendly tables that facilitate analysis of variations in metabolism among the selected organisms. TabPath is available at http://200.239.132.160:8686. lmmorei@gmail.com.

Spatial awareness comparisons between large-screen, integrated pictorial displays and conventional EFIS displays during simulated landing approaches

NASA Technical Reports Server (NTRS)

Parrish, Russell V.; Busquets, Anthony M.; Williams, Steven P.; Nold, Dean E.

1994-01-01

An extensive simulation study was performed to determine and compare the spatial awareness of commercial airline pilots on simulated landing approaches using conventional flight displays with their awareness using advanced pictorial 'pathway in the sky' displays. Sixteen commercial airline pilots repeatedly made simulated complex microwave landing system approaches to closely spaced parallel runways with an extremely short final segment. Scenarios involving conflicting traffic situation assessments and recoveries from flight path offset conditions were used to assess spatial awareness (own ship position relative the the desired flight route, the runway, and other traffic) with the various display formats. The situation assessment tools are presented, as well as the experimental designs and the results. The results demonstrate that the integrated pictorial displays substantially increase spatial awareness over conventional electronic flight information systems display formats.

Measuring Best Practices for Workplace Safety, Health, and Well-Being: The Workplace Integrated Safety and Health Assessment.

PubMed

Sorensen, Glorian; Sparer, Emily; Williams, Jessica A R; Gundersen, Daniel; Boden, Leslie I; Dennerlein, Jack T; Hashimoto, Dean; Katz, Jeffrey N; McLellan, Deborah L; Okechukwu, Cassandra A; Pronk, Nicolaas P; Revette, Anna; Wagner, Gregory R

2018-05-01

To present a measure of effective workplace organizational policies, programs, and practices that focuses on working conditions and organizational facilitators of worker safety, health and well-being: the workplace integrated safety and health (WISH) assessment. Development of this assessment used an iterative process involving a modified Delphi method, extensive literature reviews, and systematic cognitive testing. The assessment measures six core constructs identified as central to best practices for protecting and promoting worker safety, health and well-being: leadership commitment; participation; policies, programs, and practices that foster supportive working conditions; comprehensive and collaborative strategies; adherence to federal and state regulations and ethical norms; and data-driven change. The WISH Assessment holds promise as a tool that may inform organizational priority setting and guide research around causal pathways influencing implementation and outcomes related to these approaches.

Groups: knowledge spreadsheets for symbolic biocomputing.

PubMed

Travers, Michael; Paley, Suzanne M; Shrager, Jeff; Holland, Timothy A; Karp, Peter D

2013-01-01

Knowledge spreadsheets (KSs) are a visual tool for interactive data analysis and exploration. They differ from traditional spreadsheets in that rather than being oriented toward numeric data, they work with symbolic knowledge representation structures and provide operations that take into account the semantics of the application domain. 'Groups' is an implementation of KSs within the Pathway Tools system. Groups allows Pathway Tools users to define a group of objects (e.g. groups of genes or metabolites) from a Pathway/Genome Database. Groups can be transformed (e.g. by transforming a metabolite group to the group of pathways in which those metabolites are substrates); combined through set operations; analysed (e.g. through enrichment analysis); and visualized (e.g. by painting onto a metabolic map diagram). Users of the Pathway Tools-based BioCyc.org website have made extensive use of Groups, and an informal survey of Groups users suggests that Groups has achieved the goal of allowing biologists themselves to perform some data manipulations that previously would have required the assistance of a programmer. Database URL: BioCyc.org.

Audio-visual integration through the parallel visual pathways.

PubMed

Kaposvári, Péter; Csete, Gergő; Bognár, Anna; Csibri, Péter; Tóth, Eszter; Szabó, Nikoletta; Vécsei, László; Sáry, Gyula; Tamás Kincses, Zsigmond

2015-10-22

Audio-visual integration has been shown to be present in a wide range of different conditions, some of which are processed through the dorsal, and others through the ventral visual pathway. Whereas neuroimaging studies have revealed integration-related activity in the brain, there has been no imaging study of the possible role of segregated visual streams in audio-visual integration. We set out to determine how the different visual pathways participate in this communication. We investigated how audio-visual integration can be supported through the dorsal and ventral visual pathways during the double flash illusion. Low-contrast and chromatic isoluminant stimuli were used to drive preferably the dorsal and ventral pathways, respectively. In order to identify the anatomical substrates of the audio-visual interaction in the two conditions, the psychophysical results were correlated with the white matter integrity as measured by diffusion tensor imaging.The psychophysiological data revealed a robust double flash illusion in both conditions. A correlation between the psychophysical results and local fractional anisotropy was found in the occipito-parietal white matter in the low-contrast condition, while a similar correlation was found in the infero-temporal white matter in the chromatic isoluminant condition. Our results indicate that both of the parallel visual pathways may play a role in the audio-visual interaction. Copyright © 2015. Published by Elsevier B.V.

Application of Signaling Pathway-Based Adverse Outcome Pathways and High Throughput Toxicokinetic-PBPK for Developmental Cardiac Malformations

EPA Science Inventory

Associating putative molecular initiating events (MIE) with downstream cell signaling pathways and modeling fetal exposure kinetics is an important challenge for integration in developmental systems toxicology. Here, we describe an integrative systems toxicology model for develop...

Selective methanol or formate production during continuous CO₂ fermentation by the acetogen biocatalysts engineered via integration of synthetic pathways using Tn7-tool.

PubMed

Tyurin, Michael; Kiriukhin, Michael

2013-09-01

Methanol-resistant mutant acetogen Clostridium sp. MT1424 originally producing only 365 mM acetate from CO₂/CO was engineered to eliminate acetate production and spore formation using Cre-lox66/lox71-system to power subsequent methanol production via expressing synthetic methanol dehydrogenase, formaldehyde dehydrogenase and formate dehydrogenase, three copies of each, assembled in cluster and integrated to chromosome using Tn7-based approach. Production of 2.2 M methanol was steady (p < 0.005) in single step fermentations of 20 % CO₂ + 80 % H₂ blend (v/v) 25 day runs each in five independent repeats. If the integrated cluster comprised only three copies of formate dehydrogenase the respective recombinants produced 95 mM formate (p < 0.005) under the same conditions. For commercialization, the suggested source of inorganic carbon would be CO₂ waste of IGCC power plant. Hydrogen may be produced in situ via powered by solar panels electrolysis.

PathVisio 3: an extendable pathway analysis toolbox.

PubMed

Kutmon, Martina; van Iersel, Martijn P; Bohler, Anwesha; Kelder, Thomas; Nunes, Nuno; Pico, Alexander R; Evelo, Chris T

2015-02-01

PathVisio is a commonly used pathway editor, visualization and analysis software. Biological pathways have been used by biologists for many years to describe the detailed steps in biological processes. Those powerful, visual representations help researchers to better understand, share and discuss knowledge. Since the first publication of PathVisio in 2008, the original paper was cited more than 170 times and PathVisio was used in many different biological studies. As an online editor PathVisio is also integrated in the community curated pathway database WikiPathways. Here we present the third version of PathVisio with the newest additions and improvements of the application. The core features of PathVisio are pathway drawing, advanced data visualization and pathway statistics. Additionally, PathVisio 3 introduces a new powerful extension systems that allows other developers to contribute additional functionality in form of plugins without changing the core application. PathVisio can be downloaded from http://www.pathvisio.org and in 2014 PathVisio 3 has been downloaded over 5,500 times. There are already more than 15 plugins available in the central plugin repository. PathVisio is a freely available, open-source tool published under the Apache 2.0 license (http://www.apache.org/licenses/LICENSE-2.0). It is implemented in Java and thus runs on all major operating systems. The code repository is available at http://svn.bigcat.unimaas.nl/pathvisio. The support mailing list for users is available on https://groups.google.com/forum/#!forum/wikipathways-discuss and for developers on https://groups.google.com/forum/#!forum/wikipathways-devel.

EPA EcoBox Tools by Exposure Pathways - Exposure Pathways In ERA

EPA Pesticide Factsheets

Eco-Box is a toolbox for exposure assessors. Its purpose is to provide a compendium of exposure assessment and risk characterization tools that will present comprehensive step-by-step guidance and links to relevant exposure assessment data bases

miRwayDB: a database for experimentally validated microRNA-pathway associations in pathophysiological conditions

PubMed Central

Das, Sankha Subhra; Saha, Pritam

2018-01-01

Abstract MicroRNAs (miRNAs) are well-known as key regulators of diverse biological pathways. A series of experimental evidences have shown that abnormal miRNA expression profiles are responsible for various pathophysiological conditions by modulating genes in disease associated pathways. In spite of the rapid increase in research data confirming such associations, scientists still do not have access to a consolidated database offering these miRNA-pathway association details for critical diseases. We have developed miRwayDB, a database providing comprehensive information of experimentally validated miRNA-pathway associations in various pathophysiological conditions utilizing data collected from published literature. To the best of our knowledge, it is the first database that provides information about experimentally validated miRNA mediated pathway dysregulation as seen specifically in critical human diseases and hence indicative of a cause-and-effect relationship in most cases. The current version of miRwayDB collects an exhaustive list of miRNA-pathway association entries for 76 critical disease conditions by reviewing 663 published articles. Each database entry contains complete information on the name of the pathophysiological condition, associated miRNA(s), experimental sample type(s), regulation pattern (up/down) of miRNA, pathway association(s), targeted member of dysregulated pathway(s) and a brief description. In addition, miRwayDB provides miRNA, gene and pathway score to evaluate the role of a miRNA regulated pathways in various pathophysiological conditions. The database can also be used for other biomedical approaches such as validation of computational analysis, integrated analysis and prediction of computational model. It also offers a submission page to submit novel data from recently published studies. We believe that miRwayDB will be a useful tool for miRNA research community. Database URL: http://www.mirway.iitkgp.ac.in PMID:29688364

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond.

PubMed

Gama-Castro, Socorro; Salgado, Heladia; Santos-Zavaleta, Alberto; Ledezma-Tejeida, Daniela; Muñiz-Rascado, Luis; García-Sotelo, Jair Santiago; Alquicira-Hernández, Kevin; Martínez-Flores, Irma; Pannier, Lucia; Castro-Mondragón, Jaime Abraham; Medina-Rivera, Alejandra; Solano-Lira, Hilda; Bonavides-Martínez, César; Pérez-Rueda, Ernesto; Alquicira-Hernández, Shirley; Porrón-Sotelo, Liliana; López-Fuentes, Alejandra; Hernández-Koutoucheva, Anastasia; Del Moral-Chávez, Víctor; Rinaldi, Fabio; Collado-Vides, Julio

2016-01-04

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for 'neighborhood' genes to known operons and regulons, and computational developments. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

SuperTarget goes quantitative: update on drug–target interactions

PubMed Central

Hecker, Nikolai; Ahmed, Jessica; von Eichborn, Joachim; Dunkel, Mathias; Macha, Karel; Eckert, Andreas; Gilson, Michael K.; Bourne, Philip E.; Preissner, Robert

2012-01-01

There are at least two good reasons for the on-going interest in drug–target interactions: first, drug-effects can only be fully understood by considering a complex network of interactions to multiple targets (so-called off-target effects) including metabolic and signaling pathways; second, it is crucial to consider drug-target-pathway relations for the identification of novel targets for drug development. To address this on-going need, we have developed a web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A query interface enables the user to pose complex queries, for example, to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target proteins within a certain affinity range. SuperTarget is available at http://bioinformatics.charite.de/supertarget. PMID:22067455

The Molecular Ecophysiology of Programmed Cell Death in Marine Phytoplankton

NASA Astrophysics Data System (ADS)

Bidle, Kay D.

2015-01-01

Planktonic, prokaryotic, and eukaryotic photoautotrophs (phytoplankton) share a diverse and ancient evolutionary history, during which time they have played key roles in regulating marine food webs, biogeochemical cycles, and Earth's climate. Because phytoplankton represent the basis of marine ecosystems, the manner in which they die critically determines the flow and fate of photosynthetically fixed organic matter (and associated elements), ultimately constraining upper-ocean biogeochemistry. Programmed cell death (PCD) and associated pathway genes, which are triggered by a variety of nutrient stressors and are employed by parasitic viruses, play an integral role in determining the cell fate of diverse photoautotrophs in the modern ocean. Indeed, these multifaceted death pathways continue to shape the success and evolutionary trajectory of diverse phytoplankton lineages at sea. Research over the past two decades has employed physiological, biochemical, and genetic techniques to provide a novel, comprehensive, mechanistic understanding of the factors controlling this key process. Here, I discuss the current understanding of the genetics, activation, and regulation of PCD pathways in marine model systems; how PCD evolved in unicellular photoautotrophs; how it mechanistically interfaces with viral infection pathways; how stress signals are sensed and transduced into cellular responses; and how novel molecular and biochemical tools are revealing the impact of PCD genes on the fate of natural phytoplankton assemblages.

An "EAR" on environmental surveillance and monitoring: A ...

EPA Pesticide Factsheets

Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on chemical concentration alone, it can be difficult to identify which compounds may be of toxicological concern for prioritization for further monitoring or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high throughput screening data like the ToxCast™ database, which contains data for over 9,000 compounds screened through up to 1,100 assays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast™ effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast™ database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Biological pathways were then linked to adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts. Anthropogenic contaminants are frequently reported in environm

Imaging anatomy of the vestibular and visual systems.

PubMed

Gunny, Roxana; Yousry, Tarek A

2007-02-01

This review will outline the imaging anatomy of the vestibular and visual pathways, using computed tomography and magnetic resonance imaging, with emphasis on the more recent developments in neuroimaging. Technical advances in computed tomography and magnetic resonance imaging, such as the advent of multislice computed tomography and newer magnetic resonance imaging techniques such as T2-weighted magnetic resonance cisternography, have improved the imaging of the vestibular and visual pathways, allowing better visualization of the end organs and peripheral nerves. Higher field strength magnetic resonance imaging is a promising tool, which has been used to evaluate and resolve fine anatomic detail in vitro, as in the labyrinth. Advanced magnetic resonance imaging techniques such as functional magnetic resonance imaging and diffusion tractography have been used to identify cortical areas of activation and associated white matter pathways, and show potential for the future identification of complex neuronal relays involved in integrating these pathways. The assessment of the various components of the vestibular and the visual systems has improved with more detailed research on the imaging anatomy of these systems, the advent of high field magnetic resonance scanners and multislice computerized tomography, and the wider use of specific techniques such as tractography which displays white matter tracts not directly accessible until now.

The Banana Genome Hub

PubMed Central

Droc, Gaëtan; Larivière, Delphine; Guignon, Valentin; Yahiaoui, Nabila; This, Dominique; Garsmeur, Olivier; Dereeper, Alexis; Hamelin, Chantal; Argout, Xavier; Dufayard, Jean-François; Lengelle, Juliette; Baurens, Franc-Christophe; Cenci, Alberto; Pitollat, Bertrand; D’Hont, Angélique; Ruiz, Manuel; Rouard, Mathieu; Bocs, Stéphanie

2013-01-01

Banana is one of the world’s favorite fruits and one of the most important crops for developing countries. The banana reference genome sequence (Musa acuminata) was recently released. Given the taxonomic position of Musa, the completed genomic sequence has particular comparative value to provide fresh insights about the evolution of the monocotyledons. The study of the banana genome has been enhanced by a number of tools and resources that allows harnessing its sequence. First, we set up essential tools such as a Community Annotation System, phylogenomics resources and metabolic pathways. Then, to support post-genomic efforts, we improved banana existing systems (e.g. web front end, query builder), we integrated available Musa data into generic systems (e.g. markers and genetic maps, synteny blocks), we have made interoperable with the banana hub, other existing systems containing Musa data (e.g. transcriptomics, rice reference genome, workflow manager) and finally, we generated new results from sequence analyses (e.g. SNP and polymorphism analysis). Several uses cases illustrate how the Banana Genome Hub can be used to study gene families. Overall, with this collaborative effort, we discuss the importance of the interoperability toward data integration between existing information systems. Database URL: http://banana-genome.cirad.fr/ PMID:23707967

Alzheimer's disease in the omics era.

PubMed

Sancesario, Giulia M; Bernardini, Sergio

2018-06-18

Recent progresses in high-throughput technologies have led to a new scenario in investigating pathologies, named the "Omics era", which integrate the opportunity to collect large amounts of data and information at the molecular and protein levels together with the development of novel computational and statistical tools that are able to analyze and filter such data. Subsequently, advances in genotyping arrays, next generation sequencing, mass spectrometry technology, and bioinformatics allowed for the simultaneous large-scale study of thousands of genes (genomics), epigenetics factors (epigenomics), RNA (transcriptomics), metabolites (metabolomics) and proteins(proteomics), with the possibility of integrating multiple types of omics data ("multi -omics"). All of these technological innovations have modified the approach to the study of complex diseases, such as Alzheimer's Disease (AD), thus representing a promising tool to investigate the relationship between several molecular pathways in AD as well as other pathologies. This review focuses on the current knowledge on the pathology of AD, the recent findings from Omics sciences, and the challenge of the use of Big Data. We then focus on future perspectives for Omics sciences, such as the discovery of novel diagnostic biomarkers or drugs. Copyright © 2018. Published by Elsevier Inc.

COMAN: a web server for comprehensive metatranscriptomics analysis.

PubMed

Ni, Yueqiong; Li, Jun; Panagiotou, Gianni

2016-08-11

Microbiota-oriented studies based on metagenomic or metatranscriptomic sequencing have revolutionised our understanding on microbial ecology and the roles of both clinical and environmental microbes. The analysis of massive metatranscriptomic data requires extensive computational resources, a collection of bioinformatics tools and expertise in programming. We developed COMAN (Comprehensive Metatranscriptomics Analysis), a web-based tool dedicated to automatically and comprehensively analysing metatranscriptomic data. COMAN pipeline includes quality control of raw reads, removal of reads derived from non-coding RNA, followed by functional annotation, comparative statistical analysis, pathway enrichment analysis, co-expression network analysis and high-quality visualisation. The essential data generated by COMAN are also provided in tabular format for additional analysis and integration with other software. The web server has an easy-to-use interface and detailed instructions, and is freely available at http://sbb.hku.hk/COMAN/ CONCLUSIONS: COMAN is an integrated web server dedicated to comprehensive functional analysis of metatranscriptomic data, translating massive amount of reads to data tables and high-standard figures. It is expected to facilitate the researchers with less expertise in bioinformatics in answering microbiota-related biological questions and to increase the accessibility and interpretation of microbiota RNA-Seq data.

In silico environmental chemical science: properties and processes from statistical and computational modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tratnyek, Paul G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs usingmore » descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.« less

Signal Transduction Pathways of TNAP: Molecular Network Analyses.

PubMed

Négyessy, László; Györffy, Balázs; Hanics, János; Bányai, Mihály; Fonta, Caroline; Bazsó, Fülöp

2015-01-01

Despite the growing body of evidence pointing on the involvement of tissue non-specific alkaline phosphatase (TNAP) in brain function and diseases like epilepsy and Alzheimer's disease, our understanding about the role of TNAP in the regulation of neurotransmission is severely limited. The aim of our study was to integrate the fragmented knowledge into a comprehensive view regarding neuronal functions of TNAP using objective tools. As a model we used the signal transduction molecular network of a pyramidal neuron after complementing with TNAP related data and performed the analysis using graph theoretic tools. The analyses show that TNAP is in the crossroad of numerous pathways and therefore is one of the key players of the neuronal signal transduction network. Through many of its connections, most notably with molecules of the purinergic system, TNAP serves as a controller by funnelling signal flow towards a subset of molecules. TNAP also appears as the source of signal to be spread via interactions with molecules involved among others in neurodegeneration. Cluster analyses identified TNAP as part of the second messenger signalling cascade. However, TNAP also forms connections with other functional groups involved in neuronal signal transduction. The results indicate the distinct ways of involvement of TNAP in multiple neuronal functions and diseases.

Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution

EPA Science Inventory

There are many technological pathways that can lead to reduced carbon dioxide emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessmen...

Integrating disease management and wound care critical pathways in home care.

PubMed

Barr, J E

1999-10-01

This article discusses the need for an integration of the concepts of disease management and critical pathways as a foundation of a healthcare delivery system. The steps in the process for development, implementation, and evaluation of a wound care critical pathway are reviewed and variance classifications are defined. Co-pathways and algorithms are presented as methodologies for dealing with variances. A template of a wound care critical pathway that has been developed for use in the home care setting is included.

Meta-dimensional data integration identifies critical pathways for susceptibility, tumorigenesis and progression of endometrial cancer.

PubMed

Wei, Runmin; De Vivo, Immaculata; Huang, Sijia; Zhu, Xun; Risch, Harvey; Moore, Jason H; Yu, Herbert; Garmire, Lana X

2016-08-23

Endometrial Cancer (EC) is one of the most common female cancers. Genome-wide association studies (GWAS) have been investigated to identify genetic polymorphisms that are predictive of EC risks. Here we utilized a meta-dimensional integrative approach to seek genetically susceptible pathways that may be associated with tumorigenesis and progression of EC. We analyzed GWAS data obtained from Connecticut Endometrial Cancer Study (CECS) and identified the top 20 EC susceptible pathways. To further verify the significance of top 20 EC susceptible pathways, we conducted pathway-level multi-omics analyses using EC exome-Seq, RNA-Seq and survival data, all based on The Cancer Genome Atlas (TCGA) samples. We measured the overall consistent rankings of these pathways in all four data types. Some well-studied pathways, such as p53 signaling and cell cycle pathways, show consistently high rankings across different analyses. Additionally, other cell signaling pathways (e.g. IGF-1/mTOR, rac-1 and IL-5 pathway), genetic information processing pathway (e.g. homologous recombination) and metabolism pathway (e.g. sphingolipid metabolism) are also highly associated with EC risks, diagnosis and prognosis. In conclusion, the meta-dimensional integration of EC cohorts has suggested some common pathways that may be associated from predisposition, tumorigenesis to progression.

Metabonomics: its potential as a tool in toxicology for safety assessment and data integration.

PubMed

Griffin, J L; Bollard, M E

2004-10-01

The functional genomic techniques of transcriptomics and proteomics promise unparalleled global information during the drug development process. However, if these technologies are used in isolation the large multivariate data sets produced are often difficult to interpret, and have the potential of missing key metabolic events (e.g. as a result of experimental noise in the system). To better understand the significance of these megavariate data the temporal changes in phenotype must be described. High resolution 1H NMR spectroscopy used in conjunction with pattern recognition provides one such tool for defining the dynamic phenotype of a cell, organ or organism in terms of a metabolic phenotype. In this review the benefits of this metabonomics/metabolomics approach to problems in toxicology will be discussed. One of the major benefits of this approach is its high throughput nature and cost effectiveness on a per sample basis. Using such a method the consortium for metabonomic toxicology (COMET) are currently investigating approximately 150 model liver and kidney toxins. This investigation will allow the generation of expert systems where liver and kidney toxicity can be predicted for model drug compounds, providing a new research tool in the field of drug metabolism. The review will also include how metabonomics may be used to investigate co-responses with transcripts and proteins involved in metabolism and stress responses, such as during drug induced fatty liver disease. By using data integration to combine metabolite analysis and gene expression profiling key perturbed metabolic pathways can be identified and used as a tool to investigate drug function.

KinView: A visual comparative sequence analysis tool for integrated kinome research

PubMed Central

McSkimming, Daniel Ian; Dastgheib, Shima; Baffi, Timothy R.; Byrne, Dominic P.; Ferries, Samantha; Scott, Steven Thomas; Newton, Alexandra C.; Eyers, Claire E.; Kochut, Krzysztof J.; Eyers, Patrick A.

2017-01-01

Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats. PMID:27731453

Improving transcriptome construction in non-model organisms: integrating manual and automated gene definition in Emiliania huxleyi.

PubMed

Feldmesser, Ester; Rosenwasser, Shilo; Vardi, Assaf; Ben-Dor, Shifra

2014-02-22

The advent of Next Generation Sequencing technologies and corresponding bioinformatics tools allows the definition of transcriptomes in non-model organisms. Non-model organisms are of great ecological and biotechnological significance, and consequently the understanding of their unique metabolic pathways is essential. Several methods that integrate de novo assembly with genome-based assembly have been proposed. Yet, there are many open challenges in defining genes, particularly where genomes are not available or incomplete. Despite the large numbers of transcriptome assemblies that have been performed, quality control of the transcript building process, particularly on the protein level, is rarely performed if ever. To test and improve the quality of the automated transcriptome reconstruction, we used manually defined and curated genes, several of them experimentally validated. Several approaches to transcript construction were utilized, based on the available data: a draft genome, high quality RNAseq reads, and ESTs. In order to maximize the contribution of the various data, we integrated methods including de novo and genome based assembly, as well as EST clustering. After each step a set of manually curated genes was used for quality assessment of the transcripts. The interplay between the automated pipeline and the quality control indicated which additional processes were required to improve the transcriptome reconstruction. We discovered that E. huxleyi has a very high percentage of non-canonical splice junctions, and relatively high rates of intron retention, which caused unique issues with the currently available tools. While individual tools missed genes and artificially joined overlapping transcripts, combining the results of several tools improved the completeness and quality considerably. The final collection, created from the integration of several quality control and improvement rounds, was compared to the manually defined set both on the DNA and protein levels, and resulted in an improvement of 20% versus any of the read-based approaches alone. To the best of our knowledge, this is the first time that an automated transcript definition is subjected to quality control using manually defined and curated genes and thereafter the process is improved. We recommend using a set of manually curated genes to troubleshoot transcriptome reconstruction.

Keys and the crisis in taxonomy: extinction or reinvention?

PubMed

Walter, David Evans; Winterton, Shaun

2007-01-01

Dichotomous keys that follow a single pathway of character state choices to an end point have been the primary tools for the identification of unknown organisms for more than two centuries. However, a revolution in computer diagnostics is now under way that may result in the replacement of traditional keys by matrix-based computer interactive keys that have many paths to a correct identification and make extensive use of hypertext to link to images, glossaries, and other support material. Progress is also being made on replacing keys entirely by optical matching of specimens to digital databases and DNA sequences. These new tools may go some way toward alleviating the taxonomic impediment to biodiversity studies and other ecological and evolutionary research, especially with better coordination between those who produce keys and those who use them and by integrating interactive keys into larger biological Web sites.

A review of genomic data warehousing systems.

PubMed

Triplet, Thomas; Butler, Gregory

2014-07-01

To facilitate the integration and querying of genomics data, a number of generic data warehousing frameworks have been developed. They differ in their design and capabilities, as well as their intended audience. We provide a comprehensive and quantitative review of those genomic data warehousing frameworks in the context of large-scale systems biology. We reviewed in detail four genomic data warehouses (BioMart, BioXRT, InterMine and PathwayTools) freely available to the academic community. We quantified 20 aspects of the warehouses, covering the accuracy of their responses, their computational requirements and development efforts. Performance of the warehouses was evaluated under various hardware configurations to help laboratories optimize hardware expenses. Each aspect of the benchmark may be dynamically weighted by scientists using our online tool BenchDW (http://warehousebenchmark.fungalgenomics.ca/benchmark/) to build custom warehouse profiles and tailor our results to their specific needs.

The Human Blood Metabolome-Transcriptome Interface

PubMed Central

Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

2015-01-01

Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

Indicators and Measurement Tools for Health Systems Integration: A Knowledge Synthesis

PubMed Central

Oelke, Nelly D.; da Silva Lima, Maria Alice Dias; Stiphout, Michelle; Janke, Robert; Witt, Regina Rigatto; Van Vliet-Brown, Cheryl; Schill, Kaela; Rostami, Mahnoush; Hepp, Shelanne; Birney, Arden; Al-Roubaiai, Fatima; Marques, Giselda Quintana

2017-01-01

Background: Despite far reaching support for integrated care, conceptualizing and measuring integrated care remains challenging. This knowledge synthesis aimed to identify indicator domains and tools to measure progress towards integrated care. Methods: We used an established framework and a Delphi survey with integration experts to identify relevant measurement domains. For each domain, we searched and reviewed the literature for relevant tools. Findings: From 7,133 abstracts, we retrieved 114 unique tools. We found many quality tools to measure care coordination, patient engagement and team effectiveness/performance. In contrast, there were few tools in the domains of performance measurement and information systems, alignment of organizational goals and resource allocation. The search yielded 12 tools that measure overall integration or three or more indicator domains. Discussion: Our findings highlight a continued gap in tools to measure foundational components that support integrated care. In the absence of such targeted tools, “overall integration” tools may be useful for a broad assessment of the overall state of a system. Conclusions: Continued progress towards integrated care depends on our ability to evaluate the success of strategies across different levels and context. This study has identified 114 tools that measure integrated care across 16 domains, supporting efforts towards a unified measurement framework. PMID:29588637

Collaboration pathway(s) using new tools for optimizing operational climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2014-10-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the needs of decision makers, scientific investigators and global users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent (2014) rulebased decision engine modeling runs that targeted optimizing the intended NPOESS architecture, becomes a surrogate for global operational climate monitoring architecture(s). This rule-based systems tools provide valuable insight for Global climate architectures, through the comparison and evaluation of alternatives considered and the exhaustive range of trade space explored. A representative optimization of Global ECV's (essential climate variables) climate monitoring architecture(s) is explored and described in some detail with thoughts on appropriate rule-based valuations. The optimization tools(s) suggest and support global collaboration pathways and hopefully elicit responses from the audience and climate science shareholders.

Self-learning computers for surgical planning and prediction of postoperative alignment.

PubMed

Lafage, Renaud; Pesenti, Sébastien; Lafage, Virginie; Schwab, Frank J

2018-02-01

In past decades, the role of sagittal alignment has been widely demonstrated in the setting of spinal conditions. As several parameters can be affected, identifying the driver of the deformity is the cornerstone of a successful treatment approach. Despite the importance of restoring sagittal alignment for optimizing outcome, this task remains challenging. Self-learning computers and optimized algorithms are of great interest in spine surgery as in that they facilitate better planning and prediction of postoperative alignment. Nowadays, computer-assisted tools are part of surgeons' daily practice; however, the use of such tools remains to be time-consuming. NARRATIVE REVIEW AND RESULTS: Computer-assisted methods for the prediction of postoperative alignment consist of a three step analysis: identification of anatomical landmark, definition of alignment objectives, and simulation of surgery. Recently, complex rules for the prediction of alignment have been proposed. Even though this kind of work leads to more personalized objectives, the number of parameters involved renders it difficult for clinical use, stressing the importance of developing computer-assisted tools. The evolution of our current technology, including machine learning and other types of advanced algorithms, will provide powerful tools that could be useful in improving surgical outcomes and alignment prediction. These tools can combine different types of advanced technologies, such as image recognition and shape modeling, and using this technique, computer-assisted methods are able to predict spinal shape. The development of powerful computer-assisted methods involves the integration of several sources of information such as radiographic parameters (X-rays, MRI, CT scan, etc.), demographic information, and unusual non-osseous parameters (muscle quality, proprioception, gait analysis data). In using a larger set of data, these methods will aim to mimic what is actually done by spine surgeons, leading to real tailor-made solutions. Integrating newer technology can change the current way of planning/simulating surgery. The use of powerful computer-assisted tools that are able to integrate several parameters and learn from experience can change the traditional way of selecting treatment pathways and counseling patients. However, there is still much work to be done to reach a desired level as noted in other orthopedic fields, such as hip surgery. Many of these tools already exist in non-medical fields and their adaptation to spine surgery is of considerable interest.

Manuscript title: antifungal proteins from moulds: analytical tools and potential application to dry-ripened foods.

PubMed

Delgado, Josué; Owens, Rebecca A; Doyle, Sean; Asensio, Miguel A; Núñez, Félix

2016-08-01

Moulds growing on the surface of dry-ripened foods contribute to their sensory qualities, but some of them are able to produce mycotoxins that pose a hazard to consumers. Small cysteine-rich antifungal proteins (AFPs) from moulds are highly stable to pH and proteolysis and exhibit a broad inhibition spectrum against filamentous fungi, providing new chances to control hazardous moulds in fermented foods. The analytical tools for characterizing the cellular targets and affected pathways are reviewed. Strategies currently employed to study these mechanisms of action include 'omics' approaches that have come to the forefront in recent years, developing in tandem with genome sequencing of relevant organisms. These techniques contribute to a better understanding of the response of moulds against AFPs, allowing the design of complementary strategies to maximize or overcome the limitations of using AFPs on foods. AFPs alter chitin biosynthesis, and some fungi react inducing cell wall integrity (CWI) pathway. However, moulds able to increase chitin content at the cell wall by increasing proteins in either CWI or calmodulin-calcineurin signalling pathways will resist AFPs. Similarly, AFPs increase the intracellular levels of reactive oxygen species (ROS), and moulds increasing G-protein complex β subunit CpcB and/or enzymes to efficiently produce glutathione may evade apoptosis. Unknown aspects that need to be addressed include the interaction with mycotoxin production by less sensitive toxigenic moulds. However, significant steps have been taken to encourage the use of AFPs in intermediate-moisture foods, particularly for mould-ripened cheese and meat products.

Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering

PubMed Central

Prescott, Thomas P.; Lang, Moritz; Papachristodoulou, Antonis

2015-01-01

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem’s incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks. PMID:25933116

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

MetaMapR: pathway independent metabolomic network analysis incorporating unknowns.

PubMed

Grapov, Dmitry; Wanichthanarak, Kwanjeera; Fiehn, Oliver

2015-08-15

Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between >200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools. Freely available at http://dgrapov.github.io/MetaMapR/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http://dgrapov.github.io/MetaMapR/. ofiehn@ucdavis.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Internal exposure dynamics drive the Adverse Outcome Pathways of synthetic glucocorticoids in fish

NASA Astrophysics Data System (ADS)

Margiotta-Casaluci, Luigi; Owen, Stewart F.; Huerta, Belinda; Rodríguez-Mozaz, Sara; Kugathas, Subramanian; Barceló, Damià; Rand-Weaver, Mariann; Sumpter, John P.

2016-02-01

The Adverse Outcome Pathway (AOP) framework represents a valuable conceptual tool to systematically integrate existing toxicological knowledge from a mechanistic perspective to facilitate predictions of chemical-induced effects across species. However, its application for decision-making requires the transition from qualitative to quantitative AOP (qAOP). Here we used a fish model and the synthetic glucocorticoid beclomethasone dipropionate (BDP) to investigate the role of chemical-specific properties, pharmacokinetics, and internal exposure dynamics in the development of qAOPs. We generated a qAOP network based on drug plasma concentrations and focused on immunodepression, skin androgenisation, disruption of gluconeogenesis and reproductive performance. We showed that internal exposure dynamics and chemical-specific properties influence the development of qAOPs and their predictive power. Comparing the effects of two different glucocorticoids, we highlight how relatively similar in vitro hazard-based indicators can lead to different in vivo risk. This discrepancy can be predicted by their different uptake potential, pharmacokinetic (PK) and pharmacodynamic (PD) profiles. We recommend that the development phase of qAOPs should include the application of species-species uptake and physiologically-based PK/PD models. This integration will significantly enhance the predictive power, enabling a more accurate assessment of the risk and the reliable transferability of qAOPs across chemicals.

Constructing Adverse Outcome Pathways: a Demonstration of ...

EPA Pesticide Factsheets

Adverse outcome pathway (AOP) provides a conceptual framework to evaluate and integrate chemical toxicity and its effects across the levels of biological organization. As such, it is essential to develop a resource-efficient and effective approach to extend molecular initiating events (MIEs) of chemicals to their downstream phenotypes of a greater regulatory relevance. A number of ongoing public phenomics (high throughput phenotyping) efforts have been generating abundant phenotypic data annotated with ontology terms. These phenotypes can be analyzed semantically and linked to MIEs of interest, all in the context of a knowledge base integrated from a variety of ontologies for various species and knowledge domains. In such analyses, two phenotypic profiles (PPs; anchored by genes or diseases) each characterized by multiple ontology terms are compared for their semantic similarities within a common ontology graph, but across boundaries of species and knowledge domains. Taking advantage of publicly available ontologies and software tool kits, we have implemented an OS-Mapping (Ontology-based Semantics Mapping) approach as a Java application, and constructed a network of 19383 PPs as nodes with edges weighed by their pairwise semantic similarity scores. Individual PPs were assembled from public phenomics data. Out of possible 1.87×108 pairwise connections among these nodes, about 71% of them have similarity scores between 0.2 and the maximum possible of 1.0.

Reconstruction of metabolic pathways for the cattle genome

PubMed Central

Seo, Seongwon; Lewin, Harris A

2009-01-01

Background Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement. Results An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly. Conclusion CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology. PMID:19284618

Final Report: Demographic Tools for Climate Change and Environmental Assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Neill, Brian

2017-01-24

This report summarizes work over the course of a three-year project (2012-2015, with one year no-cost extension to 2016). The full proposal detailed six tasks: Task 1: Population projection model Task 2: Household model Task 3: Spatial population model Task 4: Integrated model development Task 5: Population projections for Shared Socio-economic Pathways (SSPs) Task 6: Population exposure to climate extremes We report on all six tasks, provide details on papers that have appeared or been submitted as a result of this project, and list selected key presentations that have been made within the university community and at professional meetings.

Informatics Approaches for Predicting, Understanding, and Testing Cancer Drug Combinations.

PubMed

Tang, Jing

2017-01-01

Making cancer treatment more effective is one of the grand challenges in our health care system. However, many drugs have entered clinical trials but so far showed limited efficacy or induced rapid development of resistance. We urgently need multi-targeted drug combinations, which shall selectively inhibit the cancer cells and block the emergence of drug resistance. The book chapter focuses on mathematical and computational tools to facilitate the discovery of the most promising drug combinations to improve efficacy and prevent resistance. Data integration approaches that leverage drug-target interactions, cancer molecular features, and signaling pathways for predicting, understanding, and testing drug combinations are critically reviewed.

Connecting mathematics learning through spatial reasoning

NASA Astrophysics Data System (ADS)

Mulligan, Joanne; Woolcott, Geoffrey; Mitchelmore, Michael; Davis, Brent

2018-03-01

Spatial reasoning, an emerging transdisciplinary area of interest to mathematics education research, is proving integral to all human learning. It is particularly critical to science, technology, engineering and mathematics (STEM) fields. This project will create an innovative knowledge framework based on spatial reasoning that identifies new pathways for mathematics learning, pedagogy and curriculum. Novel analytical tools will map the unknown complex systems linking spatial and mathematical concepts. It will involve the design, implementation and evaluation of a Spatial Reasoning Mathematics Program (SRMP) in Grades 3 to 5. Benefits will be seen through development of critical spatial skills for students, increased teacher capability and informed policy and curriculum across STEM education.

On a learning curve for shared decision making: Interviews with clinicians using the knee osteoarthritis Option Grid.

PubMed

Elwyn, Glyn; Rasmussen, Julie; Kinsey, Katharine; Firth, Jill; Marrin, Katy; Edwards, Adrian; Wood, Fiona

2018-02-01

Tools used in clinical encounters to illustrate to patients the risks and benefits of treatment options have been shown to increase shared decision making. However, we do not have good information about how these tools are viewed by clinicians and how clinicians think patients would react to their use. Our aim was to examine clinicians' views about the possible and actual use of tools designed to support patients and clinicians to collaborate and deliberate about treatment options, namely, Option Grid decision aids. We conducted a thematic analysis of qualitative interviews embedded in the intervention phase of a trial of an Option Grid decision aid for osteoarthritis of the knee. Interviews were conducted with 6 participating clinicians before they used the tool and again after clinicians had used the tool with 6 patients. In the first interview, clinicians voiced concerns that the tool would lead to an increase in encounter duration, patient resistance regarding involvement in decision making, and potential information overload. At the second interview, after minimal training, the clinicians reported that the tool had changed their usual way of communicating, and it was generally acceptable and helpful to integrate it into practice. After experiencing the use of Option Grids, clinicians became more willing to use the tools in their clinical encounters with patients. How best to introduce Option Grids to clinicians and adopt their use into practice will need careful consideration of context, workflow, and clinical pathways. © 2016 John Wiley & Sons, Ltd.

Key aspects of the Novartis compound collection enhancement project for the compilation of a comprehensive chemogenomics drug discovery screening collection.

PubMed

Jacoby, Edgar; Schuffenhauer, Ansgar; Popov, Maxim; Azzaoui, Kamal; Havill, Benjamin; Schopfer, Ulrich; Engeloch, Caroline; Stanek, Jaroslav; Acklin, Pierre; Rigollier, Pascal; Stoll, Friederike; Koch, Guido; Meier, Peter; Orain, David; Giger, Rudolph; Hinrichs, Jürgen; Malagu, Karine; Zimmermann, Jürg; Roth, Hans-Joerg

2005-01-01

The NIBR (Novartis Institutes for BioMedical Research) compound collection enrichment and enhancement project integrates corporate internal combinatorial compound synthesis and external compound acquisition activities in order to build up a comprehensive screening collection for a modern drug discovery organization. The main purpose of the screening collection is to supply the Novartis drug discovery pipeline with hit-to-lead compounds for today's and the future's portfolio of drug discovery programs, and to provide tool compounds for the chemogenomics investigation of novel biological pathways and circuits. As such, it integrates designed focused and diversity-based compound sets from the synthetic and natural paradigms able to cope with druggable and currently deemed undruggable targets and molecular interaction modes. Herein, we will summarize together with new trends published in the literature, scientific challenges faced and key approaches taken at NIBR to match the chemical and biological spaces.

Integrating Hospital Administrative Data to Improve Health Care Efficiency and Outcomes: “The Socrates Story”

PubMed Central

Lawrence, Justin; Delaney, Conor P.

2013-01-01

Evaluation of health care outcomes has become increasingly important as we strive to improve quality and efficiency while controlling cost. Many groups feel that analysis of large datasets will be useful in optimizing resource utilization; however, the ideal blend of clinical and administrative data points has not been developed. Hospitals and health care systems have several tools to measure cost and resource utilization, but the data are often housed in disparate systems that are not integrated and do not permit multisystem analysis. Systems Outcomes and Clinical Resources AdministraTive Efficiency Software (SOCRATES) is a novel data merging, warehousing, analysis, and reporting technology, which brings together disparate hospital administrative systems generating automated or customizable risk-adjusted reports. Used in combination with standardized enhanced care pathways, SOCRATES offers a mechanism to improve the quality and efficiency of care, with the ability to measure real-time changes in outcomes. PMID:24436649

Integrating hospital administrative data to improve health care efficiency and outcomes: "the socrates story".

PubMed

Lawrence, Justin; Delaney, Conor P

2013-03-01

Evaluation of health care outcomes has become increasingly important as we strive to improve quality and efficiency while controlling cost. Many groups feel that analysis of large datasets will be useful in optimizing resource utilization; however, the ideal blend of clinical and administrative data points has not been developed. Hospitals and health care systems have several tools to measure cost and resource utilization, but the data are often housed in disparate systems that are not integrated and do not permit multisystem analysis. Systems Outcomes and Clinical Resources AdministraTive Efficiency Software (SOCRATES) is a novel data merging, warehousing, analysis, and reporting technology, which brings together disparate hospital administrative systems generating automated or customizable risk-adjusted reports. Used in combination with standardized enhanced care pathways, SOCRATES offers a mechanism to improve the quality and efficiency of care, with the ability to measure real-time changes in outcomes.

People Experiencing Chronic Homelessness

MedlinePlus

... Housing Affordable Housing Rapid Re-Housing Supportive Housing Foster Education Connections Build Career Pathways Integrate Health Care ... Housing Affordable Housing Rapid Re-Housing Supportive Housing Foster Education Connections Build Career Pathways Integrate Health Care ...

In search of the Golden Fleece: Unraveling principles of morphogenesis by studying the integrative biology of skin appendages

PubMed Central

Hughes, Michael W.; Wu, Ping; Jiang, Ting-Xin; Lin, Sung-Jan; Dong, Chen-Yuan; Li, Ang; Hsieh, Fon-Jou; Widelitz, Randall B.; Choung, Cheng Ming

2013-01-01

Summary The mythological story of the Golden Fleece symbolizes the magical regenerative power of skin appendages. Similar to the adventurous pursuit of the Golden Fleece by the multi-talented Argonauts, today we also need an integrated multi-disciplined approach to understand the cellular and molecular processes during development, regeneration and evolution of skin appendages. To this end, we have explored several aspects of skin appendage biology that contribute to the Turing activator / inhibitor model in feather pattern formation, the topo-biological arrangement of stem cells in organ shape determination, the macro-environmental regulation of stem cells in regenerative hair waves, and potential novel molecular pathways in the morphological evolution of feathers. Here we show our current integrative biology efforts to unravel the complex cellular behavior in patterning stem cells and the control of regional specificity in skin appendages. We use feather / scale tissue recombination to demonstrate the timing control of competence and inducibility. Feathers from different body regions are used to study skin regional specificity. Bioinformatic analyses of transcriptome microarrays show the potential involvement of candidate molecular pathways. We further show Hox genes exhibit some region specific expression patterns. To visualize real time events, we applied time-lapse movies, confocal microscopy and multiphoton microscopy to analyze the morphogenesis of cultured embryonic chicken skin explants. These modern imaging technologies reveal unexpectedly complex cellular flow and organization of extracellular matrix molecules in three dimensions. While these approaches are in preliminary stages, this perspective highlights the challenges we face and new integrative tools we will use. Future work will follow these leads to develop a systems biology view and understanding in the morphogenetic principles that govern the development and regeneration of ectodermal organs. PMID:21437328

Phosphoproteomic Analysis of Protein Kinase C Signaling in Saccharomyces cerevisiae Reveals Slt2 Mitogen-activated Protein Kinase (MAPK)-dependent Phosphorylation of Eisosome Core Components*

PubMed Central

Mascaraque, Victoria; Hernáez, María Luisa; Jiménez-Sánchez, María; Hansen, Rasmus; Gil, Concha; Martín, Humberto; Cid, Víctor J.; Molina, María

2013-01-01

The cell wall integrity (CWI) pathway of the model organism Saccharomyces cerevisiae has been thoroughly studied as a paradigm of the mitogen-activated protein kinase (MAPK) pathway. It consists of a classic MAPK module comprising the Bck1 MAPK kinase kinase, two redundant MAPK kinases (Mkk1 and Mkk2), and the Slt2 MAPK. This module is activated under a variety of stimuli related to cell wall homeostasis by Pkc1, the only member of the protein kinase C family in budding yeast. Quantitative phosphoproteomics based on stable isotope labeling of amino acids in cell culture is a powerful tool for globally studying protein phosphorylation. Here we report an analysis of the yeast phosphoproteome upon overexpression of a PKC1 hyperactive allele that specifically activates CWI MAPK signaling in the absence of external stimuli. We found 82 phosphopeptides originating from 43 proteins that showed enhanced phosphorylation in these conditions. The MAPK S/T-P target motif was significantly overrepresented in these phosphopeptides. Hyperphosphorylated proteins provide putative novel targets of the Pkc1–cell wall integrity pathway involved in diverse functions such as the control of gene expression, protein synthesis, cytoskeleton maintenance, DNA repair, and metabolism. Remarkably, five components of the plasma-membrane-associated protein complex known as eisosomes were found among the up-regulated proteins. We show here that Pkc1-induced phosphorylation of the eisosome core components Pil1 and Lsp1 was not exerted directly by Pkc1, but involved signaling through the Slt2 MAPK module. PMID:23221999

The SEURAT-1 approach towards animal free human safety assessment.

PubMed

Gocht, Tilman; Berggren, Elisabet; Ahr, Hans Jürgen; Cotgreave, Ian; Cronin, Mark T D; Daston, George; Hardy, Barry; Heinzle, Elmar; Hescheler, Jürgen; Knight, Derek J; Mahony, Catherine; Peschanski, Marc; Schwarz, Michael; Thomas, Russell S; Verfaillie, Catherine; White, Andrew; Whelan, Maurice

2015-01-01

SEURAT-1 is a European public-private research consortium that is working towards animal-free testing of chemical compounds and the highest level of consumer protection. A research strategy was formulated based on the guiding principle to adopt a toxicological mode-of-action framework to describe how any substance may adversely affect human health.The proof of the initiative will be in demonstrating the applicability of the concepts on which SEURAT-1 is built on three levels:(i) Theoretical prototypes for adverse outcome pathways are formulated based on knowledge already available in the scientific literature on investigating the toxicological mode-of-actions leading to adverse outcomes (addressing mainly liver toxicity);(ii)adverse outcome pathway descriptions are used as a guide for the formulation of case studies to further elucidate the theoretical model and to develop integrated testing strategies for the prediction of certain toxicological effects (i.e., those related to the adverse outcome pathway descriptions);(iii) further case studies target the application of knowledge gained within SEURAT-1 in the context of safety assessment. The ultimate goal would be to perform ab initio predictions based on a complete understanding of toxicological mechanisms. In the near-term, it is more realistic that data from innovative testing methods will support read-across arguments. Both scenarios are addressed with case studies for improved safety assessment. A conceptual framework for a rational integrated assessment strategy emerged from designing the case studies and is discussed in the context of international developments focusing on alternative approaches for evaluating chemicals using the new 21st century tools for toxicity testing.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways.

PubMed

Becnel, Lauren B; Darlington, Yolanda F; Ochsner, Scott A; Easton-Marks, Jeremy R; Watkins, Christopher M; McOwiti, Apollo; Kankanamge, Wasula H; Wise, Michael W; DeHart, Michael; Margolis, Ronald N; McKenna, Neil J

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse 'omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy "Web 2.0" technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA's Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field.

The Integration of Remote-Sensing Detection Techniques into the Operational Decision-Making of Marine Oil Spills

NASA Astrophysics Data System (ADS)

Garron, J.; Trainor, S.

2017-12-01

Remotely-sensed data collected from satellites, airplanes and unmanned aerial systems can be used in marine oil spills to identify the overall footprint, estimate fate and transport, and to identify resources at risk. Mandates for the use of best available technology exists for addressing marine oil spills under the jurisdiction of the USCG (33 CFR 155.1050), though clear pathways to familiarization of these technologies during a marine oil spill, or more importantly, between marine oil spills, does not. Similarly, remote-sensing scientists continue to experiment with highly tuned oil detection, fate and transport techniques that can benefit decision-making during a marine oil spill response, but the process of translating these prototypical tools to operational information remains undefined, leading most researchers to describe the "potential" of these new tools in an operational setting rather than their actual use, and decision-makers relying on traditional field observational methods. Arctic marine oil spills are no different in their mandates and the remote-sensing research undertaken, but are unique via the dark, cold, remote, infrastructure-free environment in which they can occur. These conditions increase the reliance of decision-makers in an Arctic oil spill on remotely-sensed data and tools for their manipulation. In the absence of another large-scale oil spill in the US, and limited literature on the subject, this study was undertaken to understand how remotely-sensed data and tools are being used in the Incident Command System of a marine oil spill now, with an emphasis on Arctic implementation. Interviews, oil spill scenario/drill observations and marine oil spill after action reports were collected and analyzed to determine the current state of remote-sensing data use for decision-making during a marine oil spill, and to define a set of recommendations for the process of integrating new remote-sensing tools and information in future oil spill responses. Using automated synthetic aperture radar analyses of oil spills in a common operational picture as a scientific case study, this presentation is a demonstration of how landscape-level scientific data can be integrated into Arctic planning and operational decision-making.

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas

NASA Astrophysics Data System (ADS)

Moore, B., III

2014-12-01

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. Berrien Moore III (University of Oklahoma) The South Central Climate Science Center (CSC) is one of eight regional centers established by the Department of the Interior (DoI) under Secretarial Order 3289 to address the impacts of climate change on America's water, land, and other natural and cultural resources. Under DoI leadership and funding, these CSCs will provide scientific information tools and techniques to study impacts of climate change synthesize and integrate climate change impact data develop tools that the DoI managers and partners can use when managing the DOI's land, water, fish and wildlife, and cultural heritage resources (emphasis added) The network of Climate Science Centers will provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. Note from Webster, a tool is a device for doing work; it makes outcomes more realizable and more cost effective, and, in a word, better. Prior to the existence of CSCs, the university and federal scientific world certainly contained a large "set" of scientists with considerable strength in the physical, biological, natural, and social sciences to address the complexities and interdisciplinary nature of the challenges in the areas of climate variability, change, impacts, and adaptation. However, this set of scientists were hardly an integrated community let alone a focused team, but rather a collection of distinguished researchers, educators, and practitioners that were working with disparate though at times linked objectives, and they were rarely aligning themselves formally to an overarching strategic pathway. In addition, data, models, research results, tools, and products were generally somewhat "disconnected" from the broad range of stakeholders. I should note also that NOAA's Regional Integrated Sciences and Assessments ( RISA) program is an earlier "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. This contribution will discuss the important cultural shift that has flowed from Secretarial Order 3289.

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

DOE PAGES

Wang, Jack P.; Matthews, Megan L.; Williams, Cranos M.; ...

2018-04-20

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux,more » metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.« less

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jack P.; Matthews, Megan L.; Williams, Cranos M.

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux,more » metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.« less

Regulation of Cell Wall Biogenesis in Saccharomyces cerevisiae: The Cell Wall Integrity Signaling Pathway

PubMed Central

Levin, David E.

2011-01-01

The yeast cell wall is a strong, but elastic, structure that is essential not only for the maintenance of cell shape and integrity, but also for progression through the cell cycle. During growth and morphogenesis, and in response to environmental challenges, the cell wall is remodeled in a highly regulated and polarized manner, a process that is principally under the control of the cell wall integrity (CWI) signaling pathway. This pathway transmits wall stress signals from the cell surface to the Rho1 GTPase, which mobilizes a physiologic response through a variety of effectors. Activation of CWI signaling regulates the production of various carbohydrate polymers of the cell wall, as well as their polarized delivery to the site of cell wall remodeling. This review article centers on CWI signaling in Saccharomyces cerevisiae through the cell cycle and in response to cell wall stress. The interface of this signaling pathway with other pathways that contribute to the maintenance of cell wall integrity is also discussed. PMID:22174182

Improving wood properties for wood utilization through multi-omics integration in lignin biosynthesis.

PubMed

Wang, Jack P; Matthews, Megan L; Williams, Cranos M; Shi, Rui; Yang, Chenmin; Tunlaya-Anukit, Sermsawat; Chen, Hsi-Chuan; Li, Quanzi; Liu, Jie; Lin, Chien-Yuan; Naik, Punith; Sun, Ying-Hsuan; Loziuk, Philip L; Yeh, Ting-Feng; Kim, Hoon; Gjersing, Erica; Shollenberger, Todd; Shuford, Christopher M; Song, Jina; Miller, Zachary; Huang, Yung-Yun; Edmunds, Charles W; Liu, Baoguang; Sun, Yi; Lin, Ying-Chung Jimmy; Li, Wei; Chen, Hao; Peszlen, Ilona; Ducoste, Joel J; Ralph, John; Chang, Hou-Min; Muddiman, David C; Davis, Mark F; Smith, Chris; Isik, Fikret; Sederoff, Ronald; Chiang, Vincent L

2018-04-20

A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux, metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.

Toward Genome-Based Metabolic Engineering in Bacteria.

PubMed

Oesterle, Sabine; Wuethrich, Irene; Panke, Sven

2017-01-01

Prokaryotes modified stably on the genome are of great importance for production of fine and commodity chemicals. Traditional methods for genome engineering have long suffered from imprecision and low efficiencies, making construction of suitable high-producer strains laborious. Here, we review the recent advances in discovery and refinement of molecular precision engineering tools for genome-based metabolic engineering in bacteria for chemical production, with focus on the λ-Red recombineering and the clustered regularly interspaced short palindromic repeats/Cas9 nuclease systems. In conjunction, they enable the integration of in vitro-synthesized DNA segments into specified locations on the chromosome and allow for enrichment of rare mutants by elimination of unmodified wild-type cells. Combination with concurrently developing improvements in important accessory technologies such as DNA synthesis, high-throughput screening methods, regulatory element design, and metabolic pathway optimization tools has resulted in novel efficient microbial producer strains and given access to new metabolic products. These new tools have made and will likely continue to make a big impact on the bioengineering strategies that transform the chemical industry. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative Analysis of Energy Metabolic Pathways in MCF-7 Breast Cancer Cells by Selected Reaction Monitoring Assay*

PubMed Central

Drabovich, Andrei P.; Pavlou, Maria P.; Dimitromanolakis, Apostolos; Diamandis, Eleftherios P.

2012-01-01

To investigate the quantitative response of energy metabolic pathways in human MCF-7 breast cancer cells to hypoxia, glucose deprivation, and estradiol stimulation, we developed a targeted proteomics assay for accurate quantification of protein expression in glycolysis/gluconeogenesis, TCA cycle, and pentose phosphate pathways. Cell growth conditions were selected to roughly mimic the exposure of cells in the cancer tissue to the intermittent hypoxia, glucose deprivation, and hormonal stimulation. Targeted proteomics assay allowed for reproducible quantification of 76 proteins in four different growth conditions after 24 and 48 h of perturbation. Differential expression of a number of control and metabolic pathway proteins in response to the change of growth conditions was found. Elevated expression of the majority of glycolytic enzymes was observed in hypoxia. Cancer cells, as opposed to near-normal MCF-10A cells, exhibited significantly increased expression of key energy metabolic pathway enzymes (FBP1, IDH2, and G6PD) that are known to redirect cellular metabolism and increase carbon flux through the pentose phosphate pathway. Our quantitative proteomic protocol is based on a mass spectrometry-compatible acid-labile detergent and is described in detail. Optimized parameters of a multiplex selected reaction monitoring (SRM) assay for 76 proteins, 134 proteotypic peptides, and 401 transitions are included and can be downloaded and used with any SRM-compatible mass spectrometer. The presented workflow is an integrated tool for hypothesis-driven studies of mammalian cells as well as functional studies of proteins, and can greatly complement experimental methods in systems biology, metabolic engineering, and metabolic transformation of cancer cells. PMID:22535206

Pediatric Brain Tumors: Genomics and Epigenomics Pave the Way.

PubMed

Fontebasso, Adam M; Jabado, Nada

2015-01-01

Primary malignant brain tumors remain a disproportionate cause of morbidity and mortality in humans. A number of studies exploring the cancer genome of brain tumors across ages using integrated genetics and epigenetics and next-generation sequencing technologies have recently emerged. This has led to considerable advances in the understanding of the basic biology and pathogenesis of brain tumors, including the most malignant and common variants in children: gliomas and medulloblastoma. Notably, studies of pediatric brain tumors have identified unexpected oncogenic pathways implicated in tumorigenesis. These range from a single pathway/molecule defect such as abnormalities of the mitogen-activated protein kinase pathway, considered to be a hallmark of pilocytic astrocytomas, to alterations in the epigenome as a critical component altered in many subgroups of high-grade brain tumors. Importantly, the type, timing, and spatial clustering of these molecular alterations provide a better understanding of the pathogenesis of the respective brain tumor they target and critical markers for therapy that will help refine pathological grading. We summarize these novel findings in pediatric brain tumors, which also are put in the context of the evolving notion of molecular pathology, now a mandated tool for proper classification and therapy assignment in the clinical setting.

Systems Pharmacology Dissection of the Anti-Inflammatory Mechanism for the Medicinal Herb Folium Eriobotryae

PubMed Central

Zhang, Jingxiao; Li, Yan; Chen, Su-Shing; Zhang, Lilei; Wang, Jinghui; Yang, Yinfeng; Zhang, Shuwei; Pan, Yanqiu; Wang, Yonghua; Yang, Ling

2015-01-01

Inflammation is a hallmark of many diseases like diabetes, cancers, atherosclerosis and arthritis. Thus, lots of concerns have been raised toward developing novel anti-inflammatory agents. Many alternative herbal medicines possess excellent anti-inflammatory properties, yet their precise mechanisms of action are yet to be elucidated. Here, a novel systems pharmacology approach based on a large number of chemical, biological and pharmacological data was developed and exemplified by a probe herb Folium Eriobotryae, a widely used clinical anti-inflammatory botanic drug. The results show that 11 ingredients of this herb with favorable pharmacokinetic properties are predicted as active compounds for anti-inflammatory treatment. In addition, via systematic network analyses, their targets are identified to be 43 inflammation-associated proteins including especially COX2, ALOX5, PPARG, TNF and RELA that are mainly involved in the mitogen-activated protein kinase (MAPK) signaling pathway, the rheumatoid arthritis pathway and NF-κB signaling pathway. All these demonstrate that the integrated systems pharmacology method provides not only an effective tool to illustrate the anti-inflammatory mechanisms of herbs, but also a new systems-based approach for drug discovery from, but not limited to, herbs, especially when combined with further experimental validations. PMID:25636035

Engineering Escherichia coli to overproduce aromatic amino acids and derived compounds.

PubMed

Rodriguez, Alberto; Martínez, Juan A; Flores, Noemí; Escalante, Adelfo; Gosset, Guillermo; Bolivar, Francisco

2014-09-09

The production of aromatic amino acids using fermentation processes with recombinant microorganisms can be an advantageous approach to reach their global demands. In addition, a large array of compounds with alimentary and pharmaceutical applications can potentially be synthesized from intermediates of this metabolic pathway. However, contrary to other amino acids and primary metabolites, the artificial channelling of building blocks from central metabolism towards the aromatic amino acid pathway is complicated to achieve in an efficient manner. The length and complex regulation of this pathway have progressively called for the employment of more integral approaches, promoting the merge of complementary tools and techniques in order to surpass metabolic and regulatory bottlenecks. As a result, relevant insights on the subject have been obtained during the last years, especially with genetically modified strains of Escherichia coli. By combining metabolic engineering strategies with developments in synthetic biology, systems biology and bioprocess engineering, notable advances were achieved regarding the generation, characterization and optimization of E. coli strains for the overproduction of aromatic amino acids, some of their precursors and related compounds. In this paper we review and compare recent successful reports dealing with the modification of metabolic traits to attain these objectives.

Optical control of neuronal activity using a light-operated GIRK channel opener (LOGO).

PubMed

Barber, David M; Schönberger, Matthias; Burgstaller, Jessica; Levitz, Joshua; Weaver, C David; Isacoff, Ehud Y; Baier, Herwig; Trauner, Dirk

2016-01-01

G-protein coupled inwardly rectifying potassium channels (GIRKs) are ubiquitously expressed throughout the human body and are an integral part of inhibitory signal transduction pathways. Upon binding of G βγ subunits released from G-protein coupled receptors (GPCRs), GIRK channels open and reduce the activity of excitable cells via hyperpolarization. As such, they play a role in cardiac output, the coordination of movement and cognition. Due to their involvement in a multitude of pathways, the precision control of GIRK channels is an important endeavour. Here, we describe the development of the photoswitchable agonist LOGO (the L ight O perated G IRK-channel O pener), which activates GIRK channels in the dark and is rapidly deactivated upon exposure to long wavelength UV irradiation. LOGO is the first K + channel opener and selectively targets channels that contain the GIRK1 subunit. It can be used to optically silence action potential firing in dissociated hippocampal neurons and LOGO exhibits activity in vivo , controlling the motility of zebrafish larvae in a light dependent fashion. We envisage that LOGO will be a valuable research tool to dissect the function of GIRK channels from other GPCR dependent signalling pathways.

Convergent and divergent pathways decoding hierarchical additive mechanisms in treating cerebral ischemia-reperfusion injury.

PubMed

Zhang, Ying-Ying; Li, Hai-Xia; Chen, Yin-Ying; Fang, Hong; Yu, Ya-Nan; Liu, Jun; Jing, Zhi-Wei; Wang, Zhong; Wang, Yong-Yan

2014-03-01

Cerebral ischemia is considered to be a highly complex disease resulting from the complicated interplay of multiple pathways. Disappointedly, most of the previous studies were limited to a single gene or a single pathway. The extent to which all involved pathways are translated into fusing mechanisms of a combination therapy is of fundamental importance. We report an integrative strategy to reveal the additive mechanism that a combination (BJ) of compound baicalin (BA) and jasminoidin (JA) fights against cerebral ischemia based on variation of pathways and functional communities. We identified six pathways of BJ group that shared diverse additive index from 0.09 to 1, which assembled broad cross talks from seven pathways of BA and 16 pathways of JA both at horizontal and vertical levels. Besides a total of 60 overlapping functions as a robust integration background among the three groups based on significantly differential subnetworks, additive mechanism with strong confidence by networks altered functions. These results provide strong evidence that the additive mechanism is more complex than previously appreciated, and an integrative analysis of pathways may suggest an important paradigm for revealing pharmacological mechanisms underlying drug combinations. © 2013 John Wiley & Sons Ltd.

Integrated Measurements and Characterization | Photovoltaic Research | NREL

Science.gov Websites

Integrated Measurements and Characterization cluster tool offers powerful capabilities with integrated tools more details on these capabilities. Basic Cluster Tool Capabilities Sample Handling Ultra-high-vacuum connections, it can be interchanged between tools, such as the Copper Indium Gallium Diselenide cluster tool

Integrating human health and ecological data into cumulative risk assessment through the Aggregate Exposure Pathway and Adverse Outcome Pathway frameworks

EPA Science Inventory

Cumulative risk assessment (CRA) methods promote the use of a conceptual site model (CSM) to apportion exposures and integrate risk from relevant stressors across different species. Integration is important to provide a more complete assessment of risk, but evaluating endpoints a...

KRE5 Suppression Induces Cell Wall Stress and Alternative ER Stress Response Required for Maintaining Cell Wall Integrity in Candida glabrata

PubMed Central

Sasaki, Masato; Ito, Fumie; Aoyama, Toshio; Sato-Okamoto, Michiyo; Takahashi-Nakaguchi, Azusa; Chibana, Hiroji; Shibata, Nobuyuki

2016-01-01

The maintenance of cell wall integrity in fungi is required for normal cell growth, division, hyphae formation, and antifungal tolerance. We observed that endoplasmic reticulum stress regulated cell wall integrity in Candida glabrata, which possesses uniquely evolved mechanisms for unfolded protein response mechanisms. Tetracycline-mediated suppression of KRE5, which encodes a predicted UDP-glucose:glycoprotein glucosyltransferase localized in the endoplasmic reticulum, significantly increased cell wall chitin content and decreased cell wall β-1,6-glucan content. KRE5 repression induced endoplasmic reticulum stress-related gene expression and MAP kinase pathway activation, including Slt2p and Hog1p phosphorylation, through the cell wall integrity signaling pathway. Moreover, the calcineurin pathway negatively regulated cell wall integrity, but not the reduction of β-1,6-glucan content. These results indicate that KRE5 is required for maintaining both endoplasmic reticulum homeostasis and cell wall integrity, and that the calcineurin pathway acts as a regulator of chitin-glucan balance in the cell wall and as an alternative mediator of endoplasmic reticulum stress in C. glabrata. PMID:27548283

Hippo pathway and protection of genome stability in response to DNA damage.

PubMed

Pefani, Dafni E; O'Neill, Eric

2016-04-01

The integrity of DNA is constantly challenged by exposure to the damaging effects of chemical and physical agents. Elucidating the cellular mechanisms that maintain genomic integrity via DNA repair and cell growth control is vital because errors in these processes lead to genomic damage and the development of cancer. By gaining a deep molecular understanding of the signaling pathways regulating genome integrity it is hoped to uncover new therapeutics and treatment designs to combat cancer. Components of the Hippo pathway, a tumor-suppressor cascade, have recently been defined to limit cancer transformation in response to DNA damage. In this review, we briefly introduce the Hippo signaling cascade in mammals and discuss in detail how the Hippo pathway has been established as part of the DNA damage response, activated by apical signaling kinases that recognize breaks in DNA. We also highlight the significance of the Hippo pathway activator RASSF1A tumor suppressor, a direct target of ataxia telangiectasia mutated and ataxia telangiectasia and Rad3 related ATR. Furthermore we discuss how Hippo pathway in response DNA lesions can induce cell death via Yes-associated protein (YAP) (the canonical Hippo pathway effector) or promote maintenance of genome integrity in a YAP-independent manner. © 2015 FEBS.

Systematic review of integrated models of health care delivered at the primary-secondary interface: how effective is it and what determines effectiveness?

PubMed

Mitchell, Geoffrey K; Burridge, Letitia; Zhang, Jianzhen; Donald, Maria; Scott, Ian A; Dart, Jared; Jackson, Claire L

2015-01-01

Integrated multidisciplinary care is difficult to achieve between specialist clinical services and primary care practitioners, but should improve outcomes for patients with chronic and/or complex chronic physical diseases. This systematic review identifies outcomes of different models that integrate specialist and primary care practitioners, and characteristics of models that delivered favourable clinical outcomes. For quality appraisal, the Cochrane Risk of Bias tool was used. Data are presented as a narrative synthesis due to marked heterogeneity in study outcomes. Ten studies were included. Publication bias cannot be ruled out. Despite few improvements in clinical outcomes, significant improvements were reported in process outcomes regarding disease control and service delivery. No study reported negative effects compared with usual care. Economic outcomes showed modest increases in costs of integrated primary-secondary care. Six elements were identified that were common to these models of integrated primary-secondary care: (1) interdisciplinary teamwork; (2) communication/information exchange; (3) shared care guidelines or pathways; (4) training and education; (5) access and acceptability for patients; and (6) a viable funding model. Compared with usual care, integrated primary-secondary care can improve elements of disease control and service delivery at a modestly increased cost, although the impact on clinical outcomes is limited. Future trials of integrated care should incorporate design elements likely to maximise effectiveness.

[Web-based electronic patient record as an instrument for quality assurance within an integrated care concept].

PubMed

Händel, A; Jünemann, A G M; Prokosch, H-U; Beyer, A; Ganslandt, T; Grolik, R; Klein, A; Mrosek, A; Michelson, G; Kruse, F E

2009-03-01

A prerequisite for integrated care programmes is the implementation of a communication network meeting quality assurance standards. Against this background the main objective of the integrated care project between the University Eye Hospital Erlangen and the health insurance company AOK Bayern was to evaluate the potential and the acceptance of a web-based electronic patient record in the context of cataract and retinal surgery. Standardised modules for capturing pre-, intra- and post-operative data on the basis of clinical pathway guidelines for cataract- and retinal surgery have been developed. There are 6 data sets recorded per patient (1 pre-operative, 1 operative, 4-6 post-operative). For data collection, a web-based communication system (Soarian Integrated Care) has been chosen which meets the high requirements in data security, as well as being easy to handle. This teleconsultation system and the embedded electronic patient record are independent of the software used by respective offices and hospitals. Data transmission and storage were carried out in real-time. At present, 101 private ophthalmologists are taking part in the IGV contract with the University Eye Hospital Erlangen. This corresponds to 52% of all private ophthalmologists in the region. During the period from January 1st 2006 to December 31st 2006, 1844 patients were entered. Complete documentation was achieved in 1390 (75%) of all surgical procedures. For evaluation of this data, a multidimensional report and analysis tool (Cognos) was used. The deviation from target refraction as one quality indicator was in the mean 0.09 diopter. The web-based patient record used in this project was highly accepted by the private ophthalmologists. However there are still general concerns against the exchange of medical data via the internet. Nevertheless, the web-based patient record is an essential tool for a functional integration between the ambulatory and stationary health-care units. In addition to the telemedicine functions of the system, we achieved the export of the data to a data warehouse system in order to provide a flexible and powerful tool for quality assurance analysis and reporting.

Development of an Integrative Program of Nanosafety: Promote the Coordination Between Industries and Risk Assessor

NASA Astrophysics Data System (ADS)

Emond, Claude; Kouassi, Serge; Schuster, Frédéric

2013-04-01

Nanomaterials are widely present in many industrial sectors (e.g., chemical, biomedical, environment), and their application is expected to significantly expand in the coming years. However, nanomaterial use raises many questions about the potential risks to human health and the environment and, more specifically, to occupational health. The available literature supports the ability of the lung, gastrointestinal tract, and skin to act as significant barriers against systemic exposure to many nanomaterials. However, because a potential risk issue exists about the toxicity of nanomaterials to the biological material, tools need to be developed for improving the risk management of the regulators. The goal is to develop a tool that examines the current knowledge base regarding the health risks posed by engineered nanoparticles to improve nanotechnology safety prior to the marketing phase. The approach proposed during this work was to establish a safety assessment constructed on a decision-control pathway regarding nanomaterial production and consumer's product to integrate different aspects. These aspects include: (1) primarily research and identification of the nanomaterial base of physicochemical properties, toxicity, and application; (2) the occupational exposure risk during the manufacturing process; (3) and the engineered nanomaterial upon the consumer product. This approach provides important parameters to reduce the uncertainty related to the production of nanomaterials prior their commercialization, reduce the reluctance from the industry, and provide a certification tool of sanitary control for the regulators. This work provides a better understanding of a critical issue of nanomaterials and consumer safety.

Pathway cross-talk network analysis identifies critical pathways in neonatal sepsis.

PubMed

Meng, Yu-Xiu; Liu, Quan-Hong; Chen, Deng-Hong; Meng, Ying

2017-06-01

Despite advances in neonatal care, sepsis remains a major cause of morbidity and mortality in neonates worldwide. Pathway cross-talk analysis might contribute to the inference of the driving forces in bacterial sepsis and facilitate a better understanding of underlying pathogenesis of neonatal sepsis. This study aimed to explore the critical pathways associated with the progression of neonatal sepsis by the pathway cross-talk analysis. By integrating neonatal transcriptome data with known pathway data and protein-protein interaction data, we systematically uncovered the disease pathway cross-talks and constructed a disease pathway cross-talk network for neonatal sepsis. Then, attract method was employed to explore the dysregulated pathways associated with neonatal sepsis. To determine the critical pathways in neonatal sepsis, rank product (RP) algorithm, centrality analysis and impact factor (IF) were introduced sequentially, which synthetically considered the differential expression of genes and pathways, pathways cross-talks and pathway parameters in the network. The dysregulated pathways with the highest IF values as well as RP<0.01 were defined as critical pathways in neonatal sepsis. By integrating three kinds of data, only 6919 common genes were included to perform the pathway cross-talk analysis. By statistic analysis, a total of 1249 significant pathway cross-talks were selected to construct the pathway cross-talk network. Moreover, 47 dys-regulated pathways were identified via attract method, 20 pathways were identified under RP<0.01, and the top 10 pathways with the highest IF were also screened from the pathway cross-talk network. Among them, we selected 8 common pathways, i.e. critical pathways. In this study, we systematically tracked 8 critical pathways involved in neonatal sepsis by integrating attract method and pathway cross-talk network. These pathways might be responsible for the host response in infection, and of great value for advancing diagnosis and therapy of neonatal sepsis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Towards good dementia care: Awareness and uptake of an online Dementia Pathways tool for rural and regional primary health practitioners.

PubMed

Ollerenshaw, Alison; Wong Shee, Anna; Yates, Mark

2018-04-01

To explore the awareness and usage of an online dementia pathways tool (including decision tree and region-specific dementia services) for primary health practitioners (GPs and nurses) in regional Victoria. Quantitative pilot study using surveys and Google Analytics. A large regional area (48 000 square kilometres, population 220 000) in Victoria. Two hundred and sixty-three GPs and 160 practice nurses were invited to participate, with 42 respondents (GPs, n = 21; practice nurses, n = 21). Primary care practitioners' awareness and usage of the dementia pathways tool. Survey respondents that had used the tool (n = 14) reported accessing information about diagnosis, management and referral. Practitioners reported improvements in knowledge, skills and confidence about core dementia topics. There were 9683 page views between August 2013 and February 2015 (monthly average: 509 page views). The average time spent on page was 2.03 min, with many visitors (68%) spending more than 4 min at the site. This research demonstrates that the tool has been well received by practitioners and has been consistently used since its launch. Health practitioners' valued the content and the availability of local resources. Primary health practitioners reported that the dementia pathways tool provided access to region-specific referral and management resources for all stages of dementia. Such tools have broad transferability in other health areas with further research needed to determine their contribution to learning in the practice setting and over time. © 2017 National Rural Health Alliance Inc.

Optimal visual-haptic integration with articulated tools.

PubMed

Takahashi, Chie; Watt, Simon J

2017-05-01

When we feel and see an object, the nervous system integrates visual and haptic information optimally, exploiting the redundancy in multiple signals to estimate properties more precisely than is possible from either signal alone. We examined whether optimal integration is similarly achieved when using articulated tools. Such tools (tongs, pliers, etc) are a defining characteristic of human hand function, but complicate the classical sensory 'correspondence problem' underlying multisensory integration. Optimal integration requires establishing the relationship between signals acquired by different sensors (hand and eye) and, therefore, in fundamentally unrelated units. The system must also determine when signals refer to the same property of the world-seeing and feeling the same thing-and only integrate those that do. This could be achieved by comparing the pattern of current visual and haptic input to known statistics of their normal relationship. Articulated tools disrupt this relationship, however, by altering the geometrical relationship between object properties and hand posture (the haptic signal). We examined whether different tool configurations are taken into account in visual-haptic integration. We indexed integration by measuring the precision of size estimates, and compared our results to optimal predictions from a maximum-likelihood integrator. Integration was near optimal, independent of tool configuration/hand posture, provided that visual and haptic signals referred to the same object in the world. Thus, sensory correspondence was determined correctly (trial-by-trial), taking tool configuration into account. This reveals highly flexible multisensory integration underlying tool use, consistent with the brain constructing internal models of tools' properties.

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

Structure-Based Design of Potent and Selective 3-Phosphoinositide-Dependent Kinase-1 (PDK1) Inhibitors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Medina, Jesus R.; Becker, Christopher J.; Blackledge, Charles W.

2014-10-02

Phosphoinositide-dependent protein kinase-1(PDK1) is a master regulator of the AGC family of kinases and an integral component of the PI3K/AKT/mTOR pathway. As this pathway is among the most commonly deregulated across all cancers, a selective inhibitor of PDK1 might have utility as an anticancer agent. Herein we describe our lead optimization of compound 1 toward highly potent and selective PDK1 inhibitors via a structure-based design strategy. The most potent and selective inhibitors demonstrated submicromolar activity as measured by inhibition of phosphorylation of PDK1 substrates as well as antiproliferative activity against a subset of AML cell lines. In addition, reduction ofmore » phosphorylation of PDK1 substrates was demonstrated in vivo in mice bearing OCl-AML2 xenografts. These observations demonstrate the utility of these molecules as tools to further delineate the biology of PDK1 and the potential pharmacological uses of a PDK1 inhibitor.« less

A case study to illustrate the utility of the Aggregate Exposure Pathway and Adverse Outcome Pathway frameworks for integrating human health and ecological data into cumulative risk assessment

EPA Science Inventory

Cumulative risk assessment (CRA) methods, which evaluate the risk of multiple adverse outcomes (AOs) from multiple chemicals, promote the use of a conceptual site model (CSM) to integrate risk from relevant stressors. The Adverse Outcome Pathway (AOP) framework can inform these r...

A description of a non-invasive surgical training pathway using translational tools to teach intracoelomic implantation of acoustic transmitters in fish.

PubMed

Brosnan, Ian G; Williams, Wendy O; Sanders, George E; McGarry, Louise P; Greene, Charles H

2018-05-29

Researchers engaged in surgical implantation of acoustic transmitters into fish must receive adequate and appropriate training to ensure the welfare of their subjects and the quality of the data collected. Increasingly, they are being encouraged to partner with veterinarians to improve training, and to consider the principles of animal welfare in training. Here, we describe a 5-stage training pathway, including implementation of new training tools, the Translational Training Tools ™ and field certification, that was developed collaboratively by researchers and veterinarians and address the 3 R's of animal welfare in the context of surgical training. The 3 R's include animal replacement, reduction of the number of animals used, and refinement of technique to decrease or eliminate pain or distress. The Translational Training Tools ™ , described in the context of the training pathway, use tools as replacement models during training to reduce the number of animals used, and allows for refinement of surgical skills prior to working on live animals. The purpose of this paper is to document the Translational Training Tools ™ and the training pathway, which will be useful in developing de novo protocols for review by Institutional Animal Care and Use Committees (IACUCs) and similar bodies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The shortest path is not the one you know: application of biological network resources in precision oncology research.

PubMed

Kuperstein, Inna; Grieco, Luca; Cohen, David P A; Thieffry, Denis; Zinovyev, Andrei; Barillot, Emmanuel

2015-03-01

Several decades of molecular biology research have delivered a wealth of detailed descriptions of molecular interactions in normal and tumour cells. This knowledge has been functionally organised and assembled into dedicated biological pathway resources that serve as an invaluable tool, not only for structuring the information about molecular interactions but also for making it available for biological, clinical and computational studies. With the advent of high-throughput molecular profiling of tumours, close to complete molecular catalogues of mutations, gene expression and epigenetic modifications are available and require adequate interpretation. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular profiles of tumours. Making sense out of these descriptions requires biological pathway resources for functional interpretation of the data. In this review, we describe the available biological pathway resources, their characteristics in terms of construction mode, focus, aims and paradigms of biological knowledge representation. We present a new resource that is focused on cancer-related signalling, the Atlas of Cancer Signalling Networks. We briefly discuss current approaches for data integration, visualisation and analysis, using biological networks, such as pathway scoring, guilt-by-association and network propagation. Finally, we illustrate with several examples the added value of data interpretation in the context of biological networks and demonstrate that it may help in analysis of high-throughput data like mutation, gene expression or small interfering RNA screening and can guide in patients stratification. Finally, we discuss perspectives for improving precision medicine using biological network resources and tools. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular patterns of tumours and enable to put precision oncology into general clinical practice. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Solar Project Development Pathway & Resources

EPA Pesticide Factsheets

The Local Government Solar Project Portal's Solar Project Development Pathway and Resources page details the major steps along the project development pathway and each step includes resources and tools to assist you with that step.

Validation of RetroPath, a computer-aided design tool for metabolic pathway engineering.

PubMed

Fehér, Tamás; Planson, Anne-Gaëlle; Carbonell, Pablo; Fernández-Castané, Alfred; Grigoras, Ioana; Dariy, Ekaterina; Perret, Alain; Faulon, Jean-Loup

2014-11-01

Metabolic engineering has succeeded in biosynthesis of numerous commodity or high value compounds. However, the choice of pathways and enzymes used for production was many times made ad hoc, or required expert knowledge of the specific biochemical reactions. In order to rationalize the process of engineering producer strains, we developed the computer-aided design (CAD) tool RetroPath that explores and enumerates metabolic pathways connecting the endogenous metabolites of a chassis cell to the target compound. To experimentally validate our tool, we constructed 12 top-ranked enzyme combinations producing the flavonoid pinocembrin, four of which displayed significant yields. Namely, our tool queried the enzymes found in metabolic databases based on their annotated and predicted activities. Next, it ranked pathways based on the predicted efficiency of the available enzymes, the toxicity of the intermediate metabolites and the calculated maximum product flux. To implement the top-ranking pathway, our procedure narrowed down a list of nine million possible enzyme combinations to 12, a number easily assembled and tested. One round of metabolic network optimization based on RetroPath output further increased pinocembrin titers 17-fold. In total, 12 out of the 13 enzymes tested in this work displayed a relative performance that was in accordance with its predicted score. These results validate the ranking function of our CAD tool, and open the way to its utilization in the biosynthesis of novel compounds. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases: FragariaCyc, a Case Study.

PubMed

Naithani, Sushma; Jaiswal, Pankaj

2017-01-01

The species-specific plant Pathway Genome Databases (PGDBs) based on the BioCyc platform provide a conceptual model of the cellular metabolic network of an organism. Such frameworks allow analysis of the genome-scale expression data to understand changes in the overall metabolisms of an organism (or organs, tissues, and cells) in response to various extrinsic (e.g. developmental and differentiation) and/or extrinsic signals (e.g. pathogens and abiotic stresses) from the surrounding environment. Using FragariaCyc, a pathway database for the diploid strawberry Fragaria vesca, we show (1) the basic navigation across a PGDB; (2) a case study of pathway comparison across plant species; and (3) an example of RNA-Seq data analysis using Omics Viewer tool. The protocols described here generally apply to other Pathway Tools-based PGDBs.

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

PubMed

Leong, T Y; Kaiser, K; Miksch, S

2007-01-01

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, Douglas G.; Clements, Samuel L.; Patrick, Scott W.

Securing high value and critical assets is one of the biggest challenges facing this nation and others around the world. In modern integrated systems, there are four potential modes of attack available to an adversary: • physical only attack, • cyber only attack, • physical-enabled cyber attack, • cyber-enabled physical attack. Blended attacks involve an adversary working in one domain to reduce system effectiveness in another domain. This enables the attacker to penetrate further into the overall layered defenses. Existing vulnerability assessment (VA) processes and software tools which predict facility vulnerabilities typically evaluate the physical and cyber domains separately. Vulnerabilitiesmore » which result from the integration of cyber-physical control systems are not well characterized and are often overlooked by existing assessment approaches. In this paper, we modified modification of the timely detection methodology, used for decades in physical security VAs, to include cyber components. The Physical and Cyber Risk Analysis Tool (PACRAT) prototype illustrates an integrated vulnerability assessment that includes cyber-physical interdependencies. Information about facility layout, network topology, and emplaced safeguards is used to evaluate how well suited a facility is to detect, delay, and respond to attacks, to identify the pathways most vulnerable to attack, and to evaluate how often safeguards are compromised for a given threat or adversary type. We have tested the PACRAT prototype on critical infrastructure facilities and the results are promising. Future work includes extending the model to prescribe the recommended security improvements via an automated cost-benefit analysis.« less

XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits.

PubMed

Fang, Hai; Knezevic, Bogdan; Burnham, Katie L; Knight, Julian C

2016-12-13

Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem. We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable. We show how by incorporating ontology, annotation, and systems biology network-driven approaches, XGR generates more informative results than conventional analyses. We apply XGR to GWAS and eQTL summary data to explore the genomic landscape of the activated innate immune response and common immunological diseases. We provide genomic evidence for a disease taxonomy supporting the concept of a disease spectrum from autoimmune to autoinflammatory disorders. We also show how XGR can define SNP-modulated gene networks and pathways that are shared and distinct between diseases, how it achieves functional, phenotypic and epigenomic annotations of genes and variants, and how it enables exploring annotation-based relationships between genetic variants. XGR provides a single integrated solution to enhance interpretation of genomic summary data for downstream biological discovery. XGR is released as both an R package and a web-app, freely available at http://galahad.well.ox.ac.uk/XGR .

Optogenetic Induction of Aversive Taste Memory

PubMed Central

C. Keene, Alex; Masek, Pavel

2013-01-01

The Drosophila melanogaster gustatory system consists of several neuronal pathways representing diverse taste modalities. The two predominant modalities are a sweet sensing pathway that mediates attraction, and a bitter sensing pathway that mediates avoidance. A central question is how flies integrate stimuli from these pathways and generate the appropriate behavioral response. We have developed a novel assay for induction of taste memories. We demonstrate that the gustatory response to fructose is suppressed when followed by the presence of bitter quinine. We employ optogenetic neural activation using infrared laser in combination with heat sensitive channel - TRPA1 to precisely activate gustatory neurons. This optogenetic system allows for spatially and temporally controlled activation of distinct neural classes in the gustatory circuit. We directly activated bitter-sensing neurons together with presentation of fructose for remote induction of aversive taste memories. Here we report that activation of bitter-sensing neurons in the proboscis suffices as a conditioning stimulus. Spatially restricted stimulation indicates that the conditioning stimulus is indeed a signal from the bitter neurons in the proboscis and it is independent of postingestive feedback. The coincidence of temporally specific activation of bitter-sensing neurons with fructose presentation is crucial for memory formation, establishing aversive taste learning in Drosophila as associative learning. Taken together, this optogenetic system provides a powerful new tool for interrogation of the central brain circuits that mediate memory formation. PMID:22820051

Rationale of the FIBROTARGETS study designed to identify novel biomarkers of myocardial fibrosis

PubMed Central

Ferreira, João Pedro; Machu, Jean‐Loup; Girerd, Nicolas; Jaisser, Frederic; Thum, Thomas; Butler, Javed; González, Arantxa; Diez, Javier; Heymans, Stephane; McDonald, Kenneth; Gyöngyösi, Mariann; Firat, Hueseyin; Rossignol, Patrick; Pizard, Anne

2017-01-01

Abstract Aims Myocardial fibrosis alters the cardiac architecture favouring the development of cardiac dysfunction, including arrhythmias and heart failure. Reducing myocardial fibrosis may improve outcomes through the targeted diagnosis and treatment of emerging fibrotic pathways. The European‐Commission‐funded ‘FIBROTARGETS’ is a multinational academic and industrial consortium with the main aims of (i) characterizing novel key mechanistic pathways involved in the metabolism of fibrillary collagen that may serve as biotargets, (ii) evaluating the potential anti‐fibrotic properties of novel or repurposed molecules interfering with the newly identified biotargets, and (iii) characterizing bioprofiles based on distinct mechanistic phenotypes involving the aforementioned biotargets. These pathways will be explored by performing a systematic and collaborative search for mechanisms and targets of myocardial fibrosis. These mechanisms will then be translated into individualized diagnostic tools and specific therapeutic pharmacological options for heart failure. Methods and results The FIBROTARGETS consortium has merged data from 12 patient cohorts in a common database available to individual consortium partners. The database consists of >12 000 patients with a large spectrum of cardiovascular clinical phenotypes. It integrates community‐based population cohorts, cardiovascular risk cohorts, and heart failure cohorts. Conclusions The FIBROTARGETS biomarker programme is aimed at exploring fibrotic pathways allowing the bioprofiling of patients into specific ‘fibrotic’ phenotypes and identifying new therapeutic targets that will potentially enable the development of novel and tailored anti‐fibrotic therapies for heart failure. PMID:28988439

Proof of Concept: A review on how network and systems biology approaches aid in the discovery of potent anticancer drug combinations

PubMed Central

Azmi, Asfar S.; Wang, Zhiwei; Philip, Philip A.; Mohammad, Ramzi M.; Sarkar, Fazlul H.

2010-01-01

Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignances. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. This requires innovative approaches such as understanding the global physiological environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multifaceted diseases where efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology has emerged as a powerful tool benefiting our understanding of drug mechanism of action in real time. This mini-review highlights the significance of the network and systems biology-based strategy and presents a “proof-of-concept” recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma. PMID:21041384

Position-specific isotope modeling of organic micropollutants transformations through different reaction pathways

NASA Astrophysics Data System (ADS)

Jin, Biao; Rolle, Massimo

2016-04-01

Organic compounds are produced in vast quantities for industrial and agricultural use, as well as for human and animal healthcare [1]. These chemicals and their metabolites are frequently detected at trace levels in fresh water environments where they undergo degradation via different reaction pathways. Compound specific stable isotope analysis (CSIA) is a valuable tool to identify such degradation pathways in different environmental systems. Recent advances in analytical techniques have promoted the fast development and implementation of multi-element CSIA. However, quantitative frameworks to evaluate multi-element stable isotope data and incorporating mechanistic information on the degradation processes [2,3] are still lacking. In this study we propose a mechanism-based modeling approach to simultaneously evaluate concentration as well as bulk and position-specific multi-element isotope evolution during the transformation of organic micropollutants. The model explicitly simulates position-specific isotopologues for those atoms that experience isotope effects and, thereby, provides a mechanistic description of isotope fractionation occurring at different molecular positions. We validate the proposed approach with the concentration and multi-element isotope data of three selected organic micropollutants: dichlorobenzamide (BAM), isoproturon (IPU) and diclofenac (DCF). The model precisely captures the dual element isotope trends characteristic of different reaction pathways and their range of variation consistent with observed multi-element (C, N) bulk isotope fractionation. The proposed approach can also be used as a tool to explore transformation pathways in scenarios for which position-specific isotope data are not yet available. [1] Schwarzenbach, R.P., Egli, T., Hofstetter, T.B., von Gunten, U., Wehrli, B., 2010. Global Water Pollution and Human Health. Annu. Rev. Environ. Resour. doi:10.1146/annurev-environ-100809-125342. [2] Jin, B., Haderlein, S.B., Rolle, M., 2013. Integrated carbon and chlorine isotope modeling: Applications to chlorinated aliphatic hydrocarbons dechlorination. Environ. Sci. Technol. 47, 1443-1451. doi:10.1021/es304053h. [3] Jin, B., Rolle, M., 2014. Mechanistic approach to multi-element isotope modeling of organic contaminant degradation. Chemosphere 95, 131-139. doi:10.1016/j.chemosphere.2013.08.050.

A research protocol for developing a Point-Of-Care Key Evidence Tool 'POCKET': a checklist for multidimensional evidence reporting on point-of-care in vitro diagnostics.

PubMed

Huddy, Jeremy R; Ni, Melody; Mavroveli, Stella; Barlow, James; Williams, Doris-Ann; Hanna, George B

2015-07-10

Point-of-care in vitro diagnostics (POC-IVD) are increasingly becoming widespread as an acceptable means of providing rapid diagnostic results to facilitate decision-making in many clinical pathways. Evidence in utility, usability and cost-effectiveness is currently provided in a fragmented and detached manner that is fraught with methodological challenges given the disruptive nature these tests have on the clinical pathway. The Point-of-care Key Evidence Tool (POCKET) checklist aims to provide an integrated evidence-based framework that incorporates all required evidence to guide the evaluation of POC-IVD to meet the needs of policy and decisionmakers in the National Health Service (NHS). A multimethod approach will be applied in order to develop the POCKET. A thorough literature review has formed the basis of a robust Delphi process and validation study. Semistructured interviews are being undertaken with POC-IVD stakeholders, including industry, regulators, commissioners, clinicians and patients to understand what evidence is required to facilitate decision-making. Emergent themes will be translated into a series of statements to form a survey questionnaire that aims to reach a consensus in each stakeholder group to what needs to be included in the tool. Results will be presented to a workshop to discuss the statements brought forward and the optimal format for the tool. Once assembled, the tool will be field-tested through case studies to ensure validity and usability and inform refinement, if required. The final version will be published online with a call for comments. Limitations include unpredictable sample representation, development of compromise position rather than consensus, and absence of blinding in validation exercise. The Imperial College Joint Research Compliance Office and the Imperial College Hospitals NHS Trust R&D department have approved the protocol. The checklist tool will be disseminated through a PhD thesis, a website, peer-reviewed publication, academic conferences and formal presentations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

A framework for modelling the complexities of food and water security under globalisation

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

2018-01-01

We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

VitisCyc: a metabolic pathway knowledgebase for grapevine (Vitis vinifera)

PubMed Central

Naithani, Sushma; Raja, Rajani; Waddell, Elijah N.; Elser, Justin; Gouthu, Satyanarayana; Deluc, Laurent G.; Jaiswal, Pankaj

2014-01-01

We have developed VitisCyc, a grapevine-specific metabolic pathway database that allows researchers to (i) search and browse the database for its various components such as metabolic pathways, reactions, compounds, genes and proteins, (ii) compare grapevine metabolic networks with other publicly available plant metabolic networks, and (iii) upload, visualize and analyze high-throughput data such as transcriptomes, proteomes, metabolomes etc. using OMICs-Viewer tool. VitisCyc is based on the genome sequence of the nearly homozygous genotype PN40024 of Vitis vinifera “Pinot Noir” cultivar with 12X v1 annotations and was built on BioCyc platform using Pathway Tools software and MetaCyc reference database. Furthermore, VitisCyc was enriched for plant-specific pathways and grape-specific metabolites, reactions and pathways. Currently VitisCyc harbors 68 super pathways, 362 biosynthesis pathways, 118 catabolic pathways, 5 detoxification pathways, 36 energy related pathways and 6 transport pathways, 10,908 enzymes, 2912 enzymatic reactions, 31 transport reactions and 2024 compounds. VitisCyc, as a community resource, can aid in the discovery of candidate genes and pathways that are regulated during plant growth and development, and in response to biotic and abiotic stress signals generated from a plant's immediate environment. VitisCyc version 3.18 is available online at http://pathways.cgrb.oregonstate.edu. PMID:25538713

ReactPRED: a tool to predict and analyze biochemical reactions.

PubMed

Sivakumar, Tadi Venkata; Giri, Varun; Park, Jin Hwan; Kim, Tae Yong; Bhaduri, Anirban

2016-11-15

Biochemical pathways engineering is often used to synthesize or degrade target chemicals. In silico screening of the biochemical transformation space allows predicting feasible reactions, constituting these pathways. Current enabling tools are customized to predict reactions based on pre-defined biochemical transformations or reaction rule sets. Reaction rule sets are usually curated manually and tailored to specific applications. They are not exhaustive. In addition, current systems are incapable of regulating and refining data with an aim to tune specificity and sensitivity. A robust and flexible tool that allows automated reaction rule set creation along with regulated pathway prediction and analyses is a need. ReactPRED aims to address the same. ReactPRED is an open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. The tool allows automated reaction rule creation from a user defined reaction set. Additionally, reaction rule degree and rule tolerance features allow refinement of predicted data. It is available as a flexible graphical user interface and a console application. ReactPRED is available at: https://sourceforge.net/projects/reactpred/ CONTACT: anirban.b@samsung.com or ty76.kim@samsung.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Warfighter Integrated Physical Ergonomics Tool Development: Needs Analysis and State of the Art Review

DTIC Science & Technology

2011-03-01

Humansystems® Warfighter Integrated Physical Ergonomics Tool Development Page 14 e) Forces: Griffon seat design assessments include questions of vibration...the suitability of alternative designs . Humansystems® Warfighter Integrated Physical Ergonomics Tool Development Page 5 e) Performance Measures...configurations to assess Humansystems® Warfighter Integrated Physical Ergonomics Tool Development Page 8 design and acquisition decisions, and more

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

DOE PAGES

King, Zachary A.; Lu, Justin; Drager, Andreas; ...

2015-10-17

In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

PubMed Central

King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456

Logic integration of mRNA signals by an RNAi-based molecular computer.

PubMed

Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov

2010-05-01

Synthetic in vivo molecular 'computers' could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that 'transduce' mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi 'computational' module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting.

Logic integration of mRNA signals by an RNAi-based molecular computer

PubMed Central

Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov

2010-01-01

Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting. PMID:20194121

WISB: Warwick Integrative Synthetic Biology Centre

PubMed Central

McCarthy, John

2016-01-01

Synthetic biology promises to create high-impact solutions to challenges in the areas of biotechnology, human/animal health, the environment, energy, materials and food security. Equally, synthetic biologists create tools and strategies that have the potential to help us answer important fundamental questions in biology. Warwick Integrative Synthetic Biology (WISB) pursues both of these mutually complementary ‘build to apply’ and ‘build to understand’ approaches. This is reflected in our research structure, in which a core theme on predictive biosystems engineering develops underpinning understanding as well as next-generation experimental/theoretical tools, and these are then incorporated into three applied themes in which we engineer biosynthetic pathways, microbial communities and microbial effector systems in plants. WISB takes a comprehensive approach to training, education and outreach. For example, WISB is a partner in the EPSRC/BBSRC-funded U.K. Doctoral Training Centre in synthetic biology, we have developed a new undergraduate module in the subject, and we have established five WISB Research Career Development Fellowships to support young group leaders. Research in Ethical, Legal and Societal Aspects (ELSA) of synthetic biology is embedded in our centre activities. WISB has been highly proactive in building an international research and training network that includes partners in Barcelona, Boston, Copenhagen, Madrid, Marburg, São Paulo, Tartu and Valencia. PMID:27284024

WISB: Warwick Integrative Synthetic Biology Centre.

PubMed

McCarthy, John

2016-06-15

Synthetic biology promises to create high-impact solutions to challenges in the areas of biotechnology, human/animal health, the environment, energy, materials and food security. Equally, synthetic biologists create tools and strategies that have the potential to help us answer important fundamental questions in biology. Warwick Integrative Synthetic Biology (WISB) pursues both of these mutually complementary 'build to apply' and 'build to understand' approaches. This is reflected in our research structure, in which a core theme on predictive biosystems engineering develops underpinning understanding as well as next-generation experimental/theoretical tools, and these are then incorporated into three applied themes in which we engineer biosynthetic pathways, microbial communities and microbial effector systems in plants. WISB takes a comprehensive approach to training, education and outreach. For example, WISB is a partner in the EPSRC/BBSRC-funded U.K. Doctoral Training Centre in synthetic biology, we have developed a new undergraduate module in the subject, and we have established five WISB Research Career Development Fellowships to support young group leaders. Research in Ethical, Legal and Societal Aspects (ELSA) of synthetic biology is embedded in our centre activities. WISB has been highly proactive in building an international research and training network that includes partners in Barcelona, Boston, Copenhagen, Madrid, Marburg, São Paulo, Tartu and Valencia. © 2016 The Author(s).

Using Kepler for Tool Integration in Microarray Analysis Workflows.

PubMed

Gan, Zhuohui; Stowe, Jennifer C; Altintas, Ilkay; McCulloch, Andrew D; Zambon, Alexander C

Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Runhaar, Hens

An abundance of approaches, strategies, and instruments – in short: tools – have been developed that intend to stimulate or facilitate the integration of a variety of environmental objectives into development planning, national or regional sectoral policies, international agreements, business strategies, etc. These tools include legally mandatory procedures, such as Environmental Impact Assessment and Strategic Environmental Assessment; more voluntary tools such as environmental indicators developed by scientists and planning tools; green budgeting, etc. A relatively underexplored question is what integration tool fits what particular purposes and contexts, in short: “what works where?”. This paper intends to contribute to answering thismore » question, by first providing conceptual clarity about what integration entails, by suggesting and illustrating a classification of integration tools, and finally by summarising some of the lessons learned about how and why integration tools are (not) used and with what outcomes, particularly in terms of promoting the integration of environmental objectives.« less

Compound toxicity screening and structure-activity relationship modeling in Escherichia coli.

PubMed

Planson, Anne-Gaëlle; Carbonell, Pablo; Paillard, Elodie; Pollet, Nicolas; Faulon, Jean-Loup

2012-03-01

Synthetic biology and metabolic engineering are used to develop new strategies for producing valuable compounds ranging from therapeutics to biofuels in engineered microorganisms. When developing methods for high-titer production cells, toxicity is an important element to consider. Indeed the production rate can be limited due to toxic intermediates or accumulation of byproducts of the heterologous biosynthetic pathway of interest. Conversely, highly toxic molecules are desired when designing antimicrobials. Compound toxicity in bacteria plays a major role in metabolic engineering as well as in the development of new antibacterial agents. Here, we screened a diversified chemical library of 166 compounds for toxicity in Escherichia coli. The dataset was built using a clustering algorithm maximizing the chemical diversity in the library. The resulting assay data was used to develop a toxicity predictor that we used to assess the toxicity of metabolites throughout the metabolome. This new tool for predicting toxicity can thus be used for fine-tuning heterologous expression and can be integrated in a computational-framework for metabolic pathway design. Many structure-activity relationship tools have been developed for toxicology studies in eukaryotes [Valerio (2009), Toxicol Appl Pharmacol, 241(3): 356-370], however, to the best of our knowledge we present here the first E. coli toxicity prediction web server based on QSAR models (EcoliTox server: http://www.issb.genopole.fr/∼faulon/EcoliTox.php). Copyright © 2011 Wiley Periodicals, Inc.

Improving Program Design and Assessment with Broadening Participation Resources

NASA Astrophysics Data System (ADS)

Siegfried, D.; Johnson, A.; Thomas, S. H.; Fauver, A.; Detrick, L.

2012-12-01

Many theoretical and research-based approaches suggest how to best use mentoring to enhance an undergraduate research program. The Institute for Broadening Participation's Pathways to Engineering and Pathways to Ocean Sciences projects synthesized a set of mentoring studies, theoretical sources, and other texts pertinent to undergraduate research program design into a suite of practical tools that includes an online mentoring manual, an online reference library of mentoring and diversity literature, and practical guides such as Using Social Media to Build Diversity in Your REU. The overall goal is to provide easy-to-access resources that can assist faculty and program directors in implementing or honing the mentoring elements in their research programs for undergraduates. IBP's Online Mentoring Manual addresses common themes, such as modeling, student self-efficacy, career development, retention and evaluation. The Online Diversity Reference Library provides a comprehensive, annotated selection of key policy documents, research studies, intervention studies, and other texts on broadening participation in science, technology, engineering and mathematics. IBP's suite of tools provides the theoretical underpinnings and research findings that can help leaders in education integrate site-appropriate mentoring elements into their educational programs. Program directors and faculty from a variety of program types and disciplines have benefitted from using the Manual and other resources. IBP continues the work of translating and synthesizing theory to practice and welcomes your participation and partnership in that effort.

miRegulome: a knowledge-base of miRNA regulomics and analysis.

PubMed

Barh, Debmalya; Kamapantula, Bhanu; Jain, Neha; Nalluri, Joseph; Bhattacharya, Antaripa; Juneja, Lucky; Barve, Neha; Tiwari, Sandeep; Miyoshi, Anderson; Azevedo, Vasco; Blum, Kenneth; Kumar, Anil; Silva, Artur; Ghosh, Preetam

2015-08-05

miRNAs regulate post transcriptional gene expression by targeting multiple mRNAs and hence can modulate multiple signalling pathways, biological processes, and patho-physiologies. Therefore, understanding of miRNA regulatory networks is essential in order to modulate the functions of a miRNA. The focus of several existing databases is to provide information on specific aspects of miRNA regulation. However, an integrated resource on the miRNA regulome is currently not available to facilitate the exploration and understanding of miRNA regulomics. miRegulome attempts to bridge this gap. The current version of miRegulome v1.0 provides details on the entire regulatory modules of miRNAs altered in response to chemical treatments and transcription factors, based on validated data manually curated from published literature. Modules of miRegulome (upstream regulators, downstream targets, miRNA regulated pathways, functions, diseases, etc) are hyperlinked to an appropriate external resource and are displayed visually to provide a comprehensive understanding. Four analysis tools are incorporated to identify relationships among different modules based on user specified datasets. miRegulome and its tools are helpful in understanding the biology of miRNAs and will also facilitate the discovery of biomarkers and therapeutics. With added features in upcoming releases, miRegulome will be an essential resource to the scientific community. http://bnet.egr.vcu.edu/miRegulome.

Integrative Analysis of the Physical Transport Network into Australia.

PubMed

Cope, Robert C; Ross, Joshua V; Wittmann, Talia A; Prowse, Thomas A A; Cassey, Phillip

2016-01-01

Effective biosecurity is necessary to protect nations and their citizens from a variety of threats, including emerging infectious diseases, agricultural or environmental pests and pathogens, and illegal wildlife trade. The physical pathways by which these threats are transported internationally, predominantly shipping and air traffic, have undergone significant growth and changes in spatial distributions in recent decades. An understanding of the specific pathways and donor-traffic hotspots created by this integrated physical transport network is vital for the development of effective biosecurity strategies into the future. In this study, we analysed the physical transport network into Australia over the period 1999-2012. Seaborne and air traffic were weighted to calculate a "weighted cumulative impact" score for each source region worldwide, each year. High risk source regions, and those source regions that underwent substantial changes in risk over the study period, were determined. An overall risk ranking was calculated by integrating across all possible weighting combinations. The source regions having greatest overall physical connectedness with Australia were Singapore, which is a global transport hub, and the North Island of New Zealand, a close regional trading partner with Australia. Both those regions with large amounts of traffic across multiple vectors (e.g., Hong Kong), and those with high levels of traffic of only one type (e.g., Bali, Indonesia with respect to passenger flights), were represented among high risk source regions. These data provide a baseline model for the transport of individuals and commodities against which the effectiveness of biosecurity controls may be assessed, and are a valuable tool in the development of future biosecurity policy.

Integrative Analysis of the Physical Transport Network into Australia

PubMed Central

Cope, Robert C.; Ross, Joshua V.; Wittmann, Talia A.; Prowse, Thomas A. A.; Cassey, Phillip

2016-01-01

Effective biosecurity is necessary to protect nations and their citizens from a variety of threats, including emerging infectious diseases, agricultural or environmental pests and pathogens, and illegal wildlife trade. The physical pathways by which these threats are transported internationally, predominantly shipping and air traffic, have undergone significant growth and changes in spatial distributions in recent decades. An understanding of the specific pathways and donor-traffic hotspots created by this integrated physical transport network is vital for the development of effective biosecurity strategies into the future. In this study, we analysed the physical transport network into Australia over the period 1999–2012. Seaborne and air traffic were weighted to calculate a “weighted cumulative impact” score for each source region worldwide, each year. High risk source regions, and those source regions that underwent substantial changes in risk over the study period, were determined. An overall risk ranking was calculated by integrating across all possible weighting combinations. The source regions having greatest overall physical connectedness with Australia were Singapore, which is a global transport hub, and the North Island of New Zealand, a close regional trading partner with Australia. Both those regions with large amounts of traffic across multiple vectors (e.g., Hong Kong), and those with high levels of traffic of only one type (e.g., Bali, Indonesia with respect to passenger flights), were represented among high risk source regions. These data provide a baseline model for the transport of individuals and commodities against which the effectiveness of biosecurity controls may be assessed, and are a valuable tool in the development of future biosecurity policy. PMID:26881782

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network1[OPEN

PubMed Central

Gloaguen, Pauline; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves

2017-01-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. PMID:28442501

FAAP20: a novel ubiquitin-binding FA nuclear core-complex protein required for functional integrity of the FA-BRCA DNA repair pathway

PubMed Central

Ali, Abdullah Mahmood; Pradhan, Arun; Singh, Thiyam Ramsingh; Du, Changhu; Li, Jie; Wahengbam, Kebola; Grassman, Elke; Auerbach, Arleen D.; Pang, Qishen

2012-01-01

Fanconi anemia (FA) nuclear core complex is a multiprotein complex required for the functional integrity of the FA-BRCA pathway regulating DNA repair. This pathway is inactivated in FA, a devastating genetic disease, which leads to hematologic defects and cancer in patients. Here we report the isolation and characterization of a novel 20-kDa FANCA-associated protein (FAAP20). We show that FAAP20 is an integral component of the FA nuclear core complex. We identify a region on FANCA that physically interacts with FAAP20, and show that FANCA regulates stability of this protein. FAAP20 contains a conserved ubiquitin-binding zinc-finger domain (UBZ), and binds K-63–linked ubiquitin chains in vitro. The FAAP20-UBZ domain is not required for interaction with FANCA, but is required for DNA-damage–induced chromatin loading of FANCA and the functional integrity of the FA pathway. These findings reveal critical roles for FAAP20 in the FA-BRCA pathway of DNA damage repair and genome maintenance. PMID:22343915

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

PubMed

Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

2016-01-01

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

Integrating Reliability Analysis with a Performance Tool

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Ulrey, Michael

1995-01-01

A large number of commercial simulation tools support performance oriented studies of complex computer and communication systems. Reliability of these systems, when desired, must be obtained by remodeling the system in a different tool. This has obvious drawbacks: (1) substantial extra effort is required to create the reliability model; (2) through modeling error the reliability model may not reflect precisely the same system as the performance model; (3) as the performance model evolves one must continuously reevaluate the validity of assumptions made in that model. In this paper we describe an approach, and a tool that implements this approach, for integrating a reliability analysis engine into a production quality simulation based performance modeling tool, and for modeling within such an integrated tool. The integrated tool allows one to use the same modeling formalisms to conduct both performance and reliability studies. We describe how the reliability analysis engine is integrated into the performance tool, describe the extensions made to the performance tool to support the reliability analysis, and consider the tool's performance.

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing

PubMed Central

Nguyen, Nga Thi Thuy; Vincens, Pierre

2018-01-01

Abstract Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). PMID:29087490

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

PubMed

Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

2008-01-01

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

Using genetic data to strengthen causal inference in observational research.

PubMed

Pingault, Jean-Baptiste; O'Reilly, Paul F; Schoeler, Tabea; Ploubidis, George B; Rijsdijk, Frühling; Dudbridge, Frank

2018-06-05

Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.

Petunia (Petunia hybrida).

PubMed

Lutke, W Kevin

2006-01-01

Petunia hybrida genetic transformation continues to be a valuable tool for genetic research into biochemical pathways and gene expression, as well as generating commercial products with varying floral colors. In this chapter, we describe a simple and reproducible genetic transformation protocol for generating transgenic petunia plants harboring a gene of interest and selectable marker. The system utilizes Agrobacterium tumefaciens for transgene integration with plant recovery via shoot organogenesis from leaf explant material. Selection for transgenic plants is achieved using the bar gene conferring resistance to glufosinate or nptII gene for resistance to kanamycin. Transformation efficiencies of around 10% are achievable with shoots being recovered about 8 wk after transgene insertion and rooted plants transferred to the greenhouse about twelve weeks after inoculation.

From generic pathways to ICT-supported horizontally integrated care: the SmartCare approach and convergence with future Internet assembly.

PubMed

Urošević, Vladimir; Mitić, Marko

2014-01-01

Successful service integration in policy and practice requires both technology innovation and service process innovation being pursued and implemented at the same time. The SmartCare project (partially EC-funded under CIP ICT PSP Program) aims to achieve this through development, piloting and evaluation of ICT-based services, horizontally integrating health and social care in ten pilot regions, including Kraljevo region in Serbia. The project has identified and adopted two generic highest-level common thematic pathways in joint consolidation phase - integrated support for long-term care and integrated support after hospital discharge. A common set of standard functional specifications for an open ICT platform enabling the delivery of integrated care is being defined, around the challenges of data sharing, coordination and communication in these two formalized pathways. Implementation and system integration on technology and architecture level are to be based on open standards, multivendor interoperability, and leveraging on the current evolving open specification technology foundations developed in relevant projects across the European Research Area.

Integrating toxicogenomics data into cancer adverse outcome pathways

EPA Science Inventory

Integrating toxicogenomics data into adverse outcome pathways for cancer.J. Christopher CortonNHEERL/ORD, EPA, Research Triangle Park, NCAs the toxicology field continues to move towards a new paradigm in toxicity testing and safety assessment, there is the expectation that model...

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

Mandel, Johannes J; Fuß, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-01-01

Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

PathScore: a web tool for identifying altered pathways in cancer data.

PubMed

Gaffney, Stephen G; Townsend, Jeffrey P

2016-12-01

PathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects. Web application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at: github.com/sggaffney/pathscore with a GPLv3 license. stephen.gaffney@yale.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

Earth System Documentation (ES-DOC) Preparation for CMIP6

NASA Astrophysics Data System (ADS)

Denvil, S.; Murphy, S.; Greenslade, M. A.; Lawrence, B.; Guilyardi, E.; Pascoe, C.; Treshanksy, A.; Elkington, M.; Hibling, E.; Hassell, D.

2015-12-01

During the course of 2015 the Earth System Documentation (ES-DOC) project began its preparations for CMIP6 (Coupled Model Inter-comparison Project 6) by further extending the ES-DOC tooling ecosystem in support of Earth System Model (ESM) documentation creation, search, viewing & comparison. The ES-DOC online questionnaire, the ES-DOC desktop notebook, and the ES-DOC python toolkit will serve as multiple complementary pathways to generating CMIP6 documentation. It is envisaged that institutes will leverage these tools at different points of the CMIP6 lifecycle. Institutes will be particularly interested to know that the documentation burden will be either streamlined or completely automated.As all the tools are tightly integrated with the ES-DOC web-service, institutes can be confident that the latency between documentation creation & publishing will be reduced to a minimum. Published documents will be viewable with the online ES-DOC Viewer (accessible via citable URL's). Model inter-comparison scenarios will be supported using the ES-DOC online Comparator tool. The Comparator is being extended to:• Support comparison of both Model descriptions & Simulation runs;• Greatly streamline the effort involved in compiling official tables.The entire ES-DOC ecosystem is open source and built upon open standards such as the Common Information Model (CIM) (versions 1 and 2).

CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets

PubMed Central

Li, Yang; Liu, Jun S.; Mootha, Vamsi K.

2017-01-01

In recent years, there has been a huge rise in the number of publicly available transcriptional profiling datasets. These massive compendia comprise billions of measurements and provide a special opportunity to predict the function of unstudied genes based on co-expression to well-studied pathways. Such analyses can be very challenging, however, since biological pathways are modular and may exhibit co-expression only in specific contexts. To overcome these challenges we introduce CLIC, CLustering by Inferred Co-expression. CLIC accepts as input a pathway consisting of two or more genes. It then uses a Bayesian partition model to simultaneously partition the input gene set into coherent co-expressed modules (CEMs), while assigning the posterior probability for each dataset in support of each CEM. CLIC then expands each CEM by scanning the transcriptome for additional co-expressed genes, quantified by an integrated log-likelihood ratio (LLR) score weighted for each dataset. As a byproduct, CLIC automatically learns the conditions (datasets) within which a CEM is operative. We implemented CLIC using a compendium of 1774 mouse microarray datasets (28628 microarrays) or 1887 human microarray datasets (45158 microarrays). CLIC analysis reveals that of 910 canonical biological pathways, 30% consist of strongly co-expressed gene modules for which new members are predicted. For example, CLIC predicts a functional connection between protein C7orf55 (FMC1) and the mitochondrial ATP synthase complex that we have experimentally validated. CLIC is freely available at www.gene-clic.org. We anticipate that CLIC will be valuable both for revealing new components of biological pathways as well as the conditions in which they are active. PMID:28719601

FragariaCyc: A Metabolic Pathway Database for Woodland Strawberry Fragaria vesca

PubMed Central

Naithani, Sushma; Partipilo, Christina M.; Raja, Rajani; Elser, Justin L.; Jaiswal, Pankaj

2016-01-01

FragariaCyc is a strawberry-specific cellular metabolic network based on the annotated genome sequence of Fragaria vesca L. ssp. vesca, accession Hawaii 4. It was built on the Pathway-Tools platform using MetaCyc as the reference. The experimental evidences from published literature were used for supporting/editing existing entities and for the addition of new pathways, enzymes, reactions, compounds, and small molecules in the database. To date, FragariaCyc comprises 66 super-pathways, 488 unique pathways, 2348 metabolic reactions, 3507 enzymes, and 2134 compounds. In addition to searching and browsing FragariaCyc, researchers can compare pathways across various plant metabolic networks and analyze their data using Omics Viewer tool. We view FragariaCyc as a resource for the community of researchers working with strawberry and related fruit crops. It can help understanding the regulation of overall metabolism of strawberry plant during development and in response to diseases and abiotic stresses. FragariaCyc is available online at http://pathways.cgrb.oregonstate.edu. PMID:26973684

VISIBIOweb: visualization and layout services for BioPAX pathway models

PubMed Central

Dilek, Alptug; Belviranli, Mehmet E.; Dogrusoz, Ugur

2010-01-01

With recent advancements in techniques for cellular data acquisition, information on cellular processes has been increasing at a dramatic rate. Visualization is critical to analyzing and interpreting complex information; representing cellular processes or pathways is no exception. VISIBIOweb is a free, open-source, web-based pathway visualization and layout service for pathway models in BioPAX format. With VISIBIOweb, one can obtain well-laid-out views of pathway models using the standard notation of the Systems Biology Graphical Notation (SBGN), and can embed such views within one's web pages as desired. Pathway views may be navigated using zoom and scroll tools; pathway object properties, including any external database references available in the data, may be inspected interactively. The automatic layout component of VISIBIOweb may also be accessed programmatically from other tools using Hypertext Transfer Protocol (HTTP). The web site is free and open to all users and there is no login requirement. It is available at: http://visibioweb.patika.org. PMID:20460470

Techno-economic analysis of biofuel production considering logistic configurations.

PubMed

Li, Qi; Hu, Guiping

2016-04-01

In the study, a techno-economic analysis method considering logistic configurations is proposed. The economic feasibility of a low temperature biomass gasification pathway and an integrated pathway with fast pyrolysis and bio-oil gasification are evaluated and compared with the proposed method in Iowa. The results show that both pathways are profitable, biomass gasification pathway could achieve an Internal Rate of Return (IRR) of 10.00% by building a single biorefinery and integrated bio-oil gasification pathway could achieve an IRR of 3.32% by applying decentralized supply chain structure. A Monte-Carlo simulation considering interactions among parameters is also proposed and conducted, which indicates that both pathways are at high risk currently. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders

PubMed Central

Jha, Prabhash Kumar; Vijay, Aatira; Sahu, Anita; Ashraf, Mohammad Zahid

2016-01-01

Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool’s rich library was used for comprehensive functional enrichment and pathway analysis which revealed “mRNA Splicing” and “SUMO E3 ligases SUMOylate target proteins” among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers. PMID:27892526

Paper-based microreactor integrating cell culture and subsequent immunoassay for the investigation of cellular phosphorylation.

PubMed

Lei, Kin Fong; Huang, Chia-Hao

2014-12-24

Investigation of cellular phosphorylation and signaling pathway has recently gained much attention for the study of pathogenesis of cancer. Related conventional bioanalytical operations for this study including cell culture and Western blotting are time-consuming and labor-intensive. In this work, a paper-based microreactor has been developed to integrate cell culture and subsequent immunoassay on a single paper. The paper-based microreactor was a filter paper with an array of circular zones for running multiple cell cultures and subsequent immunoassays. Cancer cells were directly seeded in the circular zones without hydrogel encapsulation and cultured for 1 day. Subsequently, protein expressions including structural, functional, and phosphorylated proteins of the cells could be detected by their specific antibodies, respectively. Study of the activation level of phosphorylated Stat3 of liver cancer cells stimulated by IL-6 cytokine was demonstrated by the paper-based microreactor. This technique can highly reduce tedious bioanalytical operation and sample and reagent consumption. Also, the time required by the entire process can be shortened. This work provides a simple and rapid screening tool for the investigation of cellular phosphorylation and signaling pathway for understanding the pathogenesis of cancer. In addition, the operation of the paper-based microreactor is compatible to the molecular biological training, and therefore, it has the potential to be developed for routine protocol for various research areas in conventional bioanalytical laboratories.

Conscious coupling: The challenges and opportunities of cascading enzymatic microreactors.

PubMed

Gruber, Pia; Marques, Marco P C; O'Sullivan, Brian; Baganz, Frank; Wohlgemuth, Roland; Szita, Nicolas

2017-07-01

The continuous production of high value or difficult to synthesize products is of increasing interest to the pharmaceutical industry. Cascading reaction systems have already been employed for chemical synthesis with great success, allowing a quick change in reaction conditions and addition of new reactants as well as removal of side products. A cascading system can remove the need for isolating unstable intermediates, increasing the yield of a synthetic pathway. Based on the success for chemical synthesis, the question arises how cascading systems could be beneficial to chemo-enzymatic or biocatalytic synthesis. Microreactors, with their rapid mass and heat transfer, small reaction volumes and short diffusion pathways, are promising tools for the development of such processes. In this mini-review, the authors provide an overview of recent examples of cascaded microreactors. Special attention will be paid to how microreactors are combined and the challenges as well as opportunities that arise from such combinations. Selected chemical reaction cascades will be used to illustrate this concept, before the discussion is widened to include chemo-enzymatic and multi-enzyme cascades. The authors also present the state of the art of online and at-line monitoring for enzymatic microreactor cascades. Finally, the authors review work-up and purification steps and their integration with microreactor cascades, highlighting the potential and the challenges of integrated cascades. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MelanomaDB: A Web Tool for Integrative Analysis of Melanoma Genomic Information to Identify Disease-Associated Molecular Pathways

PubMed Central

Trevarton, Alexander J.; Mann, Michael B.; Knapp, Christoph; Araki, Hiromitsu; Wren, Jonathan D.; Stones-Havas, Steven; Black, Michael A.; Print, Cristin G.

2013-01-01

Despite on-going research, metastatic melanoma survival rates remain low and treatment options are limited. Researchers can now access a rapidly growing amount of molecular and clinical information about melanoma. This information is becoming difficult to assemble and interpret due to its dispersed nature, yet as it grows it becomes increasingly valuable for understanding melanoma. Integration of this information into a comprehensive resource to aid rational experimental design and patient stratification is needed. As an initial step in this direction, we have assembled a web-accessible melanoma database, MelanomaDB, which incorporates clinical and molecular data from publically available sources, which will be regularly updated as new information becomes available. This database allows complex links to be drawn between many different aspects of melanoma biology: genetic changes (e.g., mutations) in individual melanomas revealed by DNA sequencing, associations between gene expression and patient survival, data concerning drug targets, biomarkers, druggability, and clinical trials, as well as our own statistical analysis of relationships between molecular pathways and clinical parameters that have been produced using these data sets. The database is freely available at http://genesetdb.auckland.ac.nz/melanomadb/about.html. A subset of the information in the database can also be accessed through a freely available web application in the Illumina genomic cloud computing platform BaseSpace at http://www.biomatters.com/apps/melanoma-profiler-for-research. The MelanomaDB database illustrates dysregulation of specific signaling pathways across 310 exome-sequenced melanomas and in individual tumors and identifies the distribution of somatic variants in melanoma. We suggest that MelanomaDB can provide a context in which to interpret the tumor molecular profiles of individual melanoma patients relative to biological information and available drug therapies. PMID:23875173

Toward an operational model of decision making, emotional regulation, and mental health impact.

PubMed

Collura, Thomas Francis; Zalaquett, Ronald P; Bonnstetter, Carlos Joyce; Chatters, Seria J

2014-01-01

Current brain research increasingly reveals the underlying mechanisms and processes of human behavior, cognition, and emotion. In addition to being of interest to a wide range of scientists, educators, and professionals, as well as laypeople, brain-based models are of particular value in a clinical setting. Psychiatrists, psychologists, counselors, and other mental health professionals are in need of operational models that integrate recent findings in the physical, cognitive, and emotional domains, and offer a common language for interdisciplinary understanding and communication. Based on individual traits, predispositions, and responses to stimuli, we can begin to identify emotional and behavioral pathways and mental processing patterns. The purpose of this article is to present a brain-path activation model to understand individual differences in decision making and psychopathology. The first section discusses the role of frontal lobe electroencephalography (EEG) asymmetry, summarizes state- and trait-based models of decision making, and provides a more complex analysis that supplements the traditional simple left-right brain model. Key components of the new model are the introduction of right hemisphere parallel and left hemisphere serial scanning in rendering decisions, and the proposition of pathways that incorporate both past experiences as well as future implications into the decision process. Main attributes of each decision-making mechanism are provided. The second section applies the model within the realm of clinical mental health as a tool to understand specific human behavior and pathology. Applications include general and chronic anxiety, depression, paranoia, risk taking, and the pathways employed when well-functioning operational integration is observed. Finally, specific applications such as meditation and mindfulness are offered to facilitate positive functioning.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways

PubMed Central

Becnel, Lauren B.; Darlington, Yolanda F.; Ochsner, Scott A.; Easton-Marks, Jeremy R.; Watkins, Christopher M.; McOwiti, Apollo; Kankanamge, Wasula H.; Wise, Michael W.; DeHart, Michael; Margolis, Ronald N.; McKenna, Neil J.

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse ‘omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy “Web 2.0” technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA’s Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field. PMID:26325041

Exploring the combinatorial space of complete pathways to chemicals.

PubMed

Wang, Lin; Ng, Chiam Yu; Dash, Satyakam; Maranas, Costas D

2018-04-06

Computational pathway design tools often face the challenges of balancing the stoichiometry of co-metabolites and cofactors, and dealing with reaction rule utilization in a single workflow. To this end, we provide an overview of two complementary stoichiometry-based pathway design tools optStoic and novoStoic developed in our group to tackle these challenges. optStoic is designed to determine the stoichiometry of overall conversion first which optimizes a performance criterion (e.g. high carbon/energy efficiency) and ensures a comprehensive search of co-metabolites and cofactors. The procedure then identifies the minimum number of intervening reactions to connect the source and sink metabolites. We also further the pathway design procedure by expanding the search space to include both known and hypothetical reactions, represented by reaction rules, in a new tool termed novoStoic. Reaction rules are derived based on a mixed-integer linear programming (MILP) compatible reaction operator, which allow us to explore natural promiscuous enzymes, engineer candidate enzymes that are not already promiscuous as well as design de novo enzymes. The identified biochemical reaction rules then guide novoStoic to design routes that expand the currently known biotransformation space using a single MILP modeling procedure. We demonstrate the use of the two computational tools in pathway elucidation by designing novel synthetic routes for isobutanol. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Penalized differential pathway analysis of integrative oncogenomics studies.

PubMed

van Wieringen, Wessel N; van de Wiel, Mark A

2014-04-01

Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (L1) penalty to obtain a sparse pathway topology. Simulations show that the inclusion of DNA copy number data benefits the discovery of gene-gene interactions. In addition, the simulations reveal that cis-effects tend to be over-estimated in a univariate (single gene) analysis. In the application to real data from integrative oncogenomic studies we show that inclusion of prior information on the regulatory network architecture benefits the reproducibility of all edges. Furthermore, analyses of the TP53 and TGFb signaling pathways between ER+ and ER- samples from an integrative genomics breast cancer study identify reproducible differential regulatory patterns that corroborate with existing literature.

The application of high-resolution mass spectrometry-based data-mining tools in tandem to metabolite profiling of a triple drug combination in humans.

PubMed

Xing, Jie; Zang, Meitong; Zhang, Haiying; Zhu, Mingshe

2015-10-15

Patients are usually exposed to multiple drugs, and metabolite profiling of each drug in complex biological matrices is a big challenge. This study presented a new application of an improved high resolution mass spectrometry (HRMS)-based data-mining tools in tandem to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was metronidazole-pantoprazole-clarithromycin (MET-PAN-CLAR), which is widely used in clinic to treat ulcers caused by Helicobacter pylori. First, mass defect filter (MDF), as a targeted data processing tool, was able to recover all relevant metabolites of MET-PAN-CLAR in human plasma and urine from the full-scan MS dataset when appropriate MDF templates for each drug were defined. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, worked effectively except for several trace metabolites, which were buried in the remaining background signals. Third, an integrated strategy, i.e., untargeted BS followed by improved MDF, was effective for metabolite identification of MET-PAN-CLAR. Most metabolites except for trace ones were found in the first step of BS-processed datasets, and the results led to the setup of appropriate metabolite MDF template for the subsequent MDF data processing. Trace metabolites were further recovered by MDF, which used both common MDF templates and the novel metabolite-based MDF templates. As a result, a total of 44 metabolites or related components were found for MET-PAN-CLAR in human plasma and urine using the integrated strategy. New metabolic pathways such as N-glucuronidation of PAN and dehydrogenation of CLAR were found. This study demonstrated that the combination of accurate mass-based multiple data-mining techniques in tandem, i.e., untargeted background subtraction followed by targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drugs in vivo. Copyright © 2015 Elsevier B.V. All rights reserved.

SS-mPMG and SS-GA: tools for finding pathways and dynamic simulation of metabolic networks.

PubMed

Katsuragi, Tetsuo; Ono, Naoaki; Yasumoto, Keiichi; Altaf-Ul-Amin, Md; Hirai, Masami Y; Sriyudthsak, Kansuporn; Sawada, Yuji; Yamashita, Yui; Chiba, Yukako; Onouchi, Hitoshi; Fujiwara, Toru; Naito, Satoshi; Shiraishi, Fumihide; Kanaya, Shigehiko

2013-05-01

Metabolomics analysis tools can provide quantitative information on the concentration of metabolites in an organism. In this paper, we propose the minimum pathway model generator tool for simulating the dynamics of metabolite concentrations (SS-mPMG) and a tool for parameter estimation by genetic algorithm (SS-GA). SS-mPMG can extract a subsystem of the metabolic network from the genome-scale pathway maps to reduce the complexity of the simulation model and automatically construct a dynamic simulator to evaluate the experimentally observed behavior of metabolites. Using this tool, we show that stochastic simulation can reproduce experimentally observed dynamics of amino acid biosynthesis in Arabidopsis thaliana. In this simulation, SS-mPMG extracts the metabolic network subsystem from published databases. The parameters needed for the simulation are determined using a genetic algorithm to fit the simulation results to the experimental data. We expect that SS-mPMG and SS-GA will help researchers to create relevant metabolic networks and carry out simulations of metabolic reactions derived from metabolomics data.

White matter integrity deficits in prefrontal-amygdala pathways in Williams syndrome.

PubMed

Avery, Suzanne N; Thornton-Wells, Tricia A; Anderson, Adam W; Blackford, Jennifer Urbano

2012-01-16

Williams syndrome is a neurodevelopmental disorder associated with significant non-social fears. Consistent with this elevated non-social fear, individuals with Williams syndrome have an abnormally elevated amygdala response when viewing threatening non-social stimuli. In typically-developing individuals, amygdala activity is inhibited through dense, reciprocal white matter connections with the prefrontal cortex. Neuroimaging studies suggest a functional uncoupling of normal prefrontal-amygdala inhibition in individuals with Williams syndrome, which might underlie both the extreme amygdala activity and non-social fears. This functional uncoupling might be caused by structural deficits in underlying white matter pathways; however, prefrontal-amygdala white matter deficits have yet to be explored in Williams syndrome. We used diffusion tensor imaging to investigate prefrontal-amygdala white matter integrity differences in individuals with Williams syndrome and typically-developing controls with high levels of non-social fear. White matter pathways between the amygdala and several prefrontal regions were isolated using probabilistic tractography. Within each pathway, we tested for between-group differences in three measures of white matter integrity: fractional anisotropy (FA), radial diffusivity (RD), and parallel diffusivity (λ(1)). Individuals with Williams syndrome had lower FA, compared to controls, in several of the prefrontal-amygdala pathways investigated, indicating a reduction in white matter integrity. Lower FA in Williams syndrome was explained by significantly higher RD, with no differences in λ(1), suggestive of lower fiber density or axon myelination in prefrontal-amygdala pathways. These results suggest that deficits in the structural integrity of prefrontal-amygdala white matter pathways might underlie the increased amygdala activity and extreme non-social fears observed in Williams syndrome. Copyright © 2011 Elsevier Inc. All rights reserved.

Automated visualization of rule-based models

PubMed Central

Tapia, Jose-Juan; Faeder, James R.

2017-01-01

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

PubMed Central

Hahn, Aria S.; Altman, Tomer; Konwar, Kishori M.; Hanson, Niels W.; Kim, Dongjae; Relman, David A.; Dill, David L.; Hallam, Steven J.

2017-01-01

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools. PMID:28398290

Service-based analysis of biological pathways

PubMed Central

Zheng, George; Bouguettaya, Athman

2009-01-01

Background Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper. PMID:19796403

Surgical Technology Integration with Tools for Cognitive Human Factors (STITCH)

DTIC Science & Technology

2008-10-24

Award Number: W81XWH-06-1-0761 TITLE: Surgical Technology Integration with Tools for Cognitive Human Factors (STITCH) PRINCIPAL INVESTIGATOR: W...COVERED (From - To) 25 Sep 2007 - 24 Sep 2008 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Surgical Technology Integration with Tools for Cognitive...8 3. Tools and Display Technology

Large-scale integrative network-based analysis identifies common pathways disrupted by copy number alterations across cancers

PubMed Central

2013-01-01

Background Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. Results We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. Conclusions In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/. PMID:23822816

CompGO: an R package for comparing and visualizing Gene Ontology enrichment differences between DNA binding experiments.

PubMed

Waardenberg, Ashley J; Basset, Samuel D; Bouveret, Romaric; Harvey, Richard P

2015-09-02

Gene ontology (GO) enrichment is commonly used for inferring biological meaning from systems biology experiments. However, determining differential GO and pathway enrichment between DNA-binding experiments or using the GO structure to classify experiments has received little attention. Herein, we present a bioinformatics tool, CompGO, for identifying Differentially Enriched Gene Ontologies, called DiEGOs, and pathways, through the use of a z-score derivation of log odds ratios, and visualizing these differences at GO and pathway level. Through public experimental data focused on the cardiac transcription factor NKX2-5, we illustrate the problems associated with comparing GO enrichments between experiments using a simple overlap approach. We have developed an R/Bioconductor package, CompGO, which implements a new statistic normally used in epidemiological studies for performing comparative GO analyses and visualizing comparisons from . BED data containing genomic coordinates as well as gene lists as inputs. We justify the statistic through inclusion of experimental data and compare to the commonly used overlap method. CompGO is freely available as a R/Bioconductor package enabling easy integration into existing pipelines and is available at: http://www.bioconductor.org/packages/release/bioc/html/CompGO.html packages/release/bioc/html/CompGO.html.

Integrating care for neurodevelopmental disorders by unpacking control: A grounded theory study

PubMed Central

Waxegård, Gustaf; Thulesius, Hans

2016-01-01

Background To establish integrated healthcare pathways for patients with neurodevelopmental disorders (ND) such as autism spectrum disorder and attention-deficit hyperactivity disorder is challenging. This study sets out to investigate the main concerns for healthcare professionals when integrating ND care pathways and how they resolve these concerns. Methods Using classic grounded theory (Glaser), we analysed efforts to improve and integrate an ND care pathway for children and youth in a Swedish region over a period of 6 years. Data from 42 individual interviews with a range of ND professionals, nine group interviews with healthcare teams, participant observation, a 2-day dialogue conference, focus group meetings, regional media coverage, and reports from other Swedish regional ND projects were analysed. Results The main concern for participants was to deal with overwhelming ND complexity by unpacking control, which is control over strategies to define patients’ status and needs. Unpacking control is key to the professionals’ strivings to expand constructive life space for patients, to squeeze health care to reach available care goals, to promote professional ideologies, and to uphold workplace integrity. Control-seeking behaviour in relation to ND unpacking is ubiquitous and complicates integration of ND care pathways. Conclusions The Unpacking control theory expands central aspects of professions theory and may help to improve ND care development. PMID:27609793

Towards integrated solutions for water, energy, and land using an integrated nexus modeling framework

NASA Astrophysics Data System (ADS)

Wada, Y.

2017-12-01

Humanity has already reached or even exceeded the Earth's carrying capacity. Growing needs for food, energy and water will only exacerbate existing challenges over the next decades. Consequently, the acceptance of "business as usual" is eroding and we are being challenged to adopt new, more integrated, and more inclusive development pathways that avoid dangerous interference with the local environment and global planetary boundaries. This challenge is embodied in the United Nation's Sustainable Development Goals (SDGs), which endeavor to set a global agenda for moving towards more sustainable development strategies. To improve and sustain human welfare, it is critical that access to modern, reliable, and affordable water, energy, and food is expanded and maintained. The Integrated Solutions for Water, Energy, and Land (IS-WEL) project has been launched by IIASA, together with the Global Environment Facility (GEF) and the United Nations Industrial Development Organization (UNIDO). This project focuses on the water-energy-land nexus in the context of other major global challenges such as urbanization, environmental degradation, and equitable and sustainable futures. It develops a consistent framework for looking at the water-energy-land nexus and identify strategies for achieving the needed transformational outcomes through an advanced assessment framework. A multi-scalar approach are being developed that aims to combine global and regional integrated assessment tools with local stakeholder knowledge in order to identify robust solutions to energy, water, food, and ecosystem security in selected regions of the world. These are regions facing multiple energy, water and land use challenges and rapid demographic and economic changes, and are hardest hit by increasing climate variability and change. This project combines the global integrated assessment model (MESSAGE) with the global land (GLOBIOM) and water (Community Water Model) model respectively, and the integrated modeling framework are then combined with detailed regional decision support tools for water-energy-land nexus analysis in case study regions. A number of stakeholder meetings are used to engage local communities in the definition of important nexus drivers, scenario development and definition of performance metrics.

A critical source area phosphorus index with topographic transport factors using high resolution LiDAR digital elevation models

NASA Astrophysics Data System (ADS)

Thomas, Ian; Murphy, Paul; Fenton, Owen; Shine, Oliver; Mellander, Per-Erik; Dunlop, Paul; Jordan, Phil

2015-04-01

A new phosphorus index (PI) tool is presented which aims to improve the identification of critical source areas (CSAs) of phosphorus (P) losses from agricultural land to surface waters. In a novel approach, the PI incorporates topographic indices rather than watercourse proximity as proxies for runoff risk, to account for the dominant control of topography on runoff-generating areas and P transport pathways. Runoff propensity and hydrological connectivity are modelled using the Topographic Wetness Index (TWI) and Network Index (NI) respectively, utilising high resolution digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) to capture the influence of micro-topographic features on runoff pathways. Additionally, the PI attempts to improve risk estimates of particulate P losses by incorporating an erosion factor that accounts for fine-scale topographic variability within fields. Erosion risk is modelled using the Unit Stream Power Erosion Deposition (USPED) model, which integrates DEM-derived upslope contributing area and Universal Soil Loss Equation (USLE) factors. The PI was developed using field, sub-field and sub-catchment scale datasets of P source, mobilisation and transport factors, for four intensive agricultural catchments in Ireland representing different agri-environmental conditions. Datasets included soil test P concentrations, degree of P saturation, soil attributes, land use, artificial subsurface drainage locations, and 2 m resolution LiDAR DEMs resampled from 0.25 m resolution data. All factor datasets were integrated within a Geographical Information System (GIS) and rasterised to 2 m resolution. For each factor, values were categorised and assigned relative risk scores which ranked P loss potential. Total risk scores were calculated for each grid cell using a component formulation, which summed the products of weighted factor risk scores for runoff and erosion pathways. Results showed that the new PI was able to predict in-field risk variability and hence was able to identify CSAs at the sub-field scale. PI risk estimates and component scores were analysed at catchment and subcatchment scales, and validated using measured dissolved, particulate and total P losses at subcatchment snapshot sites and gauging stations at catchment outlets. The new PI provides CSA delineations at higher precision compared to conventional PIs, and more robust P transport risk estimates. The tool can be used to target cost-effective mitigation measures for P management within single farm units and wider catchments.

Big data to smart data in Alzheimer's disease: Real-world examples of advanced modeling and simulation.

PubMed

Haas, Magali; Stephenson, Diane; Romero, Klaus; Gordon, Mark Forrest; Zach, Neta; Geerts, Hugo

2016-09-01

Many disease-modifying clinical development programs in Alzheimer's disease (AD) have failed to date, and development of new and advanced preclinical models that generate actionable knowledge is desperately needed. This review reports on computer-based modeling and simulation approach as a powerful tool in AD research. Statistical data-analysis techniques can identify associations between certain data and phenotypes, such as diagnosis or disease progression. Other approaches integrate domain expertise in a formalized mathematical way to understand how specific components of pathology integrate into complex brain networks. Private-public partnerships focused on data sharing, causal inference and pathway-based analysis, crowdsourcing, and mechanism-based quantitative systems modeling represent successful real-world modeling examples with substantial impact on CNS diseases. Similar to other disease indications, successful real-world examples of advanced simulation can generate actionable support of drug discovery and development in AD, illustrating the value that can be generated for different stakeholders. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Integrated use of antioxidant enzymes and oxidative damage in two fish species to assess pollution in man-made hydroelectric reservoirs.

PubMed

Sakuragui, M M; Paulino, M G; Pereira, C D S; Carvalho, C S; Sadauskas-Henrique, H; Fernandes, M N

2013-07-01

This study investigated the relationship between contaminant body burden and the oxidative stress status of the gills and livers of two wild fish species in the Furnas Hydroelectric Power Station (HPS) reservoir (Minas Gerais, Brazil). Gills and livers presented similar pathways of metals and organochlorine bioaccumulation. During June, organochlorines were associated with lipid peroxidation (LPO), indicating oxidative stress due to the inhibition of the antioxidant enzymes superoxide dismutase and glutathione peroxidase. In the most polluted areas, metal concentrations in the liver were associated with metallothionein. During December, contaminants in the gills and liver were associated with catalase activity and LPO. Aldrin/dieldrin was the contaminant most associated with oxidative damage in the livers of both species. This integrated approach shed light on the relationship between adverse biological effects and bioaccumulation of contaminants inputted by intensive agricultural practices and proved to be a suitable tool for assessing the environmental quality of man-made reservoirs. Copyright © 2013 Elsevier Ltd. All rights reserved.

The RCSB protein data bank: integrative view of protein, gene and 3D structural information

PubMed Central

Rose, Peter W.; Prlić, Andreas; Altunkaya, Ali; Bi, Chunxiao; Bradley, Anthony R.; Christie, Cole H.; Costanzo, Luigi Di; Duarte, Jose M.; Dutta, Shuchismita; Feng, Zukang; Green, Rachel Kramer; Goodsell, David S.; Hudson, Brian; Kalro, Tara; Lowe, Robert; Peisach, Ezra; Randle, Christopher; Rose, Alexander S.; Shao, Chenghua; Tao, Yi-Ping; Valasatava, Yana; Voigt, Maria; Westbrook, John D.; Woo, Jesse; Yang, Huangwang; Young, Jasmine Y.; Zardecki, Christine; Berman, Helen M.; Burley, Stephen K.

2017-01-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a ‘Structural View of Biology.’ Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive. PMID:27794042

Improving newborn screening laboratory test ordering and result reporting using health information exchange

PubMed Central

van Dyck, Peter C; Rinaldo, Piero; McDonald, Clement; Howell, R Rodrey; Zuckerman, Alan; Downing, Gregory

2010-01-01

Capture, coding and communication of newborn screening (NBS) information represent a challenge for public health laboratories, health departments, hospitals, and ambulatory care practices. An increasing number of conditions targeted for screening and the complexity of interpretation contribute to a growing need for integrated information-management strategies. This makes NBS an important test of tools and architecture for electronic health information exchange (HIE) in this convergence of individual patient care and population health activities. For this reason, the American Health Information Community undertook three tasks described in this paper. First, a newborn screening use case was established to facilitate standards harmonization for common terminology and interoperability specifications guiding HIE. Second, newborn screening coding and terminology were developed for integration into electronic HIE activities. Finally, clarification of privacy, security, and clinical laboratory regulatory requirements governing information exchange was provided, serving as a framework to establish pathways for improving screening program timeliness, effectiveness, and efficiency of quality patient care services. PMID:20064796

Urothelial cancer of the upper urinary tract: emerging biomarkers and integrative models for risk stratification.

PubMed

Mathieu, Romain; Vartolomei, Mihai D; Mbeutcha, Aurélie; Karakiewicz, Pierre I; Briganti, Alberto; Roupret, Morgan; Shariat, Shahrokh F

2016-08-01

The aim of this review was to provide an overview of current biomarkers and risk stratification models in urothelial cancer of the upper urinary tract (UTUC). A non-systematic Medline/PubMed literature search was performed using the terms "biomarkers", "preoperative models", "postoperative models", "risk stratification", together with "upper tract urothelial carcinoma". Original articles published between January 2003 and August 2015 were included based on their clinical relevance. Additional references were collected by cross referencing the bibliography of the selected articles. Various promising predictive and prognostic biomarkers have been identified in UTUC thanks to the increasing knowledge of the different biological pathways involved in UTUC tumorigenesis. These biomarkers may help identify tumors with aggressive biology and worse outcomes. Current tools aim at predicting muscle invasive or non-organ confined disease, renal failure after radical nephroureterectomy and survival outcomes. These models are still mainly based on imaging and clinicopathological feature and none has integrated biomarkers. Risk stratification in UTUC is still suboptimal, especially in the preoperative setting due to current limitations in staging and grading. Identification of novel biomarkers and external validation of current prognostic models may help improve risk stratification to allow evidence-based counselling for kidney-sparing approaches, perioperative chemotherapy and/or risk-based surveillance. Despite growing understanding of the biology underlying UTUC, management of this disease remains difficult due to the lack of validated biomarkers and the limitations of current predictive and prognostic tools. Further efforts and collaborations are necessaryry to allow their integration in daily practice.

Developing an Integrated Treatment Pathway for a Post-Coronary Artery Bypass Grating (CABG) Geriatric Patient with Comorbid Hypertension and Type 1 Diabetes Mellitus for Treating Acute Hypoglycemia and Electrolyte Imbalance.

PubMed

Naqvi, Atta Abbas; Shah, Amna; Ahmad, Rizwan; Ahmad, Niyaz

2017-01-01

The ailments afflicting the elderly population is a well-defined specialty of medicine. It calls for an immaculately designed health-care plan to treat diseases in geriatrics. For chronic illnesses such as diabetes mellitus (DM), coronary heart disease, and hypertension (HTN), they require proper management throughout the rest of patient's life. An integrated treatment pathway helps in treatment decision-making and improving standards of health care for the patient. This case describes an exclusive clinical pharmacist-driven designing of an integrated treatment pathway for a post-coronary artery bypass grafting (CABG) geriatric male patient with DM type I and HTN for the treatment of hypoglycemia and electrolyte imbalance. The treatment begins addressing the chief complaints which were vomiting and unconsciousness. Biochemical screening is essential to establish a diagnosis of electrolyte imbalance along with blood glucose level after which the integrated pathway defines the treatment course. This individualized treatment pathway provides an outline of the course of treatment of acute hypoglycemia, electrolyte imbalance as well as some unconfirmed diagnosis, namely, acute coronary syndrome and respiratory tract infection for a post-CABG geriatric patient with HTN and type 1 DM. The eligibility criterion for patients to be treated according to treatment pathway is to fall in the defined category.

Recommendation Systems for Geoscience Data Portals Built by Analyzing Usage Patterns

NASA Astrophysics Data System (ADS)

Crosby, C.; Nandigam, V.; Baru, C.

2009-04-01

Since its launch five years ago, the National Science Foundation-funded GEON Project (www.geongrid.org) has been providing access to a variety of geoscience data sets such as geologic maps and other geographic information system (GIS)-oriented data, paleontologic databases, gravity and magnetics data and LiDAR topography via its online portal interface. In addition to data, the GEON Portal also provides web-based tools and other resources that enable users to process and interact with data. Examples of these tools include functions to dynamically map and integrate GIS data, compute synthetic seismograms, and to produce custom digital elevation models (DEMs) with user defined parameters such as resolution. The GEON portal built on the Gridsphere-portal framework allows us to capture user interaction with the system. In addition to the site access statistics captured by tools like Google Analystics which capture hits per unit time, search key words, operating systems, browsers, and referring sites, we also record additional statistics such as which data sets are being downloaded and in what formats, processing parameters, and navigation pathways through the portal. With over four years of data now available from the GEON Portal, this record of usage is a rich resource for exploring how earth scientists discover and utilize online data sets. Furthermore, we propose that this data could ultimately be harnessed to optimize the way users interact with the data portal, design intelligent processing and data management systems, and to make recommendations on algorithm settings and other available relevant data. The paradigm of integrating popular and commonly used patterns to make recommendations to a user is well established in the world of e-commerce where users receive suggestions on books, music and other products that they may find interesting based on their website browsing and purchasing history, as well as the patterns of fellow users who have made similar selections. However, this paradigm has not yet been explored for geoscience data portals. In this presentation we will present an initial analysis of user interaction and access statistics for the GEON OpenTopography LiDAR data distribution and processing system to illustrate what they reveal about user's spatial and temporal data access patterns, data processing parameter selections, and pathways through the data portal. We also demonstrate what these usage statistics can illustrate about aspects of the data sets that are of greatest interest. Finally, we explore how these usage statistics could be used to improve the user's experience in the data portal and to optimize how data access interfaces and tools are designed and implemented.

Rhizoma Dioscoreae extract protects against alveolar bone loss by regulating the cell cycle: A predictive study based on the protein‑protein interaction network.

PubMed

Zhang, Zhi-Guo; Song, Chang-Heng; Zhang, Fang-Zhen; Chen, Yan-Jing; Xiang, Li-Hua; Xiao, Gary Guishan; Ju, Da-Hong

2016-06-01

Rhizoma Dioscoreae extract (RDE) exhibits a protective effect on alveolar bone loss in ovariectomized (OVX) rats. The aim of this study was to predict the pathways or targets that are regulated by RDE, by re‑assessing our previously reported data and conducting a protein‑protein interaction (PPI) network analysis. In total, 383 differentially expressed genes (≥3‑fold) between alveolar bone samples from the RDE and OVX group rats were identified, and a PPI network was constructed based on these genes. Furthermore, four molecular clusters (A‑D) in the PPI network with the smallest P‑values were detected by molecular complex detection (MCODE) algorithm. Using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) tools, two molecular clusters (A and B) were enriched for biological process in Gene Ontology (GO). Only cluster A was associated with biological pathways in the IPA database. GO and pathway analysis results showed that cluster A, associated with cell cycle regulation, was the most important molecular cluster in the PPI network. In addition, cyclin‑dependent kinase 1 (CDK1) may be a key molecule achieving the cell‑cycle‑regulatory function of cluster A. From the PPI network analysis, it was predicted that delayed cell cycle progression in excessive alveolar bone remodeling via downregulation of CDK1 may be another mechanism underling the anti‑osteopenic effect of RDE on alveolar bone.

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Gujarat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Tamil Nadu

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Tamil Nadu is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Rajasthan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Andhra Pradesh

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Karnataka

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Regional Study: Maharashtra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cochran, Jaquelin M; Palchak, Joseph D; Ehlen, Annaliese K

This chapter on Andhra Pradesh is one of six state chapters included in Appendix C of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study). The objective of the state chapters is to provide modeling assumptions, results, and next steps to use and improve the model specific to each state. The model has inherent uncertainties, particularly in how the intrastate transmission network and RE generation projects will develop (e.g., locations, capacities). The model also does not include information on contracts or must-run status of particular plantsmore » for reliability purposes. By providing details on the higher spatial resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.'« less

Health Impact Modelling of Active Travel Visions for England and Wales Using an Integrated Transport and Health Impact Modelling Tool (ITHIM)

PubMed Central

Woodcock, James; Givoni, Moshe; Morgan, Andrei Scott

2013-01-01

Background Achieving health benefits while reducing greenhouse gas emissions from transport offers a potential policy win-win; the magnitude of potential benefits, however, is likely to vary. This study uses an Integrated Transport and Health Impact Modelling tool (ITHIM) to evaluate the health and environmental impacts of high walking and cycling transport scenarios for English and Welsh urban areas outside London. Methods Three scenarios with increased walking and cycling and lower car use were generated based upon the Visions 2030 Walking and Cycling project. Changes to carbon dioxide emissions were estimated by environmental modelling. Health impact assessment modelling was used to estimate changes in Disability Adjusted Life Years (DALYs) resulting from changes in exposure to air pollution, road traffic injury risk, and physical activity. We compare the findings of the model with results generated using the World Health Organization's Health Economic Assessment of Transport (HEAT) tools. Results This study found considerable reductions in disease burden under all three scenarios, with the largest health benefits attributed to reductions in ischemic heart disease. The pathways that produced the largest benefits were, in order, physical activity, road traffic injuries, and air pollution. The choice of dose response relationship for physical activity had a large impact on the size of the benefits. Modelling the impact on all-cause mortality rather than through individual diseases suggested larger benefits. Using the best available evidence we found fewer road traffic injuries for all scenarios compared with baseline but alternative assumptions suggested potential increases. Conclusions Methods to estimate the health impacts from transport related physical activity and injury risk are in their infancy; this study has demonstrated an integration of transport and health impact modelling approaches. The findings add to the case for a move from car transport to walking and cycling, and have implications for empirical and modelling research. PMID:23326315

Health impact modelling of active travel visions for England and Wales using an Integrated Transport and Health Impact Modelling Tool (ITHIM).

PubMed

Woodcock, James; Givoni, Moshe; Morgan, Andrei Scott

2013-01-01

Achieving health benefits while reducing greenhouse gas emissions from transport offers a potential policy win-win; the magnitude of potential benefits, however, is likely to vary. This study uses an Integrated Transport and Health Impact Modelling tool (ITHIM) to evaluate the health and environmental impacts of high walking and cycling transport scenarios for English and Welsh urban areas outside London. Three scenarios with increased walking and cycling and lower car use were generated based upon the Visions 2030 Walking and Cycling project. Changes to carbon dioxide emissions were estimated by environmental modelling. Health impact assessment modelling was used to estimate changes in Disability Adjusted Life Years (DALYs) resulting from changes in exposure to air pollution, road traffic injury risk, and physical activity. We compare the findings of the model with results generated using the World Health Organization's Health Economic Assessment of Transport (HEAT) tools. This study found considerable reductions in disease burden under all three scenarios, with the largest health benefits attributed to reductions in ischemic heart disease. The pathways that produced the largest benefits were, in order, physical activity, road traffic injuries, and air pollution. The choice of dose response relationship for physical activity had a large impact on the size of the benefits. Modelling the impact on all-cause mortality rather than through individual diseases suggested larger benefits. Using the best available evidence we found fewer road traffic injuries for all scenarios compared with baseline but alternative assumptions suggested potential increases. Methods to estimate the health impacts from transport related physical activity and injury risk are in their infancy; this study has demonstrated an integration of transport and health impact modelling approaches. The findings add to the case for a move from car transport to walking and cycling, and have implications for empirical and modelling research.

PathNER: a tool for systematic identification of biological pathway mentions in the literature

PubMed Central

2013-01-01

Background Biological pathways are central to many biomedical studies and are frequently discussed in the literature. Several curated databases have been established to collate the knowledge of molecular processes constituting pathways. Yet, there has been little focus on enabling systematic detection of pathway mentions in the literature. Results We developed a tool, named PathNER (Pathway Named Entity Recognition), for the systematic identification of pathway mentions in the literature. PathNER is based on soft dictionary matching and rules, with the dictionary generated from public pathway databases. The rules utilise general pathway-specific keywords, syntactic information and gene/protein mentions. Detection results from both components are merged. On a gold-standard corpus, PathNER achieved an F1-score of 84%. To illustrate its potential, we applied PathNER on a collection of articles related to Alzheimer's disease to identify associated pathways, highlighting cases that can complement an existing manually curated knowledgebase. Conclusions In contrast to existing text-mining efforts that target the automatic reconstruction of pathway details from molecular interactions mentioned in the literature, PathNER focuses on identifying specific named pathway mentions. These mentions can be used to support large-scale curation and pathway-related systems biology applications, as demonstrated in the example of Alzheimer's disease. PathNER is implemented in Java and made freely available online at http://sourceforge.net/projects/pathner/. PMID:24555844

Federated Search Tools in Fusion Centers: Bridging Databases in the Information Sharing Environment

DTIC Science & Technology

2012-09-01

considerable variation in how fusion centers plan for, gather requirements, select and acquire federated search tools to bridge disparate databases...centers, when considering integrating federated search tools; by evaluating the importance of the planning, requirements gathering, selection and...acquisition processes for integrating federated search tools; by acknowledging the challenges faced by some fusion centers during these integration processes

Software Process Automation: Experiences from the Trenches.

DTIC Science & Technology

1996-07-01

Integration of problem database Weaver tions) J Process WordPerfect, All-in-One, Oracle, CM Integration of tools Weaver System K Process Framemaker , CM...handle change requests and problem reports. * Autoplan, a project management tool * Framemaker , a document processing system * Worldview, a document...Cadre, Team Work, FrameMaker , some- thing for requirements traceability, their own homegrown scheduling tool, and their own homegrown tool integrator

The adverse outcome pathway: A multifaceted framework supporting 21st century toxicology

EPA Science Inventory

The adverse outcome pathway (AOP) framework serves as a knowledge assembly, interpretation, and communication tool designed to support the translation of pathway-specific mechanistic data into responses relevant to assessing and managing risks of chemicals to human health and the...

Resilience to the contralateral visual field bias as a window into object representations

PubMed Central

Garcea, Frank E.; Kristensen, Stephanie; Almeida, Jorge; Mahon, Bradford Z.

2016-01-01

Viewing images of manipulable objects elicits differential blood oxygen level-dependent (BOLD) contrast across parietal and dorsal occipital areas of the human brain that support object-directed reaching, grasping, and complex object manipulation. However, it is unknown which object-selective regions of parietal cortex receive their principal inputs from the ventral object-processing pathway and which receive their inputs from the dorsal object-processing pathway. Parietal areas that receive their inputs from the ventral visual pathway, rather than from the dorsal stream, will have inputs that are already filtered through object categorization and identification processes. This predicts that parietal regions that receive inputs from the ventral visual pathway should exhibit object-selective responses that are resilient to contralateral visual field biases. To test this hypothesis, adult participants viewed images of tools and animals that were presented to the left or right visual fields during functional magnetic resonance imaging (fMRI). We found that the left inferior parietal lobule showed robust tool preferences independently of the visual field in which tool stimuli were presented. In contrast, a region in posterior parietal/dorsal occipital cortex in the right hemisphere exhibited an interaction between visual field and category: tool-preferences were strongest contralateral to the stimulus. These findings suggest that action knowledge accessed in the left inferior parietal lobule operates over inputs that are abstracted from the visual input and contingent on analysis by the ventral visual pathway, consistent with its putative role in supporting object manipulation knowledge. PMID:27160998

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

PubMed Central

Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

PubMed

Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

2014-01-01

Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

Case Studies in Environment Integration

DTIC Science & Technology

1991-12-01

such as CADRE Teamwork and Frame Technology FrameMaker , are integrated. Future plans include integrating additional software development tools into...Pictures, Sabre C, and Interleaf or FrameMaker . Cad- re Technologies has announced integration agreements with Saber C and Pansophic, as well as offering...access to the Interleaf and FrameMaker documentation tools. While some of the current agreements between vendors to create tool coalitions are

Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

PubMed

Bohler, Anwesha; Eijssen, Lars M T; van Iersel, Martijn P; Leemans, Christ; Willighagen, Egon L; Kutmon, Martina; Jaillard, Magali; Evelo, Chris T

2015-08-23

Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers. We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data. PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

RoBuST: an integrated genomics resource for the root and bulb crop families Apiaceae and Alliaceae

PubMed Central

2010-01-01

Background Root and bulb vegetables (RBV) include carrots, celeriac (root celery), parsnips (Apiaceae), onions, garlic, and leek (Alliaceae)—food crops grown globally and consumed worldwide. Few data analysis platforms are currently available where data collection, annotation and integration initiatives are focused on RBV plant groups. Scientists working on RBV include breeders, geneticists, taxonomists, plant pathologists, and plant physiologists who use genomic data for a wide range of activities including the development of molecular genetic maps, delineation of taxonomic relationships, and investigation of molecular aspects of gene expression in biochemical pathways and disease responses. With genomic data coming from such diverse areas of plant science, availability of a community resource focused on these RBV data types would be of great interest to this scientific community. Description The RoBuST database has been developed to initiate a platform for collecting and organizing genomic information useful for RBV researchers. The current release of RoBuST contains genomics data for 294 Alliaceae and 816 Apiaceae plant species and has the following features: (1) comprehensive sequence annotations of 3663 genes 5959 RNAs, 22,723 ESTs and 11,438 regulatory sequence elements from Apiaceae and Alliaceae plant families; (2) graphical tools for visualization and analysis of sequence data; (3) access to traits, biosynthetic pathways, genetic linkage maps and molecular taxonomy data associated with Alliaceae and Apiaceae plants; and (4) comprehensive plant splice signal repository of 659,369 splice signals collected from 6015 plant species for comparative analysis of plant splicing patterns. Conclusions RoBuST, available at http://robust.genome.com, provides an integrated platform for researchers to effortlessly explore and analyze genomic data associated with root and bulb vegetables. PMID:20691054

Evolving the Principles and Practice of Validation for New Alternative Approaches to Toxicity Testing.

PubMed

Whelan, Maurice; Eskes, Chantra

Validation is essential for the translation of newly developed alternative approaches to animal testing into tools and solutions suitable for regulatory applications. Formal approaches to validation have emerged over the past 20 years or so and although they have helped greatly to progress the field, it is essential that the principles and practice underpinning validation continue to evolve to keep pace with scientific progress. The modular approach to validation should be exploited to encourage more innovation and flexibility in study design and to increase efficiency in filling data gaps. With the focus now on integrated approaches to testing and assessment that are based on toxicological knowledge captured as adverse outcome pathways, and which incorporate the latest in vitro and computational methods, validation needs to adapt to ensure it adds value rather than hinders progress. Validation needs to be pursued both at the method level, to characterise the performance of in vitro methods in relation their ability to detect any association of a chemical with a particular pathway or key toxicological event, and at the methodological level, to assess how integrated approaches can predict toxicological endpoints relevant for regulatory decision making. To facilitate this, more emphasis needs to be given to the development of performance standards that can be applied to classes of methods and integrated approaches that provide similar information. Moreover, the challenge of selecting the right reference chemicals to support validation needs to be addressed more systematically, consistently and in a manner that better reflects the state of the science. Above all however, validation requires true partnership between the development and user communities of alternative methods and the appropriate investment of resources.

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network.

PubMed

Gloaguen, Pauline; Bournais, Sylvain; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Tardif, Marianne; Kuntz, Marcel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves; Curien, Gilles

2017-06-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis ( Arabidopsis thaliana ) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. © 2017 American Society of Plant Biologists. All Rights Reserved.

Health care multidisciplinary teams: The sociotechnical approach for an integrated system-wide perspective.

PubMed

Marsilio, Marta; Torbica, Aleksandra; Villa, Stefano

The current literature on the enabling conditions of multidisciplinary teams focuses on the singular dimensions of the organizations (i.e., human resources, clinical pathways, objects) without shedding light on to the way in which these organizational factors interact and mutually influence one another. Drawing on a system perspective of organizations, the authors analyze the organizational patterns that promote and support multidisciplinary teams and how they interrelate and interact to enforce the organization work system. The authors develop a modified sociotechnical system (STS) model to understand how the two dimensions of technical (devices/tools, layout/organization of space, core process standardization) and social (organizational structure, management of human resources and operations) can facilitate the implementation of multidisciplinary teams in health care. The study conducts an empirical analysis based on a sample of hospital adopters of transcatheter aortic valve implantation using the revised STS model. The modified STS model applied to the case studies improves our understanding of the critical implementation factors of a multidisciplinary approach and the importance of coordinating radical changes in the technical and the social subsystems of health care organizations. The analysis informs that the multidisciplinary effort is not a sequential process and that the interplay between the two subsystems needs to be managed efficaciously as an integrated organizational whole to deliver the goals set. Hospital managers must place equal focus on the closely interrelated technical and social dimensions by investing in (a) shared layouts and spaces that cross the boundaries of the specialized health care units, (b) standardization of the core processes through the implementation of local clinical pathways, (c) structured knowledge management mechanisms, (d) the creation of clinical directorates, and (e) the design of a planning and budgeting system that integrates the multidisciplinary concept.

BMDExpress Data Viewer: A Visualization Tool to Analyze ...

EPA Pesticide Factsheets

Regulatory agencies increasingly apply benchmark dose (BMD) modeling to determine points of departure in human risk assessments. BMDExpress applies BMD modeling to transcriptomics datasets and groups genes to biological processes and pathways for rapid assessment of doses at which biological perturbations occur. However, graphing and analytical capabilities within BMDExpress are limited, and the analysis of output files is challenging. We developed a web-based application, BMDExpress Data Viewer, for visualization and graphical analyses of BMDExpress output files. The software application consists of two main components: ‘Summary Visualization Tools’ and ‘Dataset Exploratory Tools’. We demonstrate through two case studies that the ‘Summary Visualization Tools’ can be used to examine and assess the distributions of probe and pathway BMD outputs, as well as derive a potential regulatory BMD through the modes or means of the distributions. The ‘Functional Enrichment Analysis’ tool presents biological processes in a two-dimensional bubble chart view. By applying filters of pathway enrichment p-value and minimum number of significant genes, we showed that the Functional Enrichment Analysis tool can be applied to select pathways that are potentially sensitive to chemical perturbations. The ‘Multiple Dataset Comparison’ tool enables comparison of BMDs across multiple experiments (e.g., across time points, tissues, or organisms, etc.). The ‘BMDL-BM

ReNE: A Cytoscape Plugin for Regulatory Network Enhancement

PubMed Central

Politano, Gianfranco; Benso, Alfredo; Savino, Alessandro; Di Carlo, Stefano

2014-01-01

One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by ReNE is exportable in multiple formats for further analysis via third party applications. ReNE can be freely installed from the Cytoscape App Store (http://apps.cytoscape.org/apps/rene) and the full source code is freely available for download through a SVN repository accessible at http://www.sysbio.polito.it/tools_svn/BioInformatics/Rene/releases/. ReNE enhances a network by only integrating data from public repositories, without any inference or prediction. The reliability of the introduced interactions only depends on the reliability of the source data, which is out of control of ReNe developers. PMID:25541727

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

Protecting and Diversifying the Germline

PubMed Central

Gleason, Ryan J.; Anand, Amit; Kai, Toshie; Chen, Xin

2018-01-01

Gametogenesis represents the most dramatic cellular differentiation pathways in both female and male flies. At the genome level, meiosis ensures that diploid germ cells become haploid gametes. At the epigenome level, extensive changes are required to turn on and shut off gene expression in a precise spatiotemporally controlled manner. Research applying conventional molecular genetics and cell biology, in combination with rapidly advancing genomic tools have helped us to investigate (1) how germ cells maintain lineage specificity throughout their adult reproductive lifetime; (2) what molecular mechanisms ensure proper oogenesis and spermatogenesis, as well as protect genome integrity of the germline; (3) how signaling pathways contribute to germline-soma communication; and (4) if such communication is important. In this chapter, we highlight recent discoveries that have improved our understanding of these questions. On the other hand, restarting a new life cycle upon fertilization is a unique challenge faced by gametes, raising questions that involve intergenerational and transgenerational epigenetic inheritance. Therefore, we also discuss new developments that link changes during gametogenesis to early embryonic development—a rapidly growing field that promises to bring more understanding to some fundamental questions regarding metazoan development. PMID:29378808

Application of the adverse outcome pathway framework - advances and challenges

EPA Science Inventory

The adverse outcome pathway (AOP) framework, while not new in concept, has gained attention in recent years as a set of organizing principles and tools that can help facilitate greater use of mechanistic or pathway-based data in risk assessment and regulatory decision-making. Reg...

Implementing Guided Pathways: Tips and Tools

ERIC Educational Resources Information Center

Bailey, Thomas; Jaggars, Shanna Smith; Jenkins, Davis

2015-01-01

A growing number of community colleges and four-year universities are seeking to improve student outcomes by redesigning academic programs and student support services following the guided pathways approach. These institutions are mapping out highly structured, educationally coherent program pathways for students to follow by starting with the end…

Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Choi, Inhee; Sarker, Malabika; Talcott, Carolyn

2010-01-01

We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage this data in order to move from a hit to a lead to a clinical candidate and potentially a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged and are herein reviewed. We suggest these computational approaches should be more optimally integrated in a workflow with experimental approaches to accelerate TB drug discovery. PMID:21129975

IntegromeDB: an integrated system and biological search engine.

PubMed

Baitaluk, Michael; Kozhenkov, Sergey; Dubinina, Yulia; Ponomarenko, Julia

2012-01-19

With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.

Genomicus 2018: karyotype evolutionary trees and on-the-fly synteny computing.

PubMed

Nguyen, Nga Thi Thuy; Vincens, Pierre; Roest Crollius, Hugues; Louis, Alexandra

2018-01-04

Since 2010, the Genomicus web server is available online at http://genomicus.biologie.ens.fr/genomicus. This graphical browser provides access to comparative genomic analyses in four different phyla (Vertebrate, Plants, Fungi, and non vertebrate Metazoans). Users can analyse genomic information from extant species, as well as ancestral gene content and gene order for vertebrates and flowering plants, in an integrated evolutionary context. New analyses and visualization tools have recently been implemented in Genomicus Vertebrate. Karyotype structures from several genomes can now be compared along an evolutionary pathway (Multi-KaryotypeView), and synteny blocks can be computed and visualized between any two genomes (PhylDiagView). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Decker, A.D.; Kuuskraa, V.A.; Klawitter, A.L.

Recurrent basement faulting is the primary controlling mechanism for aligning and compartmentalizing upper Cretaceous aged tight gas reservoirs of the San Juan and Piceance Basins. Northwest trending structural lineaments that formed in conjunction with the Uncompahgre Highlands have profoundly influenced sedimentation trends and created boundaries for gas migration; sealing and compartmentalizing sedimentary packages in both basins. Fractures which formed over the structural lineaments provide permeability pathways which allowing gas recovery from otherwise tight gas reservoirs. Structural alignments and associated reservoir compartments have been accurately targeted by integrating advanced remote sensing imagery, high resolution aeromagnetics, seismic interpretation, stratigraphic mapping and dynamicmore » structural modelling. This unifying methodology is a powerful tool for exploration geologists and is also a systematic approach to tight gas resource assessment in frontier basins.« less

Applications of capillary electrophoresis in characterizing recombinant protein therapeutics.

PubMed

Zhao, Shuai Sherry; Chen, David D Y

2014-01-01

The use of recombinant protein for therapeutic applications has increased significantly in the last three decades. The heterogeneity of these proteins, often caused by the complex biosynthesis pathways and the subsequent PTMs, poses a challenge for drug characterization to ensure its safety, quality, integrity, and efficacy. CE, with its simple instrumentation, superior separation efficiency, small sample consumption, and short analysis time, is a well-suited analytical tool for therapeutic protein characterization. Different separation modes, including CIEF, SDS-CGE, CZE, and CE-MS, provide complementary information of the proteins. The CE applications for recombinant therapeutic proteins from the year 2000 to June 2013 are reviewed and technical concerns are discussed in this article. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The transformative potential of realigning Agape and Eros in the continued development of nursing's role.

PubMed

Valentine-Maher, Sarah

2008-01-01

Nursing may reach its highest potential when there is an integration of Agape love and Eros love within nursing. That is, an ontological framework from which service and giving of the self are aligned with creative power and development of the self. The concepts of Eros and Agape give the nurse tools to understand the contradictions of nursing and to find increased purpose, peace, and strength in her own work. For the field of nursing, the concepts of Eros and Agape offer a pathway to redefining a heroic role of service. Such a redefined role may help nursing become increasingly responsive to the true reality of human needs, from direct contact with a patient to involvement in international health.

Surgical Technology Integration with Tools for Cognitive Human Factors (STITCH)

DTIC Science & Technology

2007-10-01

Award Number: W81XWH-06-1-0761 TITLE: Surgical Technology Integration with Tools for Cognitive Human Factors (STITCH) PRINCIPAL INVESTIGATOR...23 JUL 2007 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Surgical Technology Integration with Tools for Cognitive Human Factors (STITCH) 5b. GRANT...by considering cognitive and environmental factors such as mental workload, stress, situation awareness, and level of comfort with complex tools

A Method to Evaluate Critical Factors for Successful Implementation of Clinical Pathways.

PubMed

Dong, W; Huang, Z

2015-01-01

Clinical pathways (CPs) have been viewed as a multidisciplinary tool to improve the quality and efficiency of evidence-based care. Despite widespread enthusiasm for CPs, research has shown that many CP initiatives are unsuccessful. To this end, this study provides a methodology to evaluate critical success factors (CSFs) that can aid healthcare organizations to achieve successful CP implementation. This study presents a new approach to evaluate CP implementation CSFs, with the aims being: (1) to identify CSFs for implementation of CPs through a comprehensive literature review and interviews with collaborative experts; (2) to use a filed study data with a robust fuzzy DEMATEL (the decision making trial and evaluation laboratory) approach to visualize the structure of complicated causal relationships between CSFs and obtain the influence level of these factors. The filed study data is provided by ten clinical experts of a Chinese hospital. 23 identified CSF factors which are initially identified through a review of the literature and interviews with collaborative experts. Then, a number of direct and indirect relationships are derived from the data such that different perceptions can be integrated into a compromised cause and effect model of CP implementation. The results indicate that the proposed approach can systematically evaluate CSFs and realize the importance of each factor such that the most common causes of failure of CP implementation could be eliminated or avoided. Therefore, the tool proposed would help healthcare organizations to manage CP implementation in a more effective and proactive way.

Recent advances and state-of-the-art strategies in strain and process engineering for biobutanol production by Clostridium acetobutylicum.

PubMed

Xue, Chuang; Zhao, Jingbo; Chen, Lijie; Yang, Shang-Tian; Bai, Fengwu

Butanol as an advanced biofuel has gained great attention due to its environmental benefits and superior properties compared to ethanol. However, the cost of biobutanol production via conventional acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum is not economically competitive, which has hampered its industrial application. The strain performance and downstream process greatly impact the economics of biobutanol production. Although various engineered strains with carefully orchestrated metabolic and sporulation-specific pathways have been developed, none of them is ideal for industrial biobutanol production. For further strain improvement, it is necessary to develop advanced genome editing tools and a deep understanding of cellular functioning of genes in metabolic and regulatory pathways. Processes with integrated product recovery can increase fermentation productivity by continuously removing inhibitory products while generating butanol (ABE) in a concentrated solution. In this review, we provide an overview of recent advances in C. acetobutylicum strain engineering and process development focusing on in situ product recovery. With deep understanding of systematic cellular bioinformatics, the exploration of state-of-the-art genome editing tools such as CRISPR-Cas for targeted gene knock-out and knock-in would play a vital role in Clostridium cell engineering for biobutanol production. Developing advanced hybrid separation processes for in situ butanol recovery, which will be discussed with a detailed comparison of advantages and disadvantages of various recovery techniques, is also imperative to the economical development of biobutanol. Copyright © 2017 Elsevier Inc. All rights reserved.

Obesity genetics in mouse and human: back and forth, and back again

PubMed Central

Yazdi, Fereshteh T.; Clee, Susanne M.

2015-01-01

Obesity is a major public health concern. This condition results from a constant and complex interplay between predisposing genes and environmental stimuli. Current attempts to manage obesity have been moderately effective and a better understanding of the etiology of obesity is required for the development of more successful and personalized prevention and treatment options. To that effect, mouse models have been an essential tool in expanding our understanding of obesity, due to the availability of their complete genome sequence, genetically identified and defined strains, various tools for genetic manipulation and the accessibility of target tissues for obesity that are not easily attainable from humans. Our knowledge of monogenic obesity in humans greatly benefited from the mouse obesity genetics field. Genes underlying highly penetrant forms of monogenic obesity are part of the leptin-melanocortin pathway in the hypothalamus. Recently, hypothesis-generating genome-wide association studies for polygenic obesity traits in humans have led to the identification of 119 common gene variants with modest effect, most of them having an unknown function. These discoveries have led to novel animal models and have illuminated new biologic pathways. Integrated mouse-human genetic approaches have firmly established new obesity candidate genes. Innovative strategies recently developed by scientists are described in this review to accelerate the identification of causal genes and deepen our understanding of obesity etiology. An exhaustive dissection of the molecular roots of obesity may ultimately help to tackle the growing obesity epidemic worldwide. PMID:25825681

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

PubMed

Antanaviciute, Agne; Watson, Christopher M; Harrison, Sally M; Lascelles, Carolina; Crinnion, Laura; Markham, Alexander F; Bonthron, David T; Carr, Ian M

2015-12-01

Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. Supplementary data are available at Bioinformatics online. umaan@leeds.ac.uk. © The Author 2015. Published by Oxford University Press.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Yitan; Xu, Yanxun; Helseth, Donald L.

Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood modelmore » derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes “Prior interaction map + TCGA data → Posterior interaction map.” Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.« less

An Integrative Analysis of Preeclampsia Based on the Construction of an Extended Composite Network Featuring Protein-Protein Physical Interactions and Transcriptional Relationships

PubMed Central

Vaiman, Daniel; Miralles, Francisco

2016-01-01

Preeclampsia (PE) is a pregnancy disorder defined by hypertension and proteinuria. This disease remains a major cause of maternal and fetal morbidity and mortality. Defective placentation is generally described as being at the root of the disease. The characterization of the transcriptome signature of the preeclamptic placenta has allowed to identify differentially expressed genes (DEGs). However, we still lack a detailed knowledge on how these DEGs impact the function of the placenta. The tools of network biology offer a methodology to explore complex diseases at a systems level. In this study we performed a cross-platform meta-analysis of seven publically available gene expression datasets comparing non-pathological and preeclamptic placentas. Using the rank product algorithm we identified a total of 369 DEGs consistently modified in PE. The DEGs were used as seeds to build both an extended physical protein-protein interactions network and a transcription factors regulatory network. Topological and clustering analysis was conducted to analyze the connectivity properties of the networks. Finally both networks were merged into a composite network which presents an integrated view of the regulatory pathways involved in preeclampsia and the crosstalk between them. This network is a useful tool to explore the relationship between the DEGs and enable hypothesis generation for functional experimentation. PMID:27802351

Biological and mechanical interplay at the Macro- and Microscales Modulates the Cell-Niche Fate.

PubMed

Sarig, Udi; Sarig, Hadar; Gora, Aleksander; Krishnamoorthi, Muthu Kumar; Au-Yeung, Gigi Chi Ting; de-Berardinis, Elio; Chaw, Su Yin; Mhaisalkar, Priyadarshini; Bogireddi, Hanumakumar; Ramakrishna, Seeram; Boey, Freddy Yin Chiang; Venkatraman, Subbu S; Machluf, Marcelle

2018-03-02

Tissue development, regeneration, or de-novo tissue engineering in-vitro, are based on reciprocal cell-niche interactions. Early tissue formation mechanisms, however, remain largely unknown given complex in-vivo multifactoriality, and limited tools to effectively characterize and correlate specific micro-scaled bio-mechanical interplay. We developed a unique model system, based on decellularized porcine cardiac extracellular matrices (pcECMs)-as representative natural soft-tissue biomaterial-to study a spectrum of common cell-niche interactions. Model monocultures and 1:1 co-cultures on the pcECM of human umbilical vein endothelial cells (HUVECs) and human mesenchymal stem cells (hMSCs) were mechano-biologically characterized using macro- (Instron), and micro- (AFM) mechanical testing, histology, SEM and molecular biology aspects using RT-PCR arrays. The obtained data was analyzed using developed statistics, principal component and gene-set analyses tools. Our results indicated biomechanical cell-type dependency, bi-modal elasticity distributions at the micron cell-ECM interaction level, and corresponding differing gene expression profiles. We further show that hMSCs remodel the ECM, HUVECs enable ECM tissue-specific recognition, and their co-cultures synergistically contribute to tissue integration-mimicking conserved developmental pathways. We also suggest novel quantifiable measures as indicators of tissue assembly and integration. This work may benefit basic and translational research in materials science, developmental biology, tissue engineering, regenerative medicine and cancer biomechanics.

Human health and wellbeing in environmental impact assessment in New South Wales, Australia: Auditing health impacts within environmental assessments of major projects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, Patrick J., E-mail: patrick.harris@unsw.edu.a; Harris, Elizabeth, E-mail: e.harris@unsw.edu.a; Thompson, Susan, E-mail: s.thompson@unsw.edu.a

Internationally the inclusion of health within environmental impact assessment (EIA) has been shown to be limited. While Australian EIA documentation has not been studied empirically to date, deficiencies in practice have been documented. This research developed an audit tool to undertake a qualitative descriptive analysis of 22 Major Project EAs in New South Wales, Australia. Results showed that health and wellbeing impacts were not considered explicitly. They were, however, included indirectly in the identification of traditional public health exposures associated with the physical environment and to a lesser extent the inclusion of social and economic impacts. However, no health datamore » was used to inform any of the assessments, there was no reference to causal pathways between exposures or determinants and physical or mental health effects, and there was no inclusion of the differential distribution of exposures or health impacts on different populations. The results add conceptually and practically to the long standing integration debate, showing that health is in a position to add value to the EIA process as an explicit part of standard environmental, social and economic considerations. However, to overcome the consistently documented barriers to integrating health in EIA, capacity must be developed amongst EIA professionals, led by the health sector, to progress health related knowledge and tools.« less

Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and Bioassays

PubMed Central

Shen, Mingyun; Tian, Sheng; Pan, Peichen; Sun, Huiyong; Li, Dan; Li, Youyong; Zhou, Hefeng; Li, Chuwen; Lee, Simon Ming-Yuen; Hou, Tingjun

2015-01-01

Rho-associated kinases (ROCKs) have been regarded as promising drug targets for the treatment of cardiovascular diseases, nervous system diseases and cancers. In this study, a novel integrated virtual screening protocol by combining molecular docking and pharmacophore mapping based on multiple ROCK1 crystal structures was utilized to screen the ChemBridge database for discovering potential inhibitors of ROCK1. Among the 38 tested compounds, seven of them exhibited significant inhibitory activities of ROCK1 (IC50 < 10 μM) and the most potent one (compound TS-f22) with the novel scaffold of 4-Phenyl-1H-pyrrolo [2,3-b] pyridine had an IC50 of 480 nM. Then, the structure-activity relationships of 41 analogues of TS-f22 were examined. Two potent inhibitors were proven effective in inhibiting the phosphorylation of the downstream target in the ROCK signaling pathway in vitro and protecting atorvastatin-induced cerebral hemorrhage in vivo. The high hit rate (28.95%) suggested that the integrated virtual screening strategy was quite reliable and could be used as a powerful tool for identifying promising active compounds for targets of interest. PMID:26568382

Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and Bioassays.

PubMed

Shen, Mingyun; Tian, Sheng; Pan, Peichen; Sun, Huiyong; Li, Dan; Li, Youyong; Zhou, Hefeng; Li, Chuwen; Lee, Simon Ming-Yuen; Hou, Tingjun

2015-11-16

Rho-associated kinases (ROCKs) have been regarded as promising drug targets for the treatment of cardiovascular diseases, nervous system diseases and cancers. In this study, a novel integrated virtual screening protocol by combining molecular docking and pharmacophore mapping based on multiple ROCK1 crystal structures was utilized to screen the ChemBridge database for discovering potential inhibitors of ROCK1. Among the 38 tested compounds, seven of them exhibited significant inhibitory activities of ROCK1 (IC50 < 10 μM) and the most potent one (compound TS-f22) with the novel scaffold of 4-Phenyl-1H-pyrrolo [2,3-b] pyridine had an IC50 of 480 nM. Then, the structure-activity relationships of 41 analogues of TS-f22 were examined. Two potent inhibitors were proven effective in inhibiting the phosphorylation of the downstream target in the ROCK signaling pathway in vitro and protecting atorvastatin-induced cerebral hemorrhage in vivo. The high hit rate (28.95%) suggested that the integrated virtual screening strategy was quite reliable and could be used as a powerful tool for identifying promising active compounds for targets of interest.

Proteometabolomic response of Deinococcus radiodurans exposed to UVC and vacuum conditions: Initial studies prior to the Tanpopo space mission.

PubMed

Ott, Emanuel; Kawaguchi, Yuko; Kölbl, Denise; Chaturvedi, Palak; Nakagawa, Kazumichi; Yamagishi, Akihiko; Weckwerth, Wolfram; Milojevic, Tetyana

2017-01-01

The multiple extremes resistant bacterium Deinococcus radiodurans is able to withstand harsh conditions of simulated outer space environment. The Tanpopo orbital mission performs a long-term space exposure of D. radiodurans aiming to investigate the possibility of interplanetary transfer of life. The revealing of molecular machinery responsible for survivability of D. radiodurans in the outer space environment can improve our understanding of underlying stress response mechanisms. In this paper, we have evaluated the molecular response of D. radiodurans after the exposure to space-related conditions of UVC irradiation and vacuum. Notably, scanning electron microscopy investigations showed that neither morphology nor cellular integrity of irradiated cells was affected, while integrated proteomic and metabolomic analysis revealed numerous molecular alterations in metabolic and stress response pathways. Several molecular key mechanisms of D. radiodurans, including the tricarboxylic acid cycle, the DNA damage response systems, ROS scavenging systems and transcriptional regulators responded in order to cope with the stressful situation caused by UVC irradiation under vacuum conditions. These results reveal the effectiveness of the integrative proteometabolomic approach as a tool in molecular analysis of microbial stress response caused by space-related factors.

Respiromics - An integrative analysis linking mitochondrial bioenergetics to molecular signatures.

PubMed

Walheim, Ellen; Wiśniewski, Jacek R; Jastroch, Martin

2018-03-01

Energy metabolism is challenged upon nutrient stress, eventually leading to a variety of metabolic diseases that represent a major global health burden. Here, we combine quantitative mitochondrial respirometry (Seahorse technology) and proteomics (LC-MS/MS-based total protein approach) to understand how molecular changes translate to changes in mitochondrial energy transduction during diet-induced obesity (DIO) in the liver. The integrative analysis reveals that significantly increased palmitoyl-carnitine respiration is supported by an array of proteins enriching lipid metabolism pathways. Upstream of the respiratory chain, the increased capacity for ATP synthesis during DIO associates strongest to mitochondrial uptake of pyruvate, which is routed towards carboxylation. At the respiratory chain, robust increases of complex I are uncovered by cumulative analysis of single subunit concentrations. Specifically, nuclear-encoded accessory subunits, but not mitochondrial-encoded or core units, appear to be permissive for enhanced lipid oxidation. Our integrative analysis, that we dubbed "respiromics", represents an effective tool to link molecular changes to functional mechanisms in liver energy metabolism, and, more generally, can be applied for mitochondrial analysis in a variety of metabolic and mitochondrial disease models. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

A network pharmacology-integrated metabolomics strategy for clarifying the difference between effective compounds of raw and processed Farfarae flos by ultra high-performance liquid chromatography-quadrupole-time of flight mass spectrometry.

PubMed

Ding, Mingya; Li, Zhen; Yu, Xie-An; Zhang, Dong; Li, Jin; Wang, Hui; He, Jun; Gao, Xiu-Mei; Chang, Yan-Xu

2018-07-15

This study aimed to clarify the difference between the effective compounds of raw and processed Farfarae flos using a network pharmacology-integrated metabolomics strategy. First, metabolomics data were obtained by ultra high-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF/MS). Then, metabolomics analysis was developed to screen for the influential compounds that were different between raw and processed Farfarae flos. Finally, a network pharmacology approach was applied to verify the activity of the screened compounds. As a result, 4 compounds (chlorogenic acid, caffeic acid, rutin and isoquercitrin) were successfully screened, identified, quantified and verified as the most influential effective compounds. They may synergistically inhibit the p38, JNK and ERK-mediated pathways, which would induce the inhibition of the expression of the IFA virus. The results revealed that the proposed network pharmacology-integrated metabolomics strategy was a powerful tool for discovering the effective compounds that were responsible for the difference between raw and processed Chinese herbs. Copyright © 2018 Elsevier B.V. All rights reserved.

Proteometabolomic response of Deinococcus radiodurans exposed to UVC and vacuum conditions: Initial studies prior to the Tanpopo space mission

PubMed Central

Ott, Emanuel; Kawaguchi, Yuko; Kölbl, Denise; Chaturvedi, Palak; Nakagawa, Kazumichi; Yamagishi, Akihiko; Weckwerth, Wolfram

2017-01-01

The multiple extremes resistant bacterium Deinococcus radiodurans is able to withstand harsh conditions of simulated outer space environment. The Tanpopo orbital mission performs a long-term space exposure of D. radiodurans aiming to investigate the possibility of interplanetary transfer of life. The revealing of molecular machinery responsible for survivability of D. radiodurans in the outer space environment can improve our understanding of underlying stress response mechanisms. In this paper, we have evaluated the molecular response of D. radiodurans after the exposure to space-related conditions of UVC irradiation and vacuum. Notably, scanning electron microscopy investigations showed that neither morphology nor cellular integrity of irradiated cells was affected, while integrated proteomic and metabolomic analysis revealed numerous molecular alterations in metabolic and stress response pathways. Several molecular key mechanisms of D. radiodurans, including the tricarboxylic acid cycle, the DNA damage response systems, ROS scavenging systems and transcriptional regulators responded in order to cope with the stressful situation caused by UVC irradiation under vacuum conditions. These results reveal the effectiveness of the integrative proteometabolomic approach as a tool in molecular analysis of microbial stress response caused by space-related factors. PMID:29244852

Equitable Access by Design. A Conceptual Framework for Integrated Student Supports within Linked Learning Pathways

ERIC Educational Resources Information Center

de Velasco, Jorge Ruiz; Newman, Elizabeth; Borsato, Graciela

2016-01-01

This report proposes a conceptual framework for defining and implementing a system of integrated student supports that provides equitable access to college and career readiness via Linked Learning pathways in high schools. The framework emphasizes the central commitment of the Linked Learning approach to challenge prevailing norms of…

Cross-species integration of human health and ecological endpoints into risk assessment using the Aggregate Exposure Pathway and Adverse Outcome Pathway frameworks

EPA Science Inventory

Exposure to environmental contaminants can influence both human health and ecological endpoints. Chemical risk assessments combine exposure and toxicity data to estimate the likelihood of adverse outcomes for these endpoints, but are rarely conducted in a manner that integrates ...

Fostering development of nursing practices to support integrated care when implementing integrated care pathways: what levers to use?

PubMed

Longpré, Caroline; Dubois, Carl-Ardy

2017-11-29

Care integration has been the focus of recent health system reforms. Given their functions at all levels of the care continuum, nurses have a substantial and primordial role to play in such integration processes. The aim of this study was to identify levers and strategies that organizations can use to support the development of a nursing practice aligned with the requirements of care integration in a health and social services centre (HSSC) in Quebec. The research design was a cross-sectional descriptive qualitative study based on a single case study with nested levels of analysis. The case was a public, multi-disciplinary HSSC in a semi-urban region of Quebec. Semi-structured interviews with 37 persons (nurses, professionals, managers, administrators) allowed for data saturation and ensured theoretical representation by covering four care pathways constituting different care integration contexts. Analysis involved four steps: preparing a predetermined list of codes based on the reference framework developed by Minkman (2011); coding transcript content; developing general and summary matrices to group observations for each care pathway; and creating a general model showing the overall results for the four pathways. The organization's capacity for response with regard to developing an integrated system of services resulted in two types of complementary interventions. The first involved investing in key resources and renewing organizational structures; the second involved deploying a series of organizational and clinical-administrative processes. In resource terms, integration efforts resulted in setting up new strategic services, re-arranging physical infrastructures, and deploying new technological resources. Organizational and clinical-administrative processes to promote integration involved renewing governance, improving the flow of care pathways, fostering continuous quality improvement, developing new roles, promoting clinician collaboration, and strengthening care providers' capacities. However, progress in these areas was offset by persistent constraints. The results highlight key levers organizations can use to foster the implementation and institutionalization of integrative nursing practices. They show that progress in this area requires a combination of strategies using multiple complementary levers. They also suggest that such progress calls for rethinking not only the deployment of certain organizational resources and structures, but also a series of organizational and clinical processes.

Associations between Proprioceptive Neural Pathway Structural Connectivity and Balance in People with Multiple Sclerosis

PubMed Central

Fling, Brett W.; Dutta, Geetanjali Gera; Schlueter, Heather; Cameron, Michelle H.; Horak, Fay B.

2014-01-01

Mobility and balance impairments are a hallmark of multiple sclerosis (MS), affecting nearly half of patients at presentation and resulting in decreased activity and participation, falls, injuries, and reduced quality of life. A growing body of work suggests that balance impairments in people with mild MS are primarily the result of deficits in proprioception, the ability to determine body position in space in the absence of vision. A better understanding of the pathophysiology of balance disturbances in MS is needed to develop evidence-based rehabilitation approaches. The purpose of the current study was to (1) map the cortical proprioceptive pathway in vivo using diffusion-weighted imaging and (2) assess associations between proprioceptive pathway white matter microstructural integrity and performance on clinical and behavioral balance tasks. We hypothesized that people with MS (PwMS) would have reduced integrity of cerebral proprioceptive pathways, and that reduced white matter microstructure within these tracts would be strongly related to proprioceptive-based balance deficits. We found poorer balance control on proprioceptive-based tasks and reduced white matter microstructural integrity of the cortical proprioceptive tracts in PwMS compared with age-matched healthy controls (HC). Microstructural integrity of this pathway in the right hemisphere was also strongly associated with proprioceptive-based balance control in PwMS and controls. Conversely, while white matter integrity of the right hemisphere’s proprioceptive pathway was significantly correlated with overall balance performance in HC, there was no such relationship in PwMS. These results augment existing literature suggesting that balance control in PwMS may become more dependent upon (1) cerebellar-regulated proprioceptive control, (2) the vestibular system, and/or (3) the visual system. PMID:25368564

Associations between Proprioceptive Neural Pathway Structural Connectivity and Balance in People with Multiple Sclerosis.

PubMed

Fling, Brett W; Dutta, Geetanjali Gera; Schlueter, Heather; Cameron, Michelle H; Horak, Fay B

2014-01-01

Mobility and balance impairments are a hallmark of multiple sclerosis (MS), affecting nearly half of patients at presentation and resulting in decreased activity and participation, falls, injuries, and reduced quality of life. A growing body of work suggests that balance impairments in people with mild MS are primarily the result of deficits in proprioception, the ability to determine body position in space in the absence of vision. A better understanding of the pathophysiology of balance disturbances in MS is needed to develop evidence-based rehabilitation approaches. The purpose of the current study was to (1) map the cortical proprioceptive pathway in vivo using diffusion-weighted imaging and (2) assess associations between proprioceptive pathway white matter microstructural integrity and performance on clinical and behavioral balance tasks. We hypothesized that people with MS (PwMS) would have reduced integrity of cerebral proprioceptive pathways, and that reduced white matter microstructure within these tracts would be strongly related to proprioceptive-based balance deficits. We found poorer balance control on proprioceptive-based tasks and reduced white matter microstructural integrity of the cortical proprioceptive tracts in PwMS compared with age-matched healthy controls (HC). Microstructural integrity of this pathway in the right hemisphere was also strongly associated with proprioceptive-based balance control in PwMS and controls. Conversely, while white matter integrity of the right hemisphere's proprioceptive pathway was significantly correlated with overall balance performance in HC, there was no such relationship in PwMS. These results augment existing literature suggesting that balance control in PwMS may become more dependent upon (1) cerebellar-regulated proprioceptive control, (2) the vestibular system, and/or (3) the visual system.

Teachers Connect "with" Technology: Online Tools Build New Pathways to Collaboration

ERIC Educational Resources Information Center

Phillips, Vicki L.; Olson, Lynn

2013-01-01

Teachers, curriculum experts, and other educators work together using online tools developed by the Bill & Melinda Gates Foundation to create high-quality, useful lessons and research-based instructional tools incorporating the Common Core State Standards.

NAViGaTing the Micronome – Using Multiple MicroRNA Prediction Databases to Identify Signalling Pathway-Associated MicroRNAs

PubMed Central

Shirdel, Elize A.; Xie, Wing; Mak, Tak W.; Jurisica, Igor

2011-01-01

Background MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome – referred to as the micronome – to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal — mirDIP (http://ophid.utoronto.ca/mirDIP). Results mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs. Conclusions Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level. PMID:21364759

Core signaling pathways in ovarian cancer stem cell revealed by integrative analysis of multi-marker genomics data.

PubMed

Zhang, Tianyu; Xu, Jielin; Deng, Siyuan; Zhou, Fengqi; Li, Jin; Zhang, Liwei; Li, Lang; Wang, Qi-En; Li, Fuhai

2018-01-01

Tumor recurrence occurs in more than 70% of ovarian cancer patients, and the majority eventually becomes refractory to treatments. Ovarian Cancer Stem Cells (OCSCs) are believed to be responsible for the tumor relapse and drug resistance. Therefore, eliminating ovarian CSCs is important to improve the prognosis of ovarian cancer patients. However, there is a lack of effective drugs to eliminate OCSCs because the core signaling pathways regulating OCSCs remain unclear. Also it is often hard for biologists to identify a few testable targets and infer driver signaling pathways regulating CSCs from a large number of differentially expression genes in an unbiased manner. In this study, we propose a straightforward and integrative analysis to identify potential core signaling pathways of OCSCs by integrating transcriptome data of OCSCs isolated based on two distinctive markers, ALDH and side population, with regulatory network (Transcription Factor (TF) and Target Interactome) and signaling pathways. We first identify the common activated TFs in two OCSC populations integrating the gene expression and TF-target Interactome; and then uncover up-stream signaling cascades regulating the activated TFs. In specific, 22 activated TFs are identified. Through literature search validation, 15 of them have been reported in association with cancer stem cells. Additionally, 10 TFs are found in the KEGG signaling pathways, and their up-stream signaling cascades are extracted, which also provide potential treatment targets. Moreover, 40 FDA approved drugs are identified to target on the up-stream signaling cascades, and 15 of them have been reported in literatures in cancer stem cell treatment. In conclusion, the proposed approach can uncover the activated up-stream signaling, activated TFs and up-regulated target genes that constitute the potential core signaling pathways of ovarian CSC. Also drugs and drug combinations targeting on the core signaling pathways might be able to eliminate OCSCs. The proposed approach can also be applied for identifying potential activated signaling pathways of other types of cancers.

Soldering Tool for Integrated Circuits

NASA Technical Reports Server (NTRS)

Takahashi, Ted H.

1987-01-01

Many connections soldered simultaneously in confined spaces. Improved soldering tool bonds integrated circuits onto printed-circuit boards. Intended especially for use with so-called "leadless-carrier" integrated circuits.

The Role of AhR in Autoimmune Regulation and Its Potential as a Therapeutic Target against CD4 T Cell Mediated Inflammatory Disorder

PubMed Central

Zhu, Conghui; Xie, Qunhui; Zhao, Bin

2014-01-01

AhR has recently emerged as a critical physiological regulator of immune responses affecting both innate and adaptive systems. Since the AhR signaling pathway represents an important link between environmental stimulators and immune-mediated inflammatory disorder, it has become the object of great interest among researchers recently. The current review discusses new insights into the mechanisms of action of a select group of inflammatory autoimmune diseases and the ligand-activated AhR signaling pathway. Representative ligands of AhR, both exogenous and endogenous, are also reviewed relative to their potential use as tools for understanding the role of AhR and as potential therapeutics for the treatment of various inflammatory autoimmune diseases, with a focus on CD4 helper T cells, which play important roles both in self-immune tolerance and in inflammatory autoimmune diseases. Evidence indicating the potential use of these ligands in regulating inflammation in various diseases is highlighted, and potential mechanisms of action causing immune system effects mediated by AhR signaling are also discussed. The current review will contribute to a better understanding of the role of AhR and its signaling pathway in CD4 helper T cell mediated inflammatory disorder. Considering the established importance of AhR in immune regulation and its potential as a therapeutic target, we also think that both further investigation into the molecular mechanisms of immune regulation that are mediated by the ligand-specific AhR signaling pathway, and integrated research and development of new therapeutic drug candidates targeting the AhR signaling pathway should be pursued urgently. PMID:24905409

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

PubMed

Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

2016-02-01

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.