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.

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

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

PubMed

Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

2016-01-01

In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

Microarray analysis of retinal gene expression in Egr-1 knockout mice

PubMed Central

Schippert, Ruth; Schaeffel, Frank

2009-01-01

Purpose We found earlier that 42 day-old Egr-1 knockout mice had longer eyes and a more myopic refractive error compared to their wild-types. To identify genes that could be responsible for the temporarily enhanced axial eye growth, a microarray analysis was performed in knockout and wild-type mice at the postnatal ages of 30 and 42 days. Methods The retinas of homozygous and wild-type Egr-1 knockout mice (Taconic, Ry, Denmark) were prepared for RNA isolation (RNeasy Mini Kit, Qiagen) at the age of 30 or 42 days, respectively (n=12 each). Three retinas were pooled and labeled cRNA was made. The samples were hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 Arrays. Hybridization signals were calculated using GC-RMA normalization. Genes were identified as differentially expressed if they showed a fold-change (FC) of at least 1.5 and a p-value <0.05. A false-discovery rate of 5% was applied. Ten genes with potential biologic relevance were examined further with semiquantitative real-time RT–PCR. Results Comparing mRNA expression levels between wild-type and homozygous Egr-1 knockout mice, we found 73 differentially expressed genes at the age of 30 days and 135 genes at the age of 42 days. Testing for differences in gene expression between the two ages (30 versus 42 days), 54 genes were differently expressed in wild-type mice and 215 genes in homozygous animals. Based on three networks proposed by Ingenuity pathway analysis software, nine differently expressed genes in the homozygous Egr-1 knockout mice were chosen for further validation by real-time RT–PCR, three genes in each network. In addition, the gene that was most prominently regulated in the knockout mice, compared to wild-type, at both 30 days and 42 days of age (protocadherin beta-9 [Pcdhb9]), was tested with real-time RT–PCR. Changes in four of the ten genes could be confirmed by real-time RT–PCR: nuclear prelamin A recognition factor (Narf), oxoglutarate dehydrogenase (Ogdh), selenium binding protein 1 (Selenbp1), and Pcdhb9. Except for Pcdhb9, the genes whose mRNA expression levels were validated were listed in one of the networks proposed by Ingenuity pathway analysis software. In addition to these genes, the software proposed several key-regulators which did not change in our study: retinoic acid, vascular endothelial growth factor A (VEGF-A), FBJ murine osteosarcoma viral oncogene homolog (cFos), and others. Conclusions Identification of genes that are differentially regulated during the development period between postnatal day 30 (when both homozygous and wild-type mice still have the same axial length) and day 42 (where the difference in eye length is apparent) could improve the understanding of mechanisms for the control of axial eye growth and may lead to potential targets for pharmacological intervention. With the aid of pathway-analysis software, a coarse picture of possible biochemical pathways could be generated. Although the mRNA expression levels of proteins proposed by the software, like VEGF, FOS, retinoic acid (RA) receptors, or cellular RA binding protein, did not show any changes in our experiment, these molecules have previously been implicated in the signaling cascades controlling axial eye growth. According to the pathway-analysis software, they represent links between several proteins whose mRNA expression was changed in our study. PMID:20019881

Microarray analysis of retinal gene expression in Egr-1 knockout mice.

PubMed

Schippert, Ruth; Schaeffel, Frank; Feldkaemper, Marita Pauline

2009-12-10

We found earlier that 42 day-old Egr-1 knockout mice had longer eyes and a more myopic refractive error compared to their wild-types. To identify genes that could be responsible for the temporarily enhanced axial eye growth, a microarray analysis was performed in knockout and wild-type mice at the postnatal ages of 30 and 42 days. The retinas of homozygous and wild-type Egr-1 knockout mice (Taconic, Ry, Denmark) were prepared for RNA isolation (RNeasy Mini Kit, Qiagen) at the age of 30 or 42 days, respectively (n=12 each). Three retinas were pooled and labeled cRNA was made. The samples were hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 Arrays. Hybridization signals were calculated using GC-RMA normalization. Genes were identified as differentially expressed if they showed a fold-change (FC) of at least 1.5 and a p-value <0.05. A false-discovery rate of 5% was applied. Ten genes with potential biologic relevance were examined further with semiquantitative real-time RT-PCR. Comparing mRNA expression levels between wild-type and homozygous Egr-1 knockout mice, we found 73 differentially expressed genes at the age of 30 days and 135 genes at the age of 42 days. Testing for differences in gene expression between the two ages (30 versus 42 days), 54 genes were differently expressed in wild-type mice and 215 genes in homozygous animals. Based on three networks proposed by Ingenuity pathway analysis software, nine differently expressed genes in the homozygous Egr-1 knockout mice were chosen for further validation by real-time RT-PCR, three genes in each network. In addition, the gene that was most prominently regulated in the knockout mice, compared to wild-type, at both 30 days and 42 days of age (protocadherin beta-9 [Pcdhb9]), was tested with real-time RT-PCR. Changes in four of the ten genes could be confirmed by real-time RT-PCR: nuclear prelamin A recognition factor (Narf), oxoglutarate dehydrogenase (Ogdh), selenium binding protein 1 (Selenbp1), and Pcdhb9. Except for Pcdhb9, the genes whose mRNA expression levels were validated were listed in one of the networks proposed by Ingenuity pathway analysis software. In addition to these genes, the software proposed several key-regulators which did not change in our study: retinoic acid, vascular endothelial growth factor A (VEGF-A), FBJ murine osteosarcoma viral oncogene homolog (cFos), and others. Identification of genes that are differentially regulated during the development period between postnatal day 30 (when both homozygous and wild-type mice still have the same axial length) and day 42 (where the difference in eye length is apparent) could improve the understanding of mechanisms for the control of axial eye growth and may lead to potential targets for pharmacological intervention. With the aid of pathway-analysis software, a coarse picture of possible biochemical pathways could be generated. Although the mRNA expression levels of proteins proposed by the software, like VEGF, FOS, retinoic acid (RA) receptors, or cellular RA binding protein, did not show any changes in our experiment, these molecules have previously been implicated in the signaling cascades controlling axial eye growth. According to the pathway-analysis software, they represent links between several proteins whose mRNA expression was changed in our study.

Mining featured biomarkers associated with prostatic carcinoma based on bioinformatics.

PubMed

Piao, Guanying; Wu, Jiarui

2013-11-01

To analyze the differentially expressed genes and identify featured biomarkers from prostatic carcinoma. The software "Significance Analysis of Microarray" (SAM) was used to identify the differentially coexpressed genes (DCGs). The DCGs existed in two datasets were analyzed by GO (Gene Ontology) functional annotation. A total of 389 DCGs were obtained. By GO analysis, we found these DCGs were closely related with the acinus development, TGF-β receptor and signal transduction pathways. Furthermore, five featured biomarkers were discovered by interaction analysis. These important signal pathways and oncogenes may provide potential therapeutic targets for prostatic carcinoma.

The Pathway Tools software.

PubMed

Karp, Peter D; Paley, Suzanne; Romero, Pedro

2002-01-01

Bioinformatics requires reusable software tools for creating model-organism databases (MODs). The Pathway Tools is a reusable, production-quality software environment for creating a type of MOD called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc (see http://ecocyc.org) integrates our evolving understanding of the genes, proteins, metabolic network, and genetic network of an organism. This paper provides an overview of the four main components of the Pathway Tools: The PathoLogic component supports creation of new PGDBs from the annotated genome of an organism. The Pathway/Genome Navigator provides query, visualization, and Web-publishing services for PGDBs. The Pathway/Genome Editors support interactive updating of PGDBs. The Pathway Tools ontology defines the schema of PGDBs. The Pathway Tools makes use of the Ocelot object database system for data management services for PGDBs. The Pathway Tools has been used to build PGDBs for 13 organisms within SRI and by external users.

Racial disparity in pathophysiologic pathways of preterm birth based on genetic variants

PubMed Central

Menon, Ramkumar; Pearce, Brad; Velez, Digna R; Merialdi, Mario; Williams, Scott M; Fortunato, Stephen J; Thorsen, Poul

2009-01-01

Objective To study pathophysiologic pathways in spontaneous preterm birth and possibly the racial disparity associating with maternal and fetal genetic variations, using bioinformatics tools. Methods A large scale candidate gene association study was performed on 1442 SNPs in 130 genes in a case (preterm birth < 36 weeks) control study (term birth > 37 weeks). Both maternal and fetal DNA from Caucasians (172 cases and 198 controls) and 279 African-Americans (82 cases and 197 controls) were used. A single locus association (genotypic) analysis followed by hierarchical clustering was performed, where clustering was based on p values for significant associations within each race. Using Ingenuity Pathway Analysis (IPA) software, known pathophysiologic pathways in both races were determined. Results From all SNPs entered into the analysis, the IPA mapped genes to specific disease functions. Gene variants in Caucasians were implicated in disease functions shared with other known disorders; specifically, dermatopathy, inflammation, and hematological disorders. This may reflect abnormal cervical ripening and decidual hemorrhage. In African-Americans inflammatory pathways were the most prevalent. In Caucasians, maternal gene variants showed the most prominent role in disease functions, whereas in African Americans it was fetal variants. The IPA software was used to generate molecular interaction maps that differed between races and also between maternal and fetal genetic variants. Conclusion Differences at the genetic level revealed distinct disease functions and operational pathways in African Americans and Caucasians in spontaneous preterm birth. Differences in maternal and fetal contributions in pregnancy outcome are also different between African Americans and Caucasians. These results present a set of explicit testable hypotheses regarding genetic associations with preterm birth in African Americans and Caucasians PMID:19527514

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 .

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.

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways.

PubMed

Beltrame, Luca; Calura, Enrica; Popovici, Razvan R; Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-08-01

Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and 'wet lab' scientists. The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X.

Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations.

PubMed

Förster, Frank; Beisser, Daniela; Grohme, Markus A; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C; Shkumatov, Alexander V; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O; Frohme, Marcus; Dandekar, Thomas

2012-01-01

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant.

Comparative analysis of gene expression profiles of hip articular cartilage between non-traumatic necrosis and osteoarthritis.

PubMed

Wang, Wenyu; Liu, Yang; Hao, Jingcan; Zheng, Shuyu; Wen, Yan; Xiao, Xiao; He, Awen; Fan, Qianrui; Zhang, Feng; Liu, Ruiyu

2016-10-10

Hip cartilage destruction is consistently observed in the non-traumatic osteonecrosis of femoral head (NOFH) and accelerates its bone necrosis. The molecular mechanism underlying the cartilage damage of NOFH remains elusive. In this study, we conducted a systematically comparative study of gene expression profiles between NOFH and osteoarthritis (OA). Hip articular cartilage specimens were collected from 12 NOFH patients and 12 controls with traumatic femoral neck fracture for microarray (n=4) and quantitative real-time PCR validation experiments (n=8). Gene expression profiling of articular cartilage was performed using Agilent Human 4×44K Microarray chip. The accuracy of microarray experiment was further validated by qRT-PCR. Gene expression results of OA hip cartilage were derived from previously published study. Significance Analysis of Microarrays (SAM) software was applied for identifying differently expressed genes. Gene ontology (GO) and pathway enrichment analysis were conducted by Gene Set Enrichment Analysis software and DAVID tool, respectively. Totally, 27 differently expressed genes were identified for NOFH. Comparing the gene expression profiles of NOFH cartilage and OA cartilage detected 8 common differently expressed genes, including COL5A1, OGN, ANGPTL4, CRIP1, NFIL3, METRNL, ID2 and STEAP1. GO comparative analysis identified 10 common significant GO terms, mainly implicated in apoptosis and development process. Pathway comparative analysis observed that ECM-receptor interaction pathway and focal adhesion pathway were enriched in the differently expressed genes of both NOFH and hip OA. In conclusion, we identified a set of differently expressed genes, GO and pathways for NOFH articular destruction, some of which were also involved in the hip OA. Our study results may help to reveal the pathogenetic similarities and differences of cartilage damage of NOFH and hip OA. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Assessing natural direct and indirect effects through multiple pathways.

PubMed

Lange, Theis; Rasmussen, Mette; Thygesen, Lau Caspar

2014-02-15

Within the fields of epidemiology, interventions research and social sciences researchers are often faced with the challenge of decomposing the effect of an exposure into different causal pathways working through defined mediator variables. The goal of such analyses is often to understand the mechanisms of the system or to suggest possible interventions. The case of a single mediator, thus implying only 2 causal pathways (direct and indirect) from exposure to outcome, has been extensively studied. By using the framework of counterfactual variables, researchers have established theoretical properties and developed powerful tools. However, in practical problems, it is not uncommon to have several distinct causal pathways from exposure to outcome operating through different mediators. In this article, we suggest a widely applicable approach to quantifying and ranking different causal pathways. The approach is an extension of the natural effect models proposed by Lange et al. (Am J Epidemiol. 2012;176(3):190-195). By allowing the analysis of distinct multiple pathways, the suggested approach adds to the capabilities of modern mediation techniques. Furthermore, the approach can be implemented using standard software, and we have included with this article implementation examples using R (R Foundation for Statistical Computing, Vienna, Austria) and Stata software (StataCorp LP, College Station, Texas).

Analyzing the differentially expressed genes and pathway cross-talk in aggressive breast cancer.

PubMed

Chen, Wen-Yan; Wu, Fang; You, Zhen-Yu; Zhang, Zhan-Min; Guo, Yu-Ling; Zhong, Lu-Xing

2015-01-01

The aim of this study was to explore the genes and pathways involved in the aggressive breast cancer cells. The gene expression profiles of GSE40057, including four aggressive breast cell lines and six less aggressive cell lines, were downloaded from the Gene Expression Omnibus (GEO) database. The gene differential expression analysis was carried out with limma software with the method of Bayes for multiple tests. The gene ontology (GO) term enrichment and pathway cross-talk analysis were performed with the online tool of DAVID and Cytoscape software. A total of 401 differentially expressed genes (DEG), such as pentraxin 3 (PTX3), snail family zinc finger 2 (SNAI2), interleukin-8/6 (IL-8/6), osteonectin (SPARC), matrix metallopeptidase-1 (MMP-1) and Ras-related protein Rab-25 (Rab 25), were identified between aggressive and less aggressive cell lines. They were mainly enriched in the GO terms of response to wounding, negative regulation of cell proliferation and calcium binding. Pathways in cancer dysfunctionally interacted with glyoxylate and dicarboxylate metabolism (P < 0.0001), basal transcription factors (P < 0.0001), tyrosine metabolism (P < 0.0001), calcium signaling pathway (P = 0.0021), FcγR-mediated phagocytosis (P = 0.0022), metabolism of xenobiotics by cytochrome P450 (P = 0.0097) and phagosome (P = 0.0102). The screened aggressive cancer-associated DEG (PTX3, SNAI2, IL-8/6, SPARC, MMP-1 and Rab25) and significant pathways (calcium signaling pathway, tyrosine metabolism, alanine, aspartate and glutamate metabolism) give us new insights into the mechanism of aggressive breast cancer cells, and these DEG may become promising target genes in the treatment of metastatic breast cancer. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

BioRuby: bioinformatics software for the Ruby programming language.

PubMed

Goto, Naohisa; Prins, Pjotr; Nakao, Mitsuteru; Bonnal, Raoul; Aerts, Jan; Katayama, Toshiaki

2010-10-15

The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO. BioRuby comes with a tutorial, documentation and an interactive environment, which can be used in the shell, and in the web browser. BioRuby is free and open source software, made available under the Ruby license. BioRuby runs on all platforms that support Ruby, including Linux, Mac OS X and Windows. And, with JRuby, BioRuby runs on the Java Virtual Machine. The source code is available from http://www.bioruby.org/. katayama@bioruby.org

Pros and Cons of Clinical Pathway Software Management: A Qualitative Study.

PubMed

Aarnoutse, M F; Brinkkemper, S; de Mul, M; Askari, M

2018-01-01

In this study we aimed to assess the perceived effectiveness of clinical pathway management software for healthcare professionals. A case study on the clinical pathway management software program Check-It was performed in three departments at an academic medical center. Four months after the implementation of the software, interviews were held with healthcare professionals who work with the system. The interview questions were posed in a semi-structured interview format and the participant were asked about the perceived positive or negative effects of Check-It, and whether they thought the software is effective for them. The interviews were recorded and transcribed based on grounded theory, using different coding techniques. Our results showed fewer overlooked tasks, pre-filled orders and letters, better overview, and increased protocol insight as positive aspects of using the software. Being not flexible enough was experienced as a negative aspect.

Metabolic Flux Analysis in Isotope Labeling Experiments Using the Adjoint Approach.

PubMed

Mottelet, Stephane; Gaullier, Gil; Sadaka, Georges

2017-01-01

Comprehension of metabolic pathways is considerably enhanced by metabolic flux analysis (MFA-ILE) in isotope labeling experiments. The balance equations are given by hundreds of algebraic (stationary MFA) or ordinary differential equations (nonstationary MFA), and reducing the number of operations is therefore a crucial part of reducing the computation cost. The main bottleneck for deterministic algorithms is the computation of derivatives, particularly for nonstationary MFA. In this article, we explain how the overall identification process may be speeded up by using the adjoint approach to compute the gradient of the residual sum of squares. The proposed approach shows significant improvements in terms of complexity and computation time when it is compared with the usual (direct) approach. Numerical results are obtained for the central metabolic pathways of Escherichia coli and are validated against reference software in the stationary case. The methods and algorithms described in this paper are included in the sysmetab software package distributed under an Open Source license at http://forge.scilab.org/index.php/p/sysmetab/.

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

Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways

PubMed Central

Jo, Kyuri; Jung, Inuk; Moon, Ji Hwan; Kim, Sun

2016-01-01

Motivation: To understand the dynamic nature of the biological process, it is crucial to identify perturbed pathways in an altered environment and also to infer regulators that trigger the response. Current time-series analysis methods, however, are not powerful enough to identify perturbed pathways and regulators simultaneously. Widely used methods include methods to determine gene sets such as differentially expressed genes or gene clusters and these genes sets need to be further interpreted in terms of biological pathways using other tools. Most pathway analysis methods are not designed for time series data and they do not consider gene-gene influence on the time dimension. Results: In this article, we propose a novel time-series analysis method TimeTP for determining transcription factors (TFs) regulating pathway perturbation, which narrows the focus to perturbed sub-pathways and utilizes the gene regulatory network and protein–protein interaction network to locate TFs triggering the perturbation. TimeTP first identifies perturbed sub-pathways that propagate the expression changes along the time. Starting points of the perturbed sub-pathways are mapped into the network and the most influential TFs are determined by influence maximization technique. The analysis result is visually summarized in TF-Pathway map in time clock. TimeTP was applied to PIK3CA knock-in dataset and found significant sub-pathways and their regulators relevant to the PIP3 signaling pathway. Availability and Implementation: TimeTP is implemented in Python and available at http://biohealth.snu.ac.kr/software/TimeTP/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: sunkim.bioinfo@snu.ac.kr PMID:27307609

Major carcinogenic pathways identified by gene expression analysis of peritoneal mesotheliomas following chemical treatment in F344 rats

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

Kim, Yongbaek; Thai-Vu Ton; De Angelo, Anthony B.

2006-07-15

This study was performed to characterize the gene expression profile and to identify the major carcinogenic pathways involved in rat peritoneal mesothelioma (RPM) formation following treatment of Fischer 344 rats with o-nitrotoluene (o-NT) or bromochloracetic acid (BCA). Oligo arrays, with over 20,000 target genes, were used to evaluate o-NT- and BCA-induced RPMs, when compared to a non-transformed mesothelial cell line (Fred-PE). Analysis using Ingenuity Pathway Analysis software revealed 169 cancer-related genes that were categorized into binding activity, growth and proliferation, cell cycle progression, apoptosis, and invasion and metastasis. The microarray data were validated by positive correlation with quantitative real-time RT-PCRmore » on 16 selected genes including igf1, tgfb3 and nov. Important carcinogenic pathways involved in RPM formation included insulin-like growth factor 1 (IGF-1), p38 MAPkinase, Wnt/{beta}-catenin and integrin signaling pathways. This study demonstrated that mesotheliomas in rats exposed to o-NT- and BCA were similar to mesotheliomas in humans, at least at the cellular and molecular level.« less

Transcriptome Analysis in Tardigrade Species Reveals Specific Molecular Pathways for Stress Adaptations

PubMed Central

Förster, Frank; Beisser, Daniela; Grohme, Markus A.; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C.; Shkumatov, Alexander V.; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O.; Frohme, Marcus; Dandekar, Thomas

2012-01-01

Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant. PMID:22563243

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

PubMed

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

RECOVERING FILTER-BASED MICROARRAY DATA FOR PATHWAYS ANALYSIS USING A MULTIPOINT ALIGNMENT STRATEGY

EPA Science Inventory

The use of commercial microarrays are rapidly becoming the method of choice for profiling gene expression and assessing various disease states. Research Genetics has provided a series of well defined biological and software tools to the research community for these analyses. Th...

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.

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

PubMed Central

Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

2017-01-01

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

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.

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

PubMed

Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

2012-12-01

Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.

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

Identification of key target genes and pathways in laryngeal carcinoma

PubMed Central

Liu, Feng; Du, Jintao; Liu, Jun; Wen, Bei

2016-01-01

The purpose of the present study was to screen the key genes associated with laryngeal carcinoma and to investigate the molecular mechanism of laryngeal carcinoma progression. The gene expression profile of GSE10935 [Gene Expression Omnibus (GEO) accession number], including 12 specimens from laryngeal papillomas and 12 specimens from normal laryngeal epithelia controls, was downloaded from the GEO database. Differentially expressed genes (DEGs) were screened in laryngeal papillomas compared with normal controls using Limma package in R language, followed by Gene Ontology (GO) enrichment analysis and pathway enrichment analysis. Furthermore, the protein-protein interaction (PPI) network of DEGs was constructed using Cytoscape software and modules were analyzed using MCODE plugin from the PPI network. Furthermore, significant biological pathway regions (sub-pathway) were identified by using iSubpathwayMiner analysis. A total of 67 DEGs were identified, including 27 up-regulated genes and 40 down-regulated genes and they were involved in different GO terms and pathways. PPI network analysis revealed that Ras association (RalGDS/AF-6) domain family member 1 (RASSF1) was a hub protein. The sub-pathway analysis identified 9 significantly enriched sub-pathways, including glycolysis/gluconeogenesis and nitrogen metabolism. Genes such as phosphoglycerate kinase 1 (PGK1), carbonic anhydrase II (CA2), and carbonic anhydrase XII (CA12) whose node degrees were >10 were identified in the disease risk sub-pathway. Genes in the sub-pathway, such as RASSF1, PGK1, CA2 and CA12 were presumed to serve critical roles in laryngeal carcinoma. The present study identified DEGs and their sub-pathways in the disease, which may serve as potential targets for treatment of laryngeal carcinoma. PMID:27446427

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.

Temperature distribution around thin electroconductive layers created on composite textile substrates

NASA Astrophysics Data System (ADS)

Korzeniewska, Ewa; Szczesny, Artur; Krawczyk, Andrzej; Murawski, Piotr; Mróz, Józef; Seme, Sebastian

2018-03-01

In this paper, the authors describe the distribution of temperatures around electroconductive pathways created by a physical vacuum deposition process on flexible textile substrates used in elastic electronics and textronics. Cordura material was chosen as the substrate. Silver with 99.99% purity was used as the deposited metal. This research was based on thermographic photographs of the produced samples. Analysis of the temperature field around the electroconductive layer was carried out using Image ThermaBase EU software. The analysis of the temperature distribution highlights the software's usefulness in determining the homogeneity of the created metal layer. Higher local temperatures and non-uniform distributions at the same time can negatively influence the work of the textronic system.

A comprehensive pathway map of epidermal growth factor receptor signaling

PubMed Central

Oda, Kanae; Matsuoka, Yukiko; Funahashi, Akira; Kitano, Hiroaki

2005-01-01

The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML). PMID:16729045

Analysis of vascular endothelial dysfunction genes and related pathways in obesity through systematic bioinformatics.

PubMed

Zhang, Hui; Wang, Jing; Sun, Ling; Xu, Qiuqin; Hou, Miao; Ding, Yueyue; Huang, Jie; Chen, Ye; Cao, Lei; Zhang, Jianmin; Qian, Weiguo; Lv, Haitao

2015-01-01

Obesity has become an increasingly serious health problem and popular research topic. It is associated with many diseases, especially cardiovascular disease (CVD)-related endothelial dysfunction. This study analyzed genes related to endothelial dysfunction and obesity and then summarized their most significant signaling pathways. Genes related to vascular endothelial dysfunction and obesity were extracted from a PubMed database, and analyzed by STRING, DAVID, and Gene-Go Meta-Core software. 142 genes associated with obesity were found to play a role in endothelial dysfunction in PubMed. A significant pathway (Angiotensin system maturation in protein folding and maturation) associated with obesity and endothelial dysfunction was explored. The genes and the pathway explored may play an important role in obesity. Further studies about preventing vascular endothelial dysfunction obesity should be conducted through targeting these loci and pathways.

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways

PubMed Central

Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

2011-01-01

Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and ‘wet lab’ scientists. Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X. Contact: duccio.cavalieri@unifi.it; sorin@wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21653523

Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

PubMed Central

Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

2014-01-01

Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

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

Metabolomics-based mechanisms exploration of Huang-Lian Jie-Du decoction on cerebral ischemia via UPLC-Q-TOF/MS analysis on rat serum.

PubMed

Zhu, Baojie; Cao, Huiting; Sun, Limin; Li, Bo; Guo, Liwei; Duan, Jinao; Zhu, Huaxu; Zhang, Qichun

2018-04-24

Huang-Lian Jie-Du decoction (HLJDD), a traditional formula of Chinese medicine constituted with Rhizoma Coptidis, RadixScutellariae, CortexPhellodendri amurensis and Fructus Gardeniae, exhibits unambiguous therapeutic effect on cerebral ischemia via multi-targets action. Further investigation, however, is still required to explore the relationship between those mechanisms and targets through system approaches. Rats of cerebral ischemia were completed by middle cerebral artery occlusion (MCAO) with reperfusion. Following evaluation of pharmacological actions of HLJDD on MCAO rats, the plasma samples from rats of control, MCAO and HLJDD-treated MCAO groups were prepared strictly and subjected to ultra-performance liquid chromatography quadrupole time of flight mass spectrometry for metabolites analysis. The raw mass data were imported to MassLynx software for peak detection and alignment, and further introduced to EZinfo 2.0 software for orthogonal projection to latent structures analysis, principal component analysis and partial least-squares-discriminant analysis. The metabolic pathways assay of those potential biomarkers were performed with MetaboAnalyst through the online database, HMDB, Metlin, KEGG and SMPD. Those intriguing metabolic pathways were further investigated via biochemical assay. HLJDD ameliorated the MCAO-induce cerebral damage and blocked the severe inflammation response. There were nineteen different biomarkers identified among control, MCAO and HLJDD-treated MCAO groups. Ten metabolic pathways were proposed from these significant metabolites. Incorporation with the biochemical assay of cerebral tissue, modulation of metabolic stress, regulation glutamate/GABA-glutamine cycle and enhancement of cholinergic neurons function were explored that involved in the actions of HLJDD on cerebral ischemia. HLJDD achieves therapeutic action on cerebral ischemia via coordinating the basic pathophysiological network of metabolic stress, glutamate metabolism, and acetylcholine levels and function. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparative analysis of gene expression profiles of OPN signaling pathway in four kinds of liver diseases.

PubMed

Wang, Gaiping; Chen, Shasha; Zhao, Congcong; Li, Xiaofang; Zhao, Weiming; Yang, Jing; Chang, Cuifang; Xu, Cunshuan

2016-09-01

To explore the relevance of OPN signalling pathway to the occurrence and development of nonalcoholic fatty liver disease (NAFLD), liver cirrhosis (LC), hepatic cancer (HC) and acute hepatic failure (AHF) at transcriptional level, Rat Genome 230 2.0 Array was used to detect expression profiles of OPN signalling pathway-related genes in four kinds of liver diseases. The results showed that 23, 33, 59 and 74 genes were significantly changed in the above four kinds of liver diseases, respectively. H-clustering analysis showed that the expression profiles of OPN signalling-related genes were notably different in four kinds of liver diseases. Subsequently, a total of above-mentioned 147 genes were categorized into four clusters by k-means according to the similarity of gene expression, and expression analysis systematic explorer (EASE) functional enrichment analysis revealed that OPN signalling pathway-related genes were involved in cell adhesion and migration, cell proliferation, apoptosis, stress and inflammatory reaction, etc. Finally, ingenuity pathway analysis (IPA) software was used to predict the functions of OPN signalling-related genes, and the results indicated that the activities of ROS production, cell adhesion and migration, cell proliferation were remarkably increased, while that of apoptosis, stress and inflammatory reaction were reduced in four kinds of liver diseases. In summary, the above physiological activities changed more obviously in LC, HC and AHF than in NAFLD.

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.

A systems biology approach to detect key pathways and interaction networks in gastric cancer on the basis of microarray analysis.

PubMed

Guo, Leilei; Song, Chunhua; Wang, Peng; Dai, Liping; Zhang, Jianying; Wang, Kaijuan

2015-11-01

The aim of the present study was to explore key molecular pathways contributing to gastric cancer (GC) and to construct an interaction network between significant pathways and potential biomarkers. Publicly available gene expression profiles of GSE29272 for GC, and data for the corresponding normal tissue, were downloaded from Gene Expression Omnibus. Pre‑processing and differential analysis were performed with R statistical software packages, and a number of differentially expressed genes (DEGs) were obtained. A functional enrichment analysis was performed for all the DEGs with a BiNGO plug‑in in Cytoscape. Their correlation was analyzed in order to construct a network. The modularity analysis and pathway identification operations were used to identify graph clusters and associated pathways. The underlying molecular mechanisms involving these DEGs were also assessed by data mining. A total of 249 DEGs, which were markedly upregulated and downregulated, were identified. The extracellular region contained the most significantly over‑represented functional terms, with respect to upregulated and downregulated genes, and the closest topological matches were identified for taste transduction and regulation of autophagy. In addition, extracellular matrix‑receptor interactions were identified as the most relevant pathway associated with the progression of GC. The genes for fibronectin 1, secreted phosphoprotein 1, collagen type 4 variant α‑1/2 and thrombospondin 1, which are involved in the pathways, may be considered as potential therapeutic targets for GC. A series of associations between candidate genes and key pathways were also identified for GC, and their correlation may provide novel insights into the pathogenesis of GC.

Applied mediation analyses: a review and tutorial.

PubMed

Lange, Theis; Hansen, Kim Wadt; Sørensen, Rikke; Galatius, Søren

2017-01-01

In recent years, mediation analysis has emerged as a powerful tool to disentangle causal pathways from an exposure/treatment to clinically relevant outcomes. Mediation analysis has been applied in scientific fields as diverse as labour market relations and randomized clinical trials of heart disease treatments. In parallel to these applications, the underlying mathematical theory and computer tools have been refined. This combined review and tutorial will introduce the reader to modern mediation analysis including: the mathematical framework; required assumptions; and software implementation in the R package medflex. All results are illustrated using a recent study on the causal pathways stemming from the early invasive treatment of acute coronary syndrome, for which the rich Danish population registers allow us to follow patients' medication use and more after being discharged from hospital.

Identification of possible genetic polymorphisms involved in cancer cachexia: a systematic review.

PubMed

Tan, Benjamin H L; Ross, James A; Kaasa, Stein; Skorpen, Frank; Fearon, Kenneth C H

2011-04-01

Cancer cachexia is a polygenic and complex syndrome. Genetic variations in regulation of the inflammatory response, muscle and fat metabolic pathways, and pathways in appetite regulation are likely to contribute to the susceptibility or resistance to developing cancer cachexia. A systematic search of Medline and EmBase databases, covering 1986-2008 was performed for potential candidate genes/genetic polymorphisms relating to cancer cachexia. Related genes were then identified using pathway functional analysis software. All candidate genes were reviewed for functional polymorphisms or clinically significant polymorphisms associated with cachexia using the OMIM and GeneRIF databases. Genes with variants which had functional or clinical associations with cachexia and replicated in at least one study were entered into pathway analysis software to reveal possible network associations between genes. A total of 184 polymorphisms with functional or clinical relevance to cancer cachexia were identified in 92 candidate genes. Of these, 42 polymorphisms (in 33 genes) were replicated in more than one study with 13 polymorphisms found to influence two or more hallmarks of cachexia (i.e. inflammation, loss of fat mass and/or lean mass and reduced survival). Thirty-three genes were found to be significantly interconnected in two major networks with four genes (ADIPOQ, IL6, NFKB1 and TLR4) interlinking both networks. Selection of candidate genes and polymorphisms is a key element of multigene study design. The present study provides an initial framework to select genes/polymorphisms for further study in cancer cachexia, and to develop their potential as susceptibility biomarkers of developing cachexia.

Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

PubMed

Tra, Yolande V; Evans, Irene M

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

PubMed Central

Evans, Irene M.

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

Genome Wide Association Study to Identify SNPs and CNPs Associated with Development of Radiation Injury in Prostate Cancer Patients Treated with Radiotherapy

DTIC Science & Technology

2012-10-01

catalyzes the oxidative metabolism of androgens and estrogens in human peripheral tissues18. Other physiological functions included cell adhesion... aldosterone (CNKSR3)21. The Ingenuity Pathway Analysis software (Ingenuity Systems, Inc., Redwood City, CA) grouped 11 of these 12 genes into a

Pathway collages: personalized multi-pathway diagrams.

PubMed

Paley, Suzanne; O'Maille, Paul E; Weaver, Daniel; Karp, Peter D

2016-12-13

Metabolic pathway diagrams are a classical way of visualizing a linked cascade of biochemical reactions. However, to understand some biochemical situations, viewing a single pathway is insufficient, whereas viewing the entire metabolic network results in information overload. How do we enable scientists to rapidly construct personalized multi-pathway diagrams that depict a desired collection of interacting pathways that emphasize particular pathway interactions? We define software for constructing personalized multi-pathway diagrams called pathway-collages using a combination of manual and automatic layouts. The user specifies a set of pathways of interest for the collage from a Pathway/Genome Database. Layouts for the individual pathways are generated by the Pathway Tools software, and are sent to a Javascript Pathway Collage application implemented using Cytoscape.js. That application allows the user to re-position pathways; define connections between pathways; change visual style parameters; and paint metabolomics, gene expression, and reaction flux data onto the collage to obtain a desired multi-pathway diagram. We demonstrate the use of pathway collages in two application areas: a metabolomics study of pathogen drug response, and an Escherichia coli metabolic model. Pathway collages enable facile construction of personalized multi-pathway diagrams.

Pathways to lean software development: An analysis of effective methods of change

NASA Astrophysics Data System (ADS)

Hanson, Richard D.

This qualitative Delphi study explored the challenges that exist in delivering software on time, within budget, and with the original scope identified. The literature review identified many attempts over the past several decades to reform the methods used to develop software. These attempts found that the classical waterfall method, which is firmly entrenched in American business today was to blame for this difficulty (Chatterjee, 2010). Each of these proponents of new methods sought to remove waste, lighten out the process, and implement lean principles in software development. Through this study, the experts evaluated the barriers to effective development principles and defined leadership qualities necessary to overcome these barriers. The barriers identified were issues of resistance to change, risk and reward issues, and management buy-in. Thirty experts in software development from several Fortune 500 companies across the United States explored each of these issues in detail. The conclusion reached by these experts was that visionary leadership is necessary to overcome these challenges.

Software for enhanced video capsule endoscopy: challenges for essential progress.

PubMed

Iakovidis, Dimitris K; Koulaouzidis, Anastasios

2015-03-01

Video capsule endoscopy (VCE) has revolutionized the diagnostic work-up in the field of small bowel diseases. Furthermore, VCE has the potential to become the leading screening technique for the entire gastrointestinal tract. Computational methods that can be implemented in software can enhance the diagnostic yield of VCE both in terms of efficiency and diagnostic accuracy. Since the appearance of the first capsule endoscope in clinical practice in 2001, information technology (IT) research groups have proposed a variety of such methods, including algorithms for detecting haemorrhage and lesions, reducing the reviewing time, localizing the capsule or lesion, assessing intestinal motility, enhancing the video quality and managing the data. Even though research is prolific (as measured by publication activity), the progress made during the past 5 years can only be considered as marginal with respect to clinically significant outcomes. One thing is clear-parallel pathways of medical and IT scientists exist, each publishing in their own area, but where do these research pathways meet? Could the proposed IT plans have any clinical effect and do clinicians really understand the limitations of VCE software? In this Review, we present an in-depth critical analysis that aims to inspire and align the agendas of the two scientific groups.

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis.

PubMed

Liu, Qun; Peng, Yong-Bo; Qi, Lian-Wen; Cheng, Xiao-Lan; Xu, Xiao-Jun; Liu, Le-Le; Liu, E-Hu; Li, Ping

2012-01-01

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism.

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis

PubMed Central

Liu, Qun; Peng, Yong-Bo; Qi, Lian-Wen; Cheng, Xiao-Lan; Xu, Xiao-Jun; Liu, Le-Le; Liu, E-Hu; Li, Ping

2012-01-01

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism. PMID:23243437

MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

PubMed

Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

2017-08-15

Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

HBVPathDB: a database of HBV infection-related molecular interaction network.

PubMed

Zhang, Yi; Bo, Xiao-Chen; Yang, Jing; Wang, Sheng-Qi

2005-03-21

To describe molecules or genes interaction between hepatitis B viruses (HBV) and host, for understanding how virus' and host's genes and molecules are networked to form a biological system and for perceiving mechanism of HBV infection. The knowledge of HBV infection-related reactions was organized into various kinds of pathways with carefully drawn graphs in HBVPathDB. Pathway information is stored with relational database management system (DBMS), which is currently the most efficient way to manage large amounts of data and query is implemented with powerful Structured Query Language (SQL). The search engine is written using Personal Home Page (PHP) with SQL embedded and web retrieval interface is developed for searching with Hypertext Markup Language (HTML). We present the first version of HBVPathDB, which is a HBV infection-related molecular interaction network database composed of 306 pathways with 1 050 molecules involved. With carefully drawn graphs, pathway information stored in HBVPathDB can be browsed in an intuitive way. We develop an easy-to-use interface for flexible accesses to the details of database. Convenient software is implemented to query and browse the pathway information of HBVPathDB. Four search page layout options-category search, gene search, description search, unitized search-are supported by the search engine of the database. The database is freely available at http://www.bio-inf.net/HBVPathDB/HBV/. The conventional perspective HBVPathDB have already contained a considerable amount of pathway information with HBV infection related, which is suitable for in-depth analysis of molecular interaction network of virus and host. HBVPathDB integrates pathway data-sets with convenient software for query, browsing, visualization, that provides users more opportunity to identify regulatory key molecules as potential drug targets and to explore the possible mechanism of HBV infection based on gene expression datasets.

Fractal Branching in Vascular Trees and Networks by VESsel GENeration Analysis (VESGEN)

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia A.

2016-01-01

Vascular patterning offers an informative multi-scale, fractal readout of regulatory signaling by complex molecular pathways. Understanding such molecular crosstalk is important for physiological, pathological and therapeutic research in Space Biology and Astronaut countermeasures. When mapped out and quantified by NASA's innovative VESsel GENeration Analysis (VESGEN) software, remodeling vascular patterns become useful biomarkers that advance out understanding of the response of biology and human health to challenges such as microgravity and radiation in space environments.

Possible pathways used to predict different stages of lung adenocarcinoma.

PubMed

Chen, Xiaodong; Duan, Qiongyu; Xuan, Ying; Sun, Yunan; Wu, Rong

2017-04-01

We aimed to find some specific pathways that can be used to predict the stage of lung adenocarcinoma.RNA-Seq expression profile data and clinical data of lung adenocarcinoma (stage I [37], stage II 161], stage III [75], and stage IV [45]) were obtained from the TCGA dataset. The differentially expressed genes were merged, correlation coefficient matrix between genes was constructed with correlation analysis, and unsupervised clustering was carried out with hierarchical clustering method. The specific coexpression network in every stage was constructed with cytoscape software. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed with KOBAS database and Fisher exact test. Euclidean distance algorithm was used to calculate total deviation score. The diagnostic model was constructed with SVM algorithm.Eighteen specific genes were obtained by getting intersection of 4 group differentially expressed genes. Ten significantly enriched pathways were obtained. In the distribution map of 10 pathways score in different groups, degrees that sample groups deviated from the normal level were as follows: stage I < stage II < stage III < stage IV. The pathway score of 4 stages exhibited linear change in some pathways, and the score of 1 or 2 stages were significantly different from the rest stages in some pathways. There was significant difference between dead and alive for these pathways except thyroid hormone signaling pathway.Those 10 pathways are associated with the development of lung adenocarcinoma and may be able to predict different stages of it. Furthermore, these pathways except thyroid hormone signaling pathway may be able to predict the prognosis.

GUIDOS: tools for the assessment of pattern, connectivity, and fragmentation

NASA Astrophysics Data System (ADS)

Vogt, Peter

2013-04-01

Pattern, connectivity, and fragmentation can be considered as pillars for a quantitative analysis of digital landscape images. The free software toolbox GUIDOS (http://forest.jrc.ec.europa.eu/download/software/guidos) includes a variety of dedicated methodologies for the quantitative assessment of these features. Amongst others, Morphological Spatial Pattern Analysis (MSPA) is used for an intuitive description of image pattern structures and the automatic detection of connectivity pathways. GUIDOS includes tools for the detection and quantitative assessment of key nodes and links as well as to define connectedness in raster images and to setup appropriate input files for an enhanced network analysis using Conefor Sensinode. Finally, fragmentation is usually defined from a species point of view but a generic and quantifiable indicator is needed to measure fragmentation and its changes. Some preliminary results for different conceptual approaches will be shown for a sample dataset. Complemented by pre- and post-processing routines and a complete GIS environment the portable GUIDOS Toolbox may facilitate a holistic assessment in risk assessment studies, landscape planning, and conservation/restoration policies. Alternatively, individual analysis components may contribute to or enhance studies conducted with other software packages in landscape ecology.

Time-series RNA-seq analysis package (TRAP) and its application to the analysis of rice, Oryza sativa L. ssp. Japonica, upon drought stress.

PubMed

Jo, Kyuri; Kwon, Hawk-Bin; Kim, Sun

2014-06-01

Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how organisms react to stress conditions over time. Thus many biologists routinely measure whole genome level gene expressions at multiple time points. However, there are several technical difficulties for analyzing such whole genome expression data. In addition, these days gene expression data is often measured by using RNA-sequencing rather than microarray technologies and then analysis of expression data is much more complicated since the analysis process should start with mapping short reads and produce differentially activated pathways and also possibly interactions among pathways. In addition, many useful tools for analyzing microarray gene expression data are not applicable for the RNA-seq data. Thus a comprehensive package for analyzing time series transcriptome data is much needed. In this article, we present a comprehensive package, Time-series RNA-seq Analysis Package (TRAP), integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment. In addition to implementing useful algorithms that are not available for RNA-seq data, we extended existing pathway analysis methods, ORA and SPIA, for time series analysis and estimates statistical values for combined dataset by an advanced metric. TRAP also produces visual summary of pathway interactions. Gene expression change labeling, a practical clustering method used in TRAP, enables more accurate interpretation of the data when combined with pathway analysis. We applied our methods on a real dataset for the analysis of rice (Oryza sativa L. Japonica nipponbare) upon drought stress. The result showed that TRAP was able to detect pathways more accurately than several existing methods. TRAP is available at http://biohealth.snu.ac.kr/software/TRAP/. Copyright © 2014 Elsevier Inc. All rights reserved.

The BioCyc collection of microbial genomes and metabolic pathways.

PubMed

Karp, Peter D; Billington, Richard; Caspi, Ron; Fulcher, Carol A; Latendresse, Mario; Kothari, Anamika; Keseler, Ingrid M; Krummenacker, Markus; Midford, Peter E; Ong, Quang; Ong, Wai Kit; Paley, Suzanne M; Subhraveti, Pallavi

2017-08-17

BioCyc.org is a microbial genome Web portal that combines thousands of genomes with additional information inferred by computer programs, imported from other databases and curated from the biomedical literature by biologist curators. BioCyc also provides an extensive range of query tools, visualization services and analysis software. Recent advances in BioCyc include an expansion in the content of BioCyc in terms of both the number of genomes and the types of information available for each genome; an expansion in the amount of curated content within BioCyc; and new developments in the BioCyc software tools including redesigned gene/protein pages and metabolite pages; new search tools; a new sequence-alignment tool; a new tool for visualizing groups of related metabolic pathways; and a facility called SmartTables, which enables biologists to perform analyses that previously would have required a programmer's assistance. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Key genes and pathways in measles and their interaction with environmental chemicals.

PubMed

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-06-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles.

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.

Identification and analysis of potential targets in Streptococcus sanguinis using computer aided protein data analysis

PubMed Central

Chowdhury, Md Rabiul Hossain; Bhuiyan, Md IqbalKaiser; Saha, Ayan; Mosleh, Ivan MHAI; Mondol, Sobuj; Ahmed, C M Sabbir

2014-01-01

Purpose Streptococcus sanguinis is a Gram-positive, facultative aerobic bacterium that is a member of the viridans streptococcus group. It is found in human mouths in dental plaque, which accounts for both dental cavities and bacterial endocarditis, and which entails a mortality rate of 25%. Although a range of remedial mediators have been found to control this organism, the effectiveness of agents such as penicillin, amoxicillin, trimethoprim–sulfamethoxazole, and erythromycin, was observed. The emphasis of this investigation was on finding substitute and efficient remedial approaches for the total destruction of this bacterium. Materials and methods In this computational study, various databases and online software were used to ascertain some specific targets of S. sanguinis. Particularly, the Kyoto Encyclopedia of Genes and Genomes databases were applied to determine human nonhomologous proteins, as well as the metabolic pathways involved with those proteins. Different software such as Phyre2, CastP, DoGSiteScorer, the Protein Function Predictor server, and STRING were utilized to evaluate the probable active drug binding site with its known function and protein–protein interaction. Results In this study, among 218 essential proteins of this pathogenic bacterium, 81 nonhomologous proteins were accrued, and 15 proteins that are unique in several metabolic pathways of S. sanguinis were isolated through metabolic pathway analysis. Furthermore, four essentially membrane-bound unique proteins that are involved in distinct metabolic pathways were revealed by this research. Active sites and druggable pockets of these selected proteins were investigated with bioinformatic techniques. In addition, this study also mentions the activity of those proteins, as well as their interactions with the other proteins. Conclusion Our findings helped to identify the type of protein to be considered as an efficient drug target. This study will pave the way for researchers to develop and discover more effective and specific therapeutic agents against S. sanguinis. PMID:25473301

Identification and analysis of potential targets in Streptococcus sanguinis using computer aided protein data analysis.

PubMed

Chowdhury, Md Rabiul Hossain; Bhuiyan, Md IqbalKaiser; Saha, Ayan; Mosleh, Ivan Mhai; Mondol, Sobuj; Ahmed, C M Sabbir

2014-01-01

Streptococcus sanguinis is a Gram-positive, facultative aerobic bacterium that is a member of the viridans streptococcus group. It is found in human mouths in dental plaque, which accounts for both dental cavities and bacterial endocarditis, and which entails a mortality rate of 25%. Although a range of remedial mediators have been found to control this organism, the effectiveness of agents such as penicillin, amoxicillin, trimethoprim-sulfamethoxazole, and erythromycin, was observed. The emphasis of this investigation was on finding substitute and efficient remedial approaches for the total destruction of this bacterium. In this computational study, various databases and online software were used to ascertain some specific targets of S. sanguinis. Particularly, the Kyoto Encyclopedia of Genes and Genomes databases were applied to determine human nonhomologous proteins, as well as the metabolic pathways involved with those proteins. Different software such as Phyre2, CastP, DoGSiteScorer, the Protein Function Predictor server, and STRING were utilized to evaluate the probable active drug binding site with its known function and protein-protein interaction. In this study, among 218 essential proteins of this pathogenic bacterium, 81 nonhomologous proteins were accrued, and 15 proteins that are unique in several metabolic pathways of S. sanguinis were isolated through metabolic pathway analysis. Furthermore, four essentially membrane-bound unique proteins that are involved in distinct metabolic pathways were revealed by this research. Active sites and druggable pockets of these selected proteins were investigated with bioinformatic techniques. In addition, this study also mentions the activity of those proteins, as well as their interactions with the other proteins. Our findings helped to identify the type of protein to be considered as an efficient drug target. This study will pave the way for researchers to develop and discover more effective and specific therapeutic agents against S. sanguinis.

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

PubMed

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

A new approach to systematization of the management of paper-based clinical pathways.

PubMed

Wakamiya, Shunji; Yamauchi, Kazunobu

2006-05-01

The present study was performed to explore a new approach to systematization of the management of paper-based clinical pathways by developing a new system requiring little capital investment. A new system was developed and incorporated into an existing network at a hospital with a paper-based clinical pathway management system. The effectiveness of this new system was examined by comparing the management efficiency of clinical pathways before and after its introduction, and by comparison of the new system with other such systems currently in place at other medical institutions with regard to efficiency. In addition, the acceptability of the system for other medical institutions was examined by providing free access to the software on the Internet. The development costs of the new system were low. Although the new system has been in place for more than 3 years, no problems have yet been encountered in either the existing network system or in the management system itself. The new system allows the processing of statistics and analysis of circulation or variance automatically, neither of which were possible in the original paper-based system. We provided open access to the system as free software on the Internet, and it has since been downloaded by many medical institutions and enterprises in Japan. This system is very useful for institutions where it is difficult to introduce expensive new systems for systematic management of clinical pathways, such as electronic medical records, because of problems regarding capital or system management, and it may also be useful in other countries.

Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

PubMed

Anandkumar, Balakrishna; Haga, Steve W; Wu, Hui-Fen

2014-02-01

The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.

A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

PubMed

Scarbrough, Peter M; Weber, Rachel Palmieri; Iversen, Edwin S; Brhane, Yonathan; Amos, Christopher I; Kraft, Peter; Hung, Rayjean J; Sellers, Thomas A; Witte, John S; Pharoah, Paul; Henderson, Brian E; Gruber, Stephen B; Hunter, David J; Garber, Judy E; Joshi, Amit D; McDonnell, Kevin; Easton, Doug F; Eeles, Ros; Kote-Jarai, Zsofia; Muir, Kenneth; Doherty, Jennifer A; Schildkraut, Joellen M

2016-01-01

DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility. We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling. We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10(-6)), MSH5 (P < 5.09 × 10(-6)), and BRCA2 (P = 5.70 × 10(-6)). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways. Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways. Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. ©2015 American Association for Cancer Research.

T-cell lymphomas associated gene expression signature: Bioinformatics analysis based on gene expression Omnibus.

PubMed

Zhou, Lei-Lei; Xu, Xiao-Yue; Ni, Jie; Zhao, Xia; Zhou, Jian-Wei; Feng, Ji-Feng

2018-06-01

Due to the low incidence and the heterogeneity of subtypes, the biological process of T-cell lymphomas is largely unknown. Although many genes have been detected in T-cell lymphomas, the role of these genes in biological process of T-cell lymphomas was not further analyzed. Two qualified datasets were downloaded from Gene Expression Omnibus database. The biological functions of differentially expressed genes were evaluated by gene ontology enrichment and KEGG pathway analysis. The network for intersection genes was constructed by the cytoscape v3.0 software. Kaplan-Meier survival curves and log-rank test were employed to assess the association between differentially expressed genes and clinical characters. The intersection mRNAs were proved to be associated with fundamental processes of T-cell lymphoma cells. These intersection mRNAs were involved in the activation of some cancer-related pathways, including PI3K/AKT, Ras, JAK-STAT, and NF-kappa B signaling pathway. PDGFRA, CXCL12, and CCL19 were the most significant central genes in the signal-net analysis. The results of survival analysis are not entirely credible. Our findings uncovered aberrantly expressed genes and a complex RNA signal network in T-cell lymphomas and indicated cancer-related pathways involved in disease initiation and progression, providing a new insight for biotargeted therapy in T-cell lymphomas. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Learning cellular sorting pathways using protein interactions and sequence motifs.

PubMed

Lin, Tien-Ho; Bar-Joseph, Ziv; Murphy, Robert F

2011-11-01

Proper subcellular localization is critical for proteins to perform their roles in cellular functions. Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination. The pathway a protein is transported through is determined by carrier proteins that bind to specific sequence motifs. In this article, we present a new method that integrates protein interaction and sequence motif data to model how proteins are sorted through these sorting pathways. We use a hidden Markov model (HMM) to represent protein sorting pathways. The model is able to determine intermediate sorting states and to assign carrier proteins and motifs to the sorting pathways. In simulation studies, we show that the method can accurately recover an underlying sorting model. Using data for yeast, we show that our model leads to accurate prediction of subcellular localization. We also show that the pathways learned by our model recover many known sorting pathways and correctly assign proteins to the path they utilize. The learned model identified new pathways and their putative carriers and motifs and these may represent novel protein sorting mechanisms. Supplementary results and software implementation are available from http://murphylab.web.cmu.edu/software/2010_RECOMB_pathways/.

Pig immune response to general stimulus and to porcine reproductive and respiratory syndrome virus infection: a meta-analysis approach

PubMed Central

2013-01-01

Background The availability of gene expression data that corresponds to pig immune response challenges provides compelling material for the understanding of the host immune system. Meta-analysis offers the opportunity to confirm and expand our knowledge by combining and studying at one time a vast set of independent studies creating large datasets with increased statistical power. In this study, we performed two meta-analyses of porcine transcriptomic data: i) scrutinized the global immune response to different challenges, and ii) determined the specific response to Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) infection. To gain an in-depth knowledge of the pig response to PRRSV infection, we used an original approach comparing and eliminating the common genes from both meta-analyses in order to identify genes and pathways specifically involved in the PRRSV immune response. The software Pointillist was used to cope with the highly disparate data, circumventing the biases generated by the specific responses linked to single studies. Next, we used the Ingenuity Pathways Analysis (IPA) software to survey the canonical pathways, biological functions and transcription factors found to be significantly involved in the pig immune response. We used 779 chips corresponding to 29 datasets for the pig global immune response and 279 chips obtained from 6 datasets for the pig response to PRRSV infection, respectively. Results The pig global immune response analysis showed interconnected canonical pathways involved in the regulation of translation and mitochondrial energy metabolism. Biological functions revealed in this meta-analysis were centred around translation regulation, which included protein synthesis, RNA-post transcriptional gene expression and cellular growth and proliferation. Furthermore, the oxidative phosphorylation and mitochondria dysfunctions, associated with stress signalling, were highly regulated. Transcription factors such as MYCN, MYC and NFE2L2 were found in this analysis to be potentially involved in the regulation of the immune response. The host specific response to PRRSV infection engendered the activation of well-defined canonical pathways in response to pathogen challenge such as TREM1, toll-like receptor and hyper-cytokinemia/ hyper-chemokinemia signalling. Furthermore, this analysis brought forth the central role of the crosstalk between innate and adaptive immune response and the regulation of anti-inflammatory response. The most significant transcription factor potentially involved in this analysis was HMGB1, which is required for the innate recognition of viral nucleic acids. Other transcription factors like interferon regulatory factors IRF1, IRF3, IRF5 and IRF8 were also involved in the pig specific response to PRRSV infection. Conclusions This work reveals key genes, canonical pathways and biological functions involved in the pig global immune response to diverse challenges, including PRRSV infection. The powerful statistical approach led us to consolidate previous findings as well as to gain new insights into the pig immune response either to common stimuli or specifically to PRRSV infection. PMID:23552196

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.

Molecular modeling, simulation and virtual screening of MurD ligase protein from Salmonella typhimurium LT2.

PubMed

Samal, Himanshu Bhusan; Das, Jugal Kishore; Mahapatra, Rajani Kanta; Suar, Mrutyunjay

2015-01-01

The Mur enzymes of the peptidoglycan biosynthesis pathway constitute ideal targets for the design of new classes of antimicrobial inhibitors in Gram-negative bacteria. We built a homology model of MurD of Salmonella typhimurium LT2 using MODELLER (9v12) software. 'The homology model was subjected to energy minimization by molecular dynamics (MD) simulation study with GROMACS software for a simulation time of 20 ns in water environment. The model was subjected for virtual screening study from the Zinc Database using Dockblaster software. Inhibition assay for the best inhibitor, 3-(amino methyl)-n-(4-methoxyphenyl) aniline, by flow cytometric analysis revealed the effective inhibition of peptidoglycan biosynthesis. Results from this study provide new insights for the molecular understanding and development of new antibacterial drugs against the pathogen. Copyright © 2015 Elsevier Inc. All rights reserved.

Key genes and pathways in measles and their interaction with environmental chemicals

PubMed Central

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-01-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles. PMID:29805511

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.

Exploratory Application of Neuropharmacometabolomics in Severe Childhood Traumatic Brain Injury.

PubMed

Hagos, Fanuel T; Empey, Philip E; Wang, Pengcheng; Ma, Xiaochao; Poloyac, Samuel M; Bayır, Hülya; Kochanek, Patrick M; Bell, Michael J; Clark, Robert S B

2018-05-07

To employ metabolomics-based pathway and network analyses to evaluate the cerebrospinal fluid metabolome after severe traumatic brain injury in children and the capacity of combination therapy with probenecid and N-acetylcysteine to impact glutathione-related and other pathways and networks, relative to placebo treatment. Analysis of cerebrospinal fluid obtained from children enrolled in an Institutional Review Board-approved, randomized, placebo-controlled trial of a combination of probenecid and N-acetylcysteine after severe traumatic brain injury (Trial Registration NCT01322009). Thirty-six-bed PICU in a university-affiliated children's hospital. Twelve children 2-18 years old after severe traumatic brain injury and five age-matched control subjects. Probenecid (25 mg/kg) and N-acetylcysteine (140 mg/kg) or placebo administered via naso/orogastric tube. The cerebrospinal fluid metabolome was analyzed in samples from traumatic brain injury patients 24 hours after the first dose of drugs or placebo and control subjects. Feature detection, retention time, alignment, annotation, and principal component analysis and statistical analysis were conducted using XCMS-online. The software "mummichog" was used for pathway and network analyses. A two-component principal component analysis revealed clustering of each of the groups, with distinct metabolomics signatures. Several novel pathways with plausible mechanistic involvement in traumatic brain injury were identified. A combination of metabolomics and pathway/network analyses showed that seven glutathione-centered pathways and two networks were enriched in the cerebrospinal fluid of traumatic brain injury patients treated with probenecid and N-acetylcysteine versus placebo-treated patients. Several additional pathways/networks consisting of components that are known substrates of probenecid-inhibitable transporters were also identified, providing additional mechanistic validation. This proof-of-concept neuropharmacometabolomics assessment reveals alterations in known and previously unidentified metabolic pathways and supports therapeutic target engagement of the combination of probenecid and N-acetylcysteine treatment after severe traumatic brain injury in children.

Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity.

PubMed

Aggio, Raphael B M; Ruggiero, Katya; Villas-Bôas, Silas Granato

2010-12-01

Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes. Here, we present a new algorithm Pathway Activity Profiling (PAPi) with which we are able to compare metabolic pathway activities from metabolite profiles. The applicability and potential of PAPi was demonstrated using a previously published data from the yeast Saccharomyces cerevisiae. PAPi was able to support the biological interpretations of the previously published observations and, in addition, generated new hypotheses in a straightforward manner. However, PAPi is time consuming to perform manually. Thus, we also present here a new R-software package (PAPi) which implements the PAPi algorithm and facilitates its usage to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, the PAPi package calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. PAPi also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity. These datasets are available in http://www.4shared.com/file/hTWyndYU/extra.html and http://www.4shared.com/file/VbQIIDeu/intra.html. PAPi package is available in: http://www.4shared.com/file/s0uIYWIg/PAPi_10.html s.villas-boas@auckland.ac.nz Supplementary data are available at Bioinformatics online.

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

Karp, Peter D.

Pathway Tools is a systems-biology software package written by SRI International (SRI) that produces Pathway/Genome Databases (PGDBs) for organisms with a sequenced genome. Pathway Tools also provides a wide range of capabilities for analyzing predicted metabolic networks and user-generated omics data. More than 5,000 academic, industrial, and government groups have licensed Pathway Tools. This user community includes researchers at all three DOE bioenergy centers, as well as academic and industrial metabolic engineering (ME) groups. An integral part of the Pathway Tools software is MetaCyc, a large, multiorganism database of metabolic pathways and enzymes that SRI and its academic collaborators manuallymore » curate. This project included two main goals: I. Enhance the MetaCyc content of bioenergy-related enzymes and pathways. II. Develop computational tools for engineering metabolic pathways that satisfy specified design goals, in particular for bioenergy-related pathways. In part I, SRI proposed to significantly expand the coverage of bioenergy-related metabolic information in MetaCyc, followed by the generation of organism-specific PGDBs for all energy-relevant organisms sequenced at the DOE Joint Genome Institute (JGI). Part I objectives included: 1: Expand the content of MetaCyc to include bioenergy-related enzymes and pathways. 2: Enhance the Pathway Tools software to enable display of complex polymer degradation processes. 3: Create new PGDBs for the energy-related organisms sequenced by JGI, update existing PGDBs with new MetaCyc content, and make these data available to JBEI via the BioCyc website. In part II, SRI proposed to develop an efficient computational tool for the engineering of metabolic pathways. Part II objectives included: 4: Develop computational tools for generating metabolic pathways that satisfy specified design goals, enabling users to specify parameters such as starting and ending compounds, and preferred or disallowed intermediate compounds. The pathways were to be generated using metabolic reactions from a reference database (DB). 5: Develop computational tools for ranking the pathways generated in objective (4) according to their optimality. The ranking criteria include stoichiometric yield, the number and cost of additional inputs and the cofactor compounds required by the pathway, pathway length, and pathway energetics. 6: Develop tools for visualizing generated pathways to facilitate the evaluation of a large space of generated pathways.« less

BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes.

PubMed

Gao, Junhui; Li, Li; Wu, Xiaolin; Wei, Dong-Qing

2012-03-01

BioNetSim, a Petri net-based software for modeling and simulating biochemistry processes, is developed, whose design and implement are presented in this paper, including logic construction, real-time access to KEGG (Kyoto Encyclopedia of Genes and Genomes), and BioModel database. Furthermore, glycolysis is simulated as an example of its application. BioNetSim is a helpful tool for researchers to download data, model biological network, and simulate complicated biochemistry processes. Gene regulatory networks, metabolic pathways, signaling pathways, and kinetics of cell interaction are all available in BioNetSim, which makes modeling more efficient and effective. Similar to other Petri net-based softwares, BioNetSim does well in graphic application and mathematic construction. Moreover, it shows several powerful predominances. (1) It creates models in database. (2) It realizes the real-time access to KEGG and BioModel and transfers data to Petri net. (3) It provides qualitative analysis, such as computation of constants. (4) It generates graphs for tracing the concentration of every molecule during the simulation processes.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

PubMed

Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

2015-06-05

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

Computational knowledge integration in biopharmaceutical research.

PubMed

Ficenec, David; Osborne, Mark; Pradines, Joel; Richards, Dan; Felciano, Ramon; Cho, Raymond J; Chen, Richard O; Liefeld, Ted; Owen, James; Ruttenberg, Alan; Reich, Christian; Horvath, Joseph; Clark, Tim

2003-09-01

An initiative to increase biopharmaceutical research productivity by capturing, sharing and computationally integrating proprietary scientific discoveries with public knowledge is described. This initiative involves both organisational process change and multiple interoperating software systems. The software components rely on mutually supporting integration techniques. These include a richly structured ontology, statistical analysis of experimental data against stored conclusions, natural language processing of public literature, secure document repositories with lightweight metadata, web services integration, enterprise web portals and relational databases. This approach has already begun to increase scientific productivity in our enterprise by creating an organisational memory (OM) of internal research findings, accessible on the web. Through bringing together these components it has also been possible to construct a very large and expanding repository of biological pathway information linked to this repository of findings which is extremely useful in analysis of DNA microarray data. This repository, in turn, enables our research paradigm to be shifted towards more comprehensive systems-based understandings of drug action.

Inter-species pathway perturbation prediction via data-driven detection of functional homology.

PubMed

Hafemeister, Christoph; Romero, Roberto; Bilal, Erhan; Meyer, Pablo; Norel, Raquel; Rhrissorrakrai, Kahn; Bonneau, Richard; Tarca, Adi L

2015-02-15

Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER Species Translation Challenge, where 52 stimuli were applied to both human and rat cells and perturbed pathways were identified. In the Inter-species Pathway Perturbation Prediction sub-challenge, multiple teams proposed methods to use rat transcription data from 26 stimuli to predict human gene set and pathway activity under the same perturbations. Submissions were evaluated using three performance metrics on data from the remaining 26 stimuli. We present two approaches, ranked second in this challenge, that do not rely on sequence-based orthology between rat and human genes to translate pathway perturbation state but instead identify transcriptional response orthologs across a set of training conditions. The translation from rat to human accomplished by these so-called direct methods is not dependent on the particular analysis method used to identify perturbed gene sets. In contrast, machine learning-based methods require performing a pathway analysis initially and then mapping the pathway activity between organisms. Unlike most machine learning approaches, direct methods can be used to predict the activation of a human pathway for a new (test) stimuli, even when that pathway was never activated by a training stimuli. Gene expression data are available from ArrayExpress (accession E-MTAB-2091), while software implementations are available from http://bioinformaticsprb.med.wayne.edu?p=50 and http://goo.gl/hJny3h. christoph.hafemeister@nyu.edu or atarca@med.wayne.edu. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Advanced Data Visualization in Astrophysics: The X3D Pathway

NASA Astrophysics Data System (ADS)

Vogt, Frédéric P. A.; Owen, Chris I.; Verdes-Montenegro, Lourdes; Borthakur, Sanchayeeta

2016-02-01

Most modern astrophysical data sets are multi-dimensional; a characteristic that can nowadays generally be conserved and exploited scientifically during the data reduction/simulation and analysis cascades. However, the same multi-dimensional data sets are systematically cropped, sliced, and/or projected to printable two-dimensional diagrams at the publication stage. In this article, we introduce the concept of the “X3D pathway” as a mean of simplifying and easing the access to data visualization and publication via three-dimensional (3D) diagrams. The X3D pathway exploits the facts that (1) the X3D 3D file format lies at the center of a product tree that includes interactive HTML documents, 3D printing, and high-end animations, and (2) all high-impact-factor and peer-reviewed journals in astrophysics are now published (some exclusively) online. We argue that the X3D standard is an ideal vector for sharing multi-dimensional data sets because it provides direct access to a range of different data visualization techniques, is fully open source, and is a well-defined standard from the International Organization for Standardization. Unlike other earlier propositions to publish multi-dimensional data sets via 3D diagrams, the X3D pathway is not tied to specific software (prone to rapid and unexpected evolution), but instead is compatible with a range of open-source software already in use by our community. The interactive HTML branch of the X3D pathway is also actively supported by leading peer-reviewed journals in the field of astrophysics. Finally, this article provides interested readers with a detailed set of practical astrophysical examples designed to act as a stepping stone toward the implementation of the X3D pathway for any other data set.

A proposed model for the flowering signaling pathway of sugarcane under photoperiodic control.

PubMed

Coelho, C P; Costa Netto, A P; Colasanti, J; Chalfun-Júnior, A

2013-04-25

Molecular analysis of floral induction in Arabidopsis has identified several flowering time genes related to 4 response networks defined by the autonomous, gibberellin, photoperiod, and vernalization pathways. Although grass flowering processes include ancestral functions shared by both mono- and dicots, they have developed their own mechanisms to transmit floral induction signals. Despite its high production capacity and its important role in biofuel production, almost no information is available about the flowering process in sugarcane. We searched the Sugarcane Expressed Sequence Tags database to look for elements of the flowering signaling pathway under photoperiodic control. Sequences showing significant similarity to flowering time genes of other species were clustered, annotated, and analyzed for conserved domains. Multiple alignments comparing the sequences found in the sugarcane database and those from other species were performed and their phylogenetic relationship assessed using the MEGA 4.0 software. Electronic Northerns were run with Cluster and TreeView programs, allowing us to identify putative members of the photoperiod-controlled flowering pathway of sugarcane.

Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma.

PubMed

Wu, Xiya; Zhang, Wei; Hu, Yunhua; Yi, Xianghua

2015-01-01

The purpose of this work was to explore the systematic molecular mechanism of lung adenocarcinoma and gain a deeper insight into it. Comprehensive bioinformatics methods were applied. Initially, significant differentially expressed genes (DEGs) were analyzed from the Affymetrix microarray data (GSE27262) deposited in the Gene Expression Omnibus (GEO). Subsequently, gene ontology (GO) analysis was performed using online Database for Annotation, Visualization and Integration Discovery (DAVID) software. Finally, significant pathway crosstalk was investigated based on the information derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. According to our results, the N-terminal globular domain of the type X collagen (COL10A1) gene and transmembrane protein 100 (TMEM100) gene were identified to be the most significant DEGs in tumor tissue compared with the adjacent normal tissues. The main GO categories were biological process, cellular component and molecular function. In addition, the crosstalk was significantly different between non-small cell lung cancer pathways and inositol phosphate metabolism pathway, focal adhesion signal pathway, vascular smooth muscle contraction signal pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway and calcium signaling pathway in tumor. Dysfunctional genes and pathways may play key roles in the progression and development of lung adenocarcinoma. Our data provide a systematic perspective for understanding this mechanism and may be helpful in discovering an effective treatment for lung adenocarcinoma.

Learning Cellular Sorting Pathways Using Protein Interactions and Sequence Motifs

PubMed Central

Lin, Tien-Ho; Bar-Joseph, Ziv

2011-01-01

Abstract Proper subcellular localization is critical for proteins to perform their roles in cellular functions. Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination. The pathway a protein is transported through is determined by carrier proteins that bind to specific sequence motifs. In this article, we present a new method that integrates protein interaction and sequence motif data to model how proteins are sorted through these sorting pathways. We use a hidden Markov model (HMM) to represent protein sorting pathways. The model is able to determine intermediate sorting states and to assign carrier proteins and motifs to the sorting pathways. In simulation studies, we show that the method can accurately recover an underlying sorting model. Using data for yeast, we show that our model leads to accurate prediction of subcellular localization. We also show that the pathways learned by our model recover many known sorting pathways and correctly assign proteins to the path they utilize. The learned model identified new pathways and their putative carriers and motifs and these may represent novel protein sorting mechanisms. Supplementary results and software implementation are available from http://murphylab.web.cmu.edu/software/2010_RECOMB_pathways/. PMID:21999284

Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki)

PubMed Central

2013-01-01

Background The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. Results We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki. Conclusions Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools. PMID:24209455

Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki).

PubMed

Sturgill, David; Malone, John H; Sun, Xia; Smith, Harold E; Rabinow, Leonard; Samson, Marie-Laure; Oliver, Brian

2013-11-09

The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki. Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools.

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

Identification and analysis of chemical constituents and rat serum metabolites in Suan-Zao-Ren granule using ultra high performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with multiple data processing approaches.

PubMed

Du, Yiyang; He, Bosai; Li, Qing; He, Jiao; Wang, Di; Bi, Kaishun

2017-07-01

Suan-Zao-Ren granule is widely used to treat insomnia in China. However, because of the complexity and diversity of the chemical compositions in traditional Chinese medicine formula, the comprehensive analysis of constituents in vitro and in vivo is rather difficult. In our study, an ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and the PeakView® software, which uses multiple data processing approaches including product ion filter, neutral loss filter, and mass defect filter, method was developed to characterize the ingredients and rat serum metabolites in Suan-Zao-Ren granule. A total of 101 constituents were detected in vitro. Under the same analysis conditions, 68 constituents were characterized in rat serum, including 35 prototype components and 33 metabolites. The metabolic pathways of main components were also illustrated. Among them, the metabolic pathways of timosaponin AI were firstly revealed. The bioactive compounds mainly underwent the phase I metabolic pathways including hydroxylation, oxidation, hydrolysis, and phase II metabolic pathways including sulfate conjugation, glucuronide conjugation, cysteine conjugation, acetycysteine conjugation, and glutathione conjugation. In conclusion, our results showed that this analysis approach was extremely useful for the in-depth pharmacological research of Suan-Zao-Ren granule and provided a chemical basis for its rational. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MicroRNA profiling in intraocular medulloepitheliomas.

PubMed

Edward, Deepak P; Alkatan, Hind; Rafiq, Qundeel; Eberhart, Charles; Al Mesfer, Saleh; Ghazi, Nicola; Al Safieh, Leen; Kondkar, Altaf A; Abu Amero, Khaled K

2015-01-01

To study the differential expression of microRNA (miRNA) profiles between intraocular medulloepithelioma (ME) and normal control tissue (CT). Total RNA was extracted from formalin fixed paraffin embedded (FFPE) intraocular ME (n=7) and from age matched ciliary body controls (n=8). The clinical history and phenotype was recorded. MiRNA profiles were determined using the Affymetrix GeneChip miRNA Arrays analyzed using expression console 1.3 software. Validation of significantly dysregulated miRNA was confirmed by quantitative real-time PCR. The web-based DNA Intelligent Analysis (DIANA)-miRPath v2.0 was used to perform enrichment analysis of differentially expressed (DE) miRNA gene targets in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The pathologic evaluation revealed one benign (benign non-teratoid, n=1) and six malignant tumors (malignant teratoid, n=2; malignant non-teratoid, n = 4). A total of 88 miRNAs were upregulated and 43 miRNAs were downregulated significantly (P<0.05) in the tumor specimens. Many of these significantly dysregulated miRNAs were known to play various roles in carcinogenesis and tumor behavior. RT-PCR validated three significantly upregulated miRNAs and three significantly downregulated miRNAs namely miR-217, miR-216a, miR-216b, miR-146a, miR-509-3p and miR-211. Many DE miRNAs that were significant in ME tumors showed dysregulation in retinoblastoma, glioblastoma, and precursor, normal and reactive human cartilage. Enriched pathway analysis suggested a significant association of upregulated miRNAs with 15 pathways involved in prion disease and several types of cancer. The pathways involving significantly downregulated miRNAs included the toll-like receptor (TLR) (p<4.36E-16) and Nuclear Factor kappa B (NF-κB) signaling pathways (p<9.00E-06). We report significantly dysregulated miRNAs in intraocular ME tumors, which exhibited abnormal profiles in other cancers as well such as retinoblastoma and glioblastoma. Pathway analysis of all dysregulated miRNAs shared commonalities with other cancer pathways.

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.

PubMed

Quigley, David A; Kandyba, Eve; Huang, Phillips; Halliwill, Kyle D; Sjölund, Jonas; Pelorosso, Facundo; Wong, Christine E; Hirst, Gillian L; Wu, Di; Delrosario, Reyno; Kumar, Atul; Balmain, Allan

2016-07-26

Inherited germline polymorphisms can cause gene expression levels in normal tissues to differ substantially between individuals. We present an analysis of the genetic architecture of normal adult skin from 470 genetically unique mice, demonstrating the effect of germline variants, skin tissue location, and perturbation by exogenous inflammation or tumorigenesis on gene signaling pathways. Gene networks related to specific cell types and signaling pathways, including sonic hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins, differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for expression quantitative trait loci (eQTL) network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

Mutation analysis of 13 driver genes of colorectal cancer-related pathways in Taiwanese patients

PubMed Central

Chang, Yuli Christine; Chang, Jan-Gowth; Liu, Ta-Chih; Lin, Chien-Yu; Yang, Shu-Fen; Ho, Cheng-Mao; Chen, William Tzu-Liang; Chang, Ya-Sian

2016-01-01

AIM: To investigate the driver gene mutations associated with colorectal cancer (CRC) in the Taiwanese population. METHODS: In this study, 103 patients with CRC were evaluated. The samples consisted of 66 men and 37 women with a median age of 59 years and an age range of 26-86 years. We used high-resolution melting analysis (HRM) and direct DNA sequencing to characterize the mutations in 13 driver genes of CRC-related pathways. The HRM assays were conducted using the LightCycler® 480 Instrument provided with the software LightCycler® 480 Gene Scanning Software Version 1.5. We also compared the clinicopathological data of CRC patients with the driver gene mutation status. RESULTS: Of the 103 patients evaluated, 73.79% had mutations in one of the 13 driver genes. We discovered 18 novel mutations in APC, MLH1, MSH2, PMS2, SMAD4 and TP53 that have not been previously reported. Additionally, we found 16 de novo mutations in APC, BMPR1A, MLH1, MSH2, MSH6, MUTYH and PMS2 in cancerous tissues previously reported in the dbSNP database; however, these mutations could not be detected in peripheral blood cells. The APC mutation correlates with lymph node metastasis (34.69% vs 12.96%, P = 0.009) and cancer stage (34.78% vs 14.04%, P = 0.013). No association was observed between other driver gene mutations and clinicopathological features. Furthermore, having two or more driver gene mutations correlates with the degree of lymph node metastasis (42.86% vs 24.07%, P = 0.043). CONCLUSION: Our findings confirm the importance of 13 CRC-related pathway driver genes in the development of CRC in Taiwanese patients. PMID:26900293

Mutation analysis of 13 driver genes of colorectal cancer-related pathways in Taiwanese patients.

PubMed

Chang, Yuli Christine; Chang, Jan-Gowth; Liu, Ta-Chih; Lin, Chien-Yu; Yang, Shu-Fen; Ho, Cheng-Mao; Chen, William Tzu-Liang; Chang, Ya-Sian

2016-02-21

To investigate the driver gene mutations associated with colorectal cancer (CRC) in the Taiwanese population. In this study, 103 patients with CRC were evaluated. The samples consisted of 66 men and 37 women with a median age of 59 years and an age range of 26-86 years. We used high-resolution melting analysis (HRM) and direct DNA sequencing to characterize the mutations in 13 driver genes of CRC-related pathways. The HRM assays were conducted using the LightCycler® 480 Instrument provided with the software LightCycler® 480 Gene Scanning Software Version 1.5. We also compared the clinicopathological data of CRC patients with the driver gene mutation status. Of the 103 patients evaluated, 73.79% had mutations in one of the 13 driver genes. We discovered 18 novel mutations in APC, MLH1, MSH2, PMS2, SMAD4 and TP53 that have not been previously reported. Additionally, we found 16 de novo mutations in APC, BMPR1A, MLH1, MSH2, MSH6, MUTYH and PMS2 in cancerous tissues previously reported in the dbSNP database; however, these mutations could not be detected in peripheral blood cells. The APC mutation correlates with lymph node metastasis (34.69% vs 12.96%, P = 0.009) and cancer stage (34.78% vs 14.04%, P = 0.013). No association was observed between other driver gene mutations and clinicopathological features. Furthermore, having two or more driver gene mutations correlates with the degree of lymph node metastasis (42.86% vs 24.07%, P = 0.043). Our findings confirm the importance of 13 CRC-related pathway driver genes in the development of CRC in Taiwanese patients.

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.

Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

PubMed

Chen, Long; Zhang, Chunhua; Wang, Yanling; Li, Yuqian; Han, Qiaoqiao; Yang, Huixin; Zhu, Yuechun

2017-08-01

Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, and recently, G6PD has been associated with diseases including inflammation and cancer. The aim of the present study was to conduct a search of the National Center for Biotechnology Information PubMed library for articles discussing G6PD. Genes that were identified to be associated with G6PD were recorded, and the frequency at which each gene appeared was calculated. Gene ontology (GO), pathway and network analyses were then performed. A total of 98 G6PD‑associated genes and 33 microRNAs (miRNAs) that potentially regulate G6PD were identified. The 98 G6PD‑associated genes were then sub‑classified into three functional groups by GO analysis, followed by analysis of function, pathway, network, and disease association. Out of the 47 signaling pathways identified, seven were significantly correlated with G6PD‑associated genes. At least two out of four independent programs identified the 33 miRNAs that were predicted to target G6PD. miR‑1207‑5P, miR‑1 and miR‑125a‑5p were predicted by all four software programs to target G6PD. The results of the present study revealed that dysregulation of G6PD was associated with cancer, autoimmune diseases, and oxidative stress‑induced disorders. These results revealed the potential roles of G6PD‑regulated signaling and metabolic pathways in the etiology of these diseases.

Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing

PubMed Central

Chen, Long; Zhang, Chunhua; Wang, Yanling; Li, Yuqian; Han, Qiaoqiao; Yang, Huixin; Zhu, Yuechun

2017-01-01

Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, and recently, G6PD has been associated with diseases including inflammation and cancer. The aim of the present study was to conduct a search of the National Center for Biotechnology Information PubMed library for articles discussing G6PD. Genes that were identified to be associated with G6PD were recorded, and the frequency at which each gene appeared was calculated. Gene ontology (GO), pathway and network analyses were then performed. A total of 98 G6PD-associated genes and 33 microRNAs (miRNAs) that potentially regulate G6PD were identified. The 98 G6PD-associated genes were then sub-classified into three functional groups by GO analysis, followed by analysis of function, pathway, network, and disease association. Out of the 47 signaling pathways identified, seven were significantly correlated with G6PD-associated genes. At least two out of four independent programs identified the 33 miRNAs that were predicted to target G6PD. miR-1207-5P, miR-1 and miR-125a-5p were predicted by all four software programs to target G6PD. The results of the present study revealed that dysregulation of G6PD was associated with cancer, autoimmune diseases, and oxidative stress-induced disorders. These results revealed the potential roles of G6PD-regulated signaling and metabolic pathways in the etiology of these diseases. PMID:28627690

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

Pure mechanistic analysis of additive neuroprotective effects between baicalin and jasminoidin in ischemic stroke mice.

PubMed

Wang, Peng-Qian; Liu, Qiong; Xu, Wen-Juan; Yu, Ya-Nan; Zhang, Ying-Ying; Li, Bing; Liu, Jun; Wang, Zhong

2018-06-01

Both baicalin (BA) and jasminoidin (JA) are active ingredients in Chinese herb medicine Scutellaria baicalensis and Fructus gardeniae, respectively. They have been shown to exert additive neuroprotective action in ischemic stroke models. In this study we used transcriptome analysis to explore the pure therapeutic mechanisms of BA, JA and their combination (BJ) contributing to phenotype variation and reversal of pathological processes. Mice with middle cerebral artery obstruction were treated with BA, JA, their combination (BJ), or concha margaritifera (CM). Cerebral infarct volume was examined to determine the effect of these compounds on phenotype. Using the hippocampus microarray and ingenuity pathway analysis (IPA) software, we exacted the differentially expressed genes, networks, pathways, and functions in positive-phenotype groups (BA, JA and BJ) by comparing with the negative-phenotype group (CM). In the BA, JA, and BJ groups, a total of 7, 4, and 11 specific target molecules, 1, 1, and 4 networks, 51, 59, and 18 canonical pathways and 70, 53, and 64 biological functions, respectively, were identified. Pure therapeutic mechanisms of BA and JA were mainly overlapped in specific target molecules, functions and pathways, which were related to the nervous system, inflammation and immune response. The specific mechanisms of BA and JA were associated with apoptosis and cancer-related signaling and endocrine and hormone regulation, respectively. In the BJ group, novel target profiles distinct from mono-therapies were revealed, including 11 specific target molecules, 10 functions, and 10 pathways, the majority of which were related to a virus-mediated immune response. The pure additive effects between BA and JA were based on enhanced action in virus-mediated immune response. This pure mechanistic analysis may provide a clearer outline of the target profiles of multi-target compounds and combination therapies.

Educational utility of advanced three-dimensional virtual imaging in evaluating the anatomical configuration of the frontal recess.

PubMed

Agbetoba, Abib; Luong, Amber; Siow, Jin Keat; Senior, Brent; Callejas, Claudio; Szczygielski, Kornel; Citardi, Martin J

2017-02-01

Endoscopic sinus surgery represents a cornerstone in the professional development of otorhinolaryngology trainees. Mastery of these surgical skills requires an understanding of paranasal sinus and skull-base anatomy. The frontal sinus is associated with a wide range of variation and complex anatomical configuration, and thus represents an important challenge for all trainees performing endoscopic sinus surgery. Forty-five otorhinolaryngology trainees and 20 medical school students from 5 academic institutions were enrolled and randomized into 1 of 2 groups. Each subject underwent learning of frontal recess anatomy with both traditional 2-dimensional (2D) learning methods using a standard Digital Imaging and Communications in Medicine (DICOM) viewing software (RadiAnt Dicom Viewer Version 1.9.16) and 3-dimensional (3D) learning utilizing a novel preoperative virtual planning software (Scopis Building Blocks), with one half learning with the 2D method first and the other half learning with the 3D method first. Four questionnaires that included a total of 20 items were scored for subjects' self-assessment on knowledge of frontal recess and frontal sinus drainage pathway anatomy following each learned modality. A 2-sample Wilcoxon rank-sum test was used in the statistical analysis comparing the 2 groups. Most trainees (89%) believed that the virtual 3D planning software significantly improved their understanding of the spatial orientation of the frontal sinus drainage pathway. Incorporation of virtual 3D planning surgical software may help augment trainees' understanding and spatial orientation of the frontal recess and sinus anatomy. The potential increase in trainee proficiency and comprehension theoretically may translate to improved surgical skill and patient outcomes and in reduced surgical time. © 2016 ARS-AAOA, LLC.

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

Multilayer-omics analysis of renal cell carcinoma, including the whole exome, methylome and transcriptome.

PubMed

Arai, Eri; Sakamoto, Hiromi; Ichikawa, Hitoshi; Totsuka, Hirohiko; Chiku, Suenori; Gotoh, Masahiro; Mori, Taisuke; Nakatani, Tamao; Ohnami, Sumiko; Nakagawa, Tohru; Fujimoto, Hiroyuki; Wang, Linghua; Aburatani, Hiroyuki; Yoshida, Teruhiko; Kanai, Yae

2014-09-15

The aim of this study was to identify pathways that have a significant impact during renal carcinogenesis. Sixty-seven paired samples of both noncancerous renal cortex tissue and cancerous tissue from patients with clear cell renal cell carcinomas (RCCs) were subjected to whole-exome, methylome and transcriptome analyses using Agilent SureSelect All Exon capture followed by sequencing on an Illumina HiSeq 2000 platform, Illumina Infinium HumanMethylation27 BeadArray and Agilent SurePrint Human Gene Expression microarray, respectively. Sanger sequencing and quantitative reverse transcription-PCR were performed for technical verification. MetaCore software was used for pathway analysis. Somatic nonsynonymous single-nucleotide mutations, insertions/deletions and intragenic breaks of 2,153, 359 and 8 genes were detected, respectively. Mutations of GCN1L1, MED12 and CCNC, which are members of CDK8 mediator complex directly regulating β-catenin-driven transcription, were identified in 16% of the RCCs. Mutations of MACF1, which functions in the Wnt/β-catenin signaling pathway, were identified in 4% of the RCCs. A combination of methylome and transcriptome analyses further highlighted the significant role of the Wnt/β-catenin signaling pathway in renal carcinogenesis. Genetic aberrations and reduced expression of ERC2 and ABCA13 were frequent in RCCs, and MTOR mutations were identified as one of the major disrupters of cell signaling during renal carcinogenesis. Our results confirm that multilayer-omics analysis can be a powerful tool for revealing pathways that play a significant role in carcinogenesis. © 2014 The Authors. Published by Wiley Periodicals, Inc. on behalf of UICC.

Multilayer-omics analysis of renal cell carcinoma, including the whole exome, methylome and transcriptome

PubMed Central

Arai, Eri; Sakamoto, Hiromi; Ichikawa, Hitoshi; Totsuka, Hirohiko; Chiku, Suenori; Gotoh, Masahiro; Mori, Taisuke; Nakatani, Tamao; Ohnami, Sumiko; Nakagawa, Tohru; Fujimoto, Hiroyuki; Wang, Linghua; Aburatani, Hiroyuki; Yoshida, Teruhiko; Kanai, Yae

2014-01-01

The aim of this study was to identify pathways that have a significant impact during renal carcinogenesis. Sixty-seven paired samples of both noncancerous renal cortex tissue and cancerous tissue from patients with clear cell renal cell carcinomas (RCCs) were subjected to whole-exome, methylome and transcriptome analyses using Agilent SureSelect All Exon capture followed by sequencing on an Illumina HiSeq 2000 platform, Illumina Infinium HumanMethylation27 BeadArray and Agilent SurePrint Human Gene Expression microarray, respectively. Sanger sequencing and quantitative reverse transcription-PCR were performed for technical verification. MetaCore software was used for pathway analysis. Somatic nonsynonymous single-nucleotide mutations, insertions/deletions and intragenic breaks of 2,153, 359 and 8 genes were detected, respectively. Mutations of GCN1L1, MED12 and CCNC, which are members of CDK8 mediator complex directly regulating β-catenin-driven transcription, were identified in 16% of the RCCs. Mutations of MACF1, which functions in the Wnt/β-catenin signaling pathway, were identified in 4% of the RCCs. A combination of methylome and transcriptome analyses further highlighted the significant role of the Wnt/β-catenin signaling pathway in renal carcinogenesis. Genetic aberrations and reduced expression of ERC2 and ABCA13 were frequent in RCCs, and MTOR mutations were identified as one of the major disrupters of cell signaling during renal carcinogenesis. Our results confirm that multilayer-omics analysis can be a powerful tool for revealing pathways that play a significant role in carcinogenesis. PMID:24504440

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.

PubMed

Macedo, Nayana Damiani; Buzin, Aline Rodrigues; de Araujo, Isabela Bastos Binotti Abreu; Nogueira, Breno Valentim; de Andrade, Tadeu Uggere; Endringer, Denise Coutinho; Lenz, Dominik

2017-02-01

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation. A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software. Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively. Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Use of CellNetAnalyzer in biotechnology and metabolic engineering.

PubMed

von Kamp, Axel; Thiele, Sven; Hädicke, Oliver; Klamt, Steffen

2017-11-10

Mathematical models of the cellular metabolism have become an essential tool for the optimization of biotechnological processes. They help to obtain a systemic understanding of the metabolic processes in the used microorganisms and to find suitable genetic modifications maximizing the production performance. In particular, methods of stoichiometric and constraint-based modeling are frequently used in the context of metabolic and bioprocess engineering. Since metabolic networks can be complex and comprise hundreds or even thousands of metabolites and reactions, dedicated software tools are required for an efficient analysis. One such software suite is CellNetAnalyzer, a MATLAB package providing, among others, various methods for analyzing stoichiometric and constraint-based metabolic models. CellNetAnalyzer can be used via command-line based operations or via a graphical user interface with embedded network visualizations. Herein we will present key functionalities of CellNetAnalyzer for applications in biotechnology and metabolic engineering and thereby review constraint-based modeling techniques such as metabolic flux analysis, flux balance analysis, flux variability analysis, metabolic pathway analysis (elementary flux modes) and methods for computational strain design. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Developing Breast Cancer Program at Xavier: Genomic and Proteomic Analysis of Signaling Pathways Involved in Xenohormone and MEK5 Regulation of Breast Cancer

DTIC Science & Technology

2005-05-01

purification of intermediates to antibiotic medicines Hangzhou First Pharmaceutical Company Hangzhou, P. R. China Research chemist September 1987...NAME OF RESPONSIBLE PERSON OF ABSTRACT OF PAGES a. REPORT b. ABSTRACT c . THIS PAGE LTU 19b. TELEPHONE NUMBER (include area U U U 32 code) Standard Form...used as the second-dimension system c . BioRad PROTEAN® d. VersaDocTM Imaging Systems with PDQUEST software Preliminary results Using the newly installed

A multianalytical approach to evaluate the association of 55 SNPs in 28 genes with obesity risk in North Indian adults.

PubMed

Srivastava, Apurva; Mittal, Balraj; Prakash, Jai; Srivastava, Pranjal; Srivastava, Nimisha; Srivastava, Neena

2017-03-01

The aim of the study was to investigate the association of 55 SNPs in 28 genes with obesity risk in a North Indian population using a multianalytical approach. Overall, 480 subjects from the North Indian population were studied using strict inclusion/exclusion criteria. SNP Genotyping was carried out by Sequenom Mass ARRAY platform (Sequenom, San Diego, CA) and validated Taqman ® allelic discrimination (Applied Biosystems ® ). Statistical analyses were performed using SPSS software version 19.0, SNPStats, GMDR software (version 6) and GENEMANIA. Logistic regression analysis of 55 SNPs revealed significant associations (P < .05) of 49 SNPs with BMI linked obesity risk whereas the remaining 6 SNPs revealed no association (P > .05). The pathway-wise G-score revealed the significant role (P = .0001) of food intake-energy expenditure pathway genes. In CART analysis, the combined genotypes of FTO rs9939609 and TCF7L2 rs7903146 revealed the highest risk for BMI linked obesity. The analysis of the FTO-IRX3 locus revealed high LD and high order gene-gene interactions for BMI linked obesity. The interaction network of all of the associated genes in the present study generated by GENEMANIA revealed direct and indirect connections. In addition, the analysis with centralized obesity revealed that none of the SNPs except for FTO rs17818902 were significantly associated (P < .05). In this multi-analytical approach, FTO rs9939609 and IRX3 rs3751723, along with TCF7L2 rs7903146 and TMEM18 rs6548238, emerged as the major SNPs contributing to BMI linked obesity risk in the North Indian population. © 2016 Wiley Periodicals, Inc.

Identifying arsenic trioxide (ATO) functions in leukemia cells by using time series gene expression profiles.

PubMed

Yang, Hong; Lin, Shan; Cui, Jingru

2014-02-10

Arsenic trioxide (ATO) is presently the most active single agent in the treatment of acute promyelocytic leukemia (APL). In order to explore the molecular mechanism of ATO in leukemia cells with time series, we adopted bioinformatics strategy to analyze expression changing patterns and changes in transcription regulation modules of time series genes filtered from Gene Expression Omnibus database (GSE24946). We totally screened out 1847 time series genes for subsequent analysis. The KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment analysis of these genes showed that oxidative phosphorylation and ribosome were the top 2 significantly enriched pathways. STEM software was employed to compare changing patterns of gene expression with assigned 50 expression patterns. We screened out 7 significantly enriched patterns and 4 tendency charts of time series genes. The result of Gene Ontology showed that functions of times series genes mainly distributed in profiles 41, 40, 39 and 38. Seven genes with positive regulation of cell adhesion function were enriched in profile 40, and presented the same first increased model then decreased model as profile 40. The transcription module analysis showed that they mainly involved in oxidative phosphorylation pathway and ribosome pathway. Overall, our data summarized the gene expression changes in ATO treated K562-r cell lines with time and suggested that time series genes mainly regulated cell adhesive. Furthermore, our result may provide theoretical basis of molecular biology in treating acute promyelocytic leukemia. Copyright © 2013 Elsevier B.V. All rights reserved.

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

De novo transcriptome assembly in chili pepper (Capsicum frutescens) to identify genes involved in the biosynthesis of capsaicinoids.

PubMed

Liu, Shaoqun; Li, Wanshun; Wu, Yimin; Chen, Changming; Lei, Jianjun

2013-01-01

The capsaicinoids are a group of compounds produced by chili pepper fruits and are used widely in many fields, especially in medical purposes. The capsaicinoid biosynthetic pathway has not yet been established clearly. To understand more knowledge in biosynthesis of capsaicinoids, we applied RNA-seq for the mixture of placenta and pericarp of pungent pepper (Capsicum frutescens L.). We have assessed the effect of various assembly parameters using different assembly software, and obtained one of the best strategies for de novo assembly of transcriptome data. We obtained a total 54,045 high-quality unigenes (transcripts) using Trinity software. About 92.65% of unigenes showed similarity to the public protein sequences, genome of potato and tomato and pepper (C. annuum) ESTs databases. Our results predicted 3 new structural genes (DHAD, TD, PAT), which filled gaps of the capsaicinoid biosynthetic pathway predicted by Mazourek, and revealed new candidate genes involved in capsaicinoid biosynthesis based on KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. A significant number of SSR (Simple Sequence Repeat) and SNP (Single Nucleotide Polymorphism) markers were predicted in C. frutescens and C. annuum sequences, which will be helpful in the identification of polymorphisms within chili pepper populations. These data will provide new insights to the pathway of capsaicinoid biosynthesis and subsequent research of chili peppers. In addition, our strategy of de novo transcriptome assembly is applicable to a wide range of similar studies.

De Novo Transcriptome Assembly in Chili Pepper (Capsicum frutescens) to Identify Genes Involved in the Biosynthesis of Capsaicinoids

PubMed Central

Liu, Shaoqun; Li, Wanshun; Wu, Yimin; Chen, Changming; Lei, Jianjun

2013-01-01

The capsaicinoids are a group of compounds produced by chili pepper fruits and are used widely in many fields, especially in medical purposes. The capsaicinoid biosynthetic pathway has not yet been established clearly. To understand more knowledge in biosynthesis of capsaicinoids, we applied RNA-seq for the mixture of placenta and pericarp of pungent pepper (Capsicum frutescens L.). We have assessed the effect of various assembly parameters using different assembly software, and obtained one of the best strategies for de novo assembly of transcriptome data. We obtained a total 54,045 high-quality unigenes (transcripts) using Trinity software. About 92.65% of unigenes showed similarity to the public protein sequences, genome of potato and tomato and pepper (C. annuum) ESTs databases. Our results predicted 3 new structural genes (DHAD, TD, PAT), which filled gaps of the capsaicinoid biosynthetic pathway predicted by Mazourek, and revealed new candidate genes involved in capsaicinoid biosynthesis based on KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. A significant number of SSR (Simple Sequence Repeat) and SNP (Single Nucleotide Polymorphism) markers were predicted in C. frutescens and C. annuum sequences, which will be helpful in the identification of polymorphisms within chili pepper populations. These data will provide new insights to the pathway of capsaicinoid biosynthesis and subsequent research of chili peppers. In addition, our strategy of de novo transcriptome assembly is applicable to a wide range of similar studies. PMID:23349661

Estrogen pathway polymorphisms in relation to primary open angle glaucoma: An analysis accounting for gender from the United States

PubMed Central

Loomis, Stephanie J.; Weinreb, Robert N.; Kang, Jae H.; Yaspan, Brian L.; Bailey, Jessica Cooke; Gaasterland, Douglas; Gaasterland, Terry; Lee, Richard K.; Scott, William K.; Lichter, Paul R.; Budenz, Donald L.; Liu, Yutao; Realini, Tony; Friedman, David S.; McCarty, Catherine A.; Moroi, Sayoko E.; Olson, Lana; Schuman, Joel S.; Singh, Kuldev; Vollrath, Douglas; Wollstein, Gadi; Zack, Donald J.; Brilliant, Murray; Sit, Arthur J.; Christen, William G.; Fingert, John; Kraft, Peter; Zhang, Kang; Allingham, R. Rand; Pericak-Vance, Margaret A.; Richards, Julia E.; Hauser, Michael A.; Haines, Jonathan L.; Wiggs, Janey L.

2013-01-01

Purpose Circulating estrogen levels are relevant in glaucoma phenotypic traits. We assessed the association between an estrogen metabolism single nucleotide polymorphism (SNP) panel in relation to primary open angle glaucoma (POAG), accounting for gender. Methods We included 3,108 POAG cases and 3,430 controls of both genders from the Glaucoma Genes and Environment (GLAUGEN) study and the National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) consortium genotyped on the Illumina 660W-Quad platform. We assessed the relation between the SNP panels representative of estrogen metabolism and POAG using pathway- and gene-based approaches with the Pathway Analysis by Randomization Incorporating Structure (PARIS) software. PARIS executes a permutation algorithm to assess statistical significance relative to the pathways and genes of comparable genetic architecture. These analyses were performed using the meta-analyzed results from the GLAUGEN and NEIGHBOR data sets. We evaluated POAG overall as well as two subtypes of POAG defined as intraocular pressure (IOP) ≥22 mmHg (high-pressure glaucoma [HPG]) or IOP <22 mmHg (normal pressure glaucoma [NPG]) at diagnosis. We conducted these analyses for each gender separately and then jointly in men and women. Results Among women, the estrogen SNP pathway was associated with POAG overall (permuted p=0.006) and HPG (permuted p<0.001) but not NPG (permuted p=0.09). Interestingly, there was no relation between the estrogen SNP pathway and POAG when men were considered alone (permuted p>0.99). Among women, gene-based analyses revealed that the catechol-O-methyltransferase gene showed strong associations with HTG (permuted gene p≤0.001) and NPG (permuted gene p=0.01). Conclusions The estrogen SNP pathway was associated with POAG among women. PMID:23869166

Xtalk: a path-based approach for identifying crosstalk between signaling pathways

PubMed Central

Tegge, Allison N.; Sharp, Nicholas; Murali, T. M.

2016-01-01

Motivation: Cells communicate with their environment via signal transduction pathways. On occasion, the activation of one pathway can produce an effect downstream of another pathway, a phenomenon known as crosstalk. Existing computational methods to discover such pathway pairs rely on simple overlap statistics. Results: We present Xtalk, a path-based approach for identifying pairs of pathways that may crosstalk. Xtalk computes the statistical significance of the average length of multiple short paths that connect receptors in one pathway to the transcription factors in another. By design, Xtalk reports the precise interactions and mechanisms that support the identified crosstalk. We applied Xtalk to signaling pathways in the KEGG and NCI-PID databases. We manually curated a gold standard set of 132 crosstalking pathway pairs and a set of 140 pairs that did not crosstalk, for which Xtalk achieved an area under the receiver operator characteristic curve of 0.65, a 12% improvement over the closest competing approach. The area under the receiver operator characteristic curve varied with the pathway, suggesting that crosstalk should be evaluated on a pathway-by-pathway level. We also analyzed an extended set of 658 pathway pairs in KEGG and to a set of more than 7000 pathway pairs in NCI-PID. For the top-ranking pairs, we found substantial support in the literature (81% for KEGG and 78% for NCI-PID). We provide examples of networks computed by Xtalk that accurately recovered known mechanisms of crosstalk. Availability and implementation: The XTALK software is available at http://bioinformatics.cs.vt.edu/~murali/software. Crosstalk networks are available at http://graphspace.org/graphs?tags=2015-bioinformatics-xtalk. Contact: ategge@vt.edu, murali@cs.vt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26400040

Analyzing gene perturbation screens with nested effects models in R and bioconductor.

PubMed

Fröhlich, Holger; Beissbarth, Tim; Tresch, Achim; Kostka, Dennis; Jacob, Juby; Spang, Rainer; Markowetz, F

2008-11-01

Nested effects models (NEMs) are a class of probabilistic models introduced to analyze the effects of gene perturbation screens visible in high-dimensional phenotypes like microarrays or cell morphology. NEMs reverse engineer upstream/downstream relations of cellular signaling cascades. NEMs take as input a set of candidate pathway genes and phenotypic profiles of perturbing these genes. NEMs return a pathway structure explaining the observed perturbation effects. Here, we describe the package nem, an open-source software to efficiently infer NEMs from data. Our software implements several search algorithms for model fitting and is applicable to a wide range of different data types and representations. The methods we present summarize the current state-of-the-art in NEMs. Our software is written in the R language and freely avail-able via the Bioconductor project at http://www.bioconductor.org.

Simultaneous Identification of Multiple Driver Pathways in Cancer

PubMed Central

Leiserson, Mark D. M.; Blokh, Dima

2013-01-01

Distinguishing the somatic mutations responsible for cancer (driver mutations) from random, passenger mutations is a key challenge in cancer genomics. Driver mutations generally target cellular signaling and regulatory pathways consisting of multiple genes. This heterogeneity complicates the identification of driver mutations by their recurrence across samples, as different combinations of mutations in driver pathways are observed in different samples. We introduce the Multi-Dendrix algorithm for the simultaneous identification of multiple driver pathways de novo in somatic mutation data from a cohort of cancer samples. The algorithm relies on two combinatorial properties of mutations in a driver pathway: high coverage and mutual exclusivity. We derive an integer linear program that finds set of mutations exhibiting these properties. We apply Multi-Dendrix to somatic mutations from glioblastoma, breast cancer, and lung cancer samples. Multi-Dendrix identifies sets of mutations in genes that overlap with known pathways – including Rb, p53, PI(3)K, and cell cycle pathways – and also novel sets of mutually exclusive mutations, including mutations in several transcription factors or other genes involved in transcriptional regulation. These sets are discovered directly from mutation data with no prior knowledge of pathways or gene interactions. We show that Multi-Dendrix outperforms other algorithms for identifying combinations of mutations and is also orders of magnitude faster on genome-scale data. Software available at: http://compbio.cs.brown.edu/software. PMID:23717195

Whole-genome transcription and DNA methylation analysis of peripheral blood mononuclear cells identified aberrant gene regulation pathways in systemic lupus erythematosus.

PubMed

Zhu, Honglin; Mi, Wentao; Luo, Hui; Chen, Tao; Liu, Shengxi; Raman, Indu; Zuo, Xiaoxia; Li, Quan-Zhen

2016-07-13

Recent achievement in genetics and epigenetics has led to the exploration of the pathogenesis of systemic lupus erythematosus (SLE). Identification of differentially expressed genes and their regulatory mechanism(s) at whole-genome level will provide a comprehensive understanding of the development of SLE and its devastating complications, lupus nephritis (LN). We performed whole-genome transcription and DNA methylation analysis in PBMC of 30 SLE patients, including 15 with LN (SLE LN(+)) and 15 without LN (SLE LN(-)), and 25 normal controls (NC) using HumanHT-12 Beadchips and Illumina Human Methy450 chips. The serum proinflammatory cytokines were quantified using Bio-plex Human Cytokine 27-plex assay. Differentially expressed genes and differentially methylated CpG were analyzed with GenomeStudio, R, and SAM software. The association between DNA methylation and gene expression were tested. Gene interaction pathways of the differentially expressed genes were analyzed by IPA software. We identified 552 upregulated genes and 550 downregulated genes in PBMC of SLE. Integration of DNA methylation and gene expression profiling showed that 334 upregulated genes were hypomethylated, and 479 downregulated genes were hypermethylated. Pathway analysis on the differential genes in SLE revealed significant enrichment in interferon (IFN) signaling and toll-like receptor (TLR) signaling pathways. Nine IFN- and seven TLR-related genes were identified and displayed step-wise increase in SLE LN(-) and SLE LN(+). Hypomethylated CpG sites were detected on these genes. The gene expressions for MX1, GPR84, and E2F2 were increased in SLE LN(+) as compared to SLE LN(-) patients. The serum levels of inflammatory cytokines, including IL17A, IP-10, bFGF, TNF-α, IL-6, IL-15, GM-CSF, IL-1RA, IL-5, and IL-12p70, were significantly elevated in SLE compared with NC. The levels of IL-15 and IL1RA correlated with their mRNA expression. The upregulation of IL-15 may be regulated by hypomethylated CpG sites in the promotor region of the gene. Our study has demonstrated that significant number of differential genes in SLE were involved in IFN, TLR signaling pathways, and inflammatory cytokines. The enrichment of differential genes has been associated with aberrant DNA methylation, which may be relevant to the pathogenesis of SLE. Our observations have laid the groundwork for further diagnostic and mechanistic studies of SLE and LN.

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

PubMed Central

He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

2017-01-01

The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF. PMID:28713939

Proteomic investigation into betulinic acid-induced apoptosis of human cervical cancer HeLa cells.

PubMed

Xu, Tao; Pang, Qiuying; Zhou, Dong; Zhang, Aiqin; Luo, Shaman; Wang, Yang; Yan, Xiufeng

2014-01-01

Betulinic acid is a pentacyclic triterpenoid that exhibits anticancer functions in human cancer cells. This study provides evidence that betulinic acid is highly effective against the human cervical cancer cell line HeLa by inducing dose- and time-dependent apoptosis. The apoptotic process was further investigated using a proteomics approach to reveal protein expression changes in HeLa cells following betulinic acid treatment. Proteomic analysis revealed that there were six up- and thirty down-regulated proteins in betulinic acid-induced HeLa cells, and these proteins were then subjected to functional pathway analysis using multiple analysis software. UDP-glucose 6-dehydrogenase, 6-phosphogluconate dehydrogenase decarboxylating, chain A Horf6-a novel human peroxidase enzyme that involved in redox process, was found to be down-regulated during the apoptosis process of the oxidative stress response pathway. Consistent with our results at the protein level, an increase in intracellular reactive oxygen species was observed in betulinic acid-treated cells. The proteins glucose-regulated protein and cargo-selection protein TIP47, which are involved in the endoplasmic reticulum pathway, were up-regulated by betulinic acid treatment. Meanwhile, 14-3-3 family proteins, including 14-3-3β and 14-3-3ε, were down-regulated in response to betulinic acid treatment, which is consistent with the decrease in expression of the target genes 14-3-3β and 14-3-3ε. Furthermore, it was found that the antiapoptotic bcl-2 gene was down-regulated while the proapoptotic bax gene was up-regulated after betulinic acid treatment in HeLa cells. These results suggest that betulinic acid induces apoptosis of HeLa cells by triggering both the endoplasmic reticulum pathway and the ROS-mediated mitochondrial pathway.

Signaling network of dendritic cells in response to pathogens: a community-input supported knowledgebase.

PubMed

Patil, Sonali; Pincas, Hanna; Seto, Jeremy; Nudelman, German; Nudelman, Irina; Sealfon, Stuart C

2010-10-07

Dendritic cells are antigen-presenting cells that play an essential role in linking the innate and adaptive immune systems. Much research has focused on the signaling pathways triggered upon infection of dendritic cells by various pathogens. The high level of activity in the field makes it desirable to have a pathway-based resource to access the information in the literature. Current pathway diagrams lack either comprehensiveness, or an open-access editorial interface. Hence, there is a need for a dependable, expertly curated knowledgebase that integrates this information into a map of signaling networks. We have built a detailed diagram of the dendritic cell signaling network, with the goal of providing researchers with a valuable resource and a facile method for community input. Network construction has relied on comprehensive review of the literature and regular updates. The diagram includes detailed depictions of pathways activated downstream of different pathogen recognition receptors such as Toll-like receptors, retinoic acid-inducible gene-I-like receptors, C-type lectin receptors and nucleotide-binding oligomerization domain-like receptors. Initially assembled using CellDesigner software, it provides an annotated graphical representation of interactions stored in Systems Biology Mark-up Language. The network, which comprises 249 nodes and 213 edges, has been web-published through the Biological Pathway Publisher software suite. Nodes are annotated with PubMed references and gene-related information, and linked to a public wiki, providing a discussion forum for updates and corrections. To gain more insight into regulatory patterns of dendritic cell signaling, we analyzed the network using graph-theory methods: bifan, feedforward and multi-input convergence motifs were enriched. This emphasis on activating control mechanisms is consonant with a network that subserves persistent and coordinated responses to pathogen detection. This map represents a navigable aid for presenting a consensus view of the current knowledge on dendritic cell signaling that can be continuously improved through contributions of research community experts. Because the map is available in a machine readable format, it can be edited and may assist researchers in data analysis. Furthermore, the availability of a comprehensive knowledgebase might help further research in this area such as vaccine development. The dendritic cell signaling knowledgebase is accessible at http://tsb.mssm.edu/pathwayPublisher/DC_pathway/DC_pathway_index.html.

'Isotopo' a database application for facile analysis and management of mass isotopomer data.

PubMed

Ahmed, Zeeshan; Zeeshan, Saman; Huber, Claudia; Hensel, Michael; Schomburg, Dietmar; Münch, Richard; Eylert, Eva; Eisenreich, Wolfgang; Dandekar, Thomas

2014-01-01

The composition of stable-isotope labelled isotopologues/isotopomers in metabolic products can be measured by mass spectrometry and supports the analysis of pathways and fluxes. As a prerequisite, the original mass spectra have to be processed, managed and stored to rapidly calculate, analyse and compare isotopomer enrichments to study, for instance, bacterial metabolism in infection. For such applications, we provide here the database application 'Isotopo'. This software package includes (i) a database to store and process isotopomer data, (ii) a parser to upload and translate different data formats for such data and (iii) an improved application to process and convert signal intensities from mass spectra of (13)C-labelled metabolites such as tertbutyldimethylsilyl-derivatives of amino acids. Relative mass intensities and isotopomer distributions are calculated applying a partial least square method with iterative refinement for high precision data. The data output includes formats such as graphs for overall enrichments in amino acids. The package is user-friendly for easy and robust data management of multiple experiments. The 'Isotopo' software is available at the following web link (section Download): http://spp1316.uni-wuerzburg.de/bioinformatics/isotopo/. The package contains three additional files: software executable setup (installer), one data set file (discussed in this article) and one excel file (which can be used to convert data from excel to '.iso' format). The 'Isotopo' software is compatible only with the Microsoft Windows operating system. http://spp1316.uni-wuerzburg.de/bioinformatics/isotopo/. © The Author(s) 2014. Published by Oxford University Press.

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

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction.

PubMed

Dhanasekaran, A Ranjitha; Pearson, Jon L; Ganesan, Balasubramanian; Weimer, Bart C

2015-02-25

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism's genome as a database restricts metabolite identification to only those compounds that the organism can produce. To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment's MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis. Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction.

PubMed

Santos, Carlos; Eggle, Daniela; States, David J

2005-04-15

Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map. A 'gold standard' set of names and assertions was derived by manual scanning of the Wnt genes website (http://www.stanford.edu/~rnusse/wntwindow.html) including 53 interactions involved in Wnt signaling. This system was used to analyze a corpus of peer-reviewed articles related to Wnt signaling including 3369 Pubmed and 1230 full text papers. Names for key Wnt-pathway associated proteins and biological entities are identified using a chi-squared analysis of noun phrases over-represented in the Wnt literature as compared to the general signal transduction literature. Interestingly, we identified several instances where generic terms were used on the website when more specific terms occur in the literature, and one typographic error on the Wnt canonical pathway. Using the named entity list and performing an exhaustive assertion extraction of the corpus, 34 of the 53 interactions in the 'gold standard' Wnt signaling set were successfully identified (64% recall). In addition, the automated extraction found several interactions involving key Wnt-related molecules which were missing or different from those in the canonical diagram, and these were confirmed by manual review of the text. These results suggest that a combination of NLP techniques for information extraction can form a useful first-pass tool for assisting human annotation and maintenance of signal pathway databases. The pipeline software components are freely available on request to the authors. dstates@umich.edu http://stateslab.bioinformatics.med.umich.edu/software.html.

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data

PubMed Central

Gogoshin, Grigoriy; Boerwinkle, Eric

2017-01-01

Abstract Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology—type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types—single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc. PMID:27681505

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data.

PubMed

Gogoshin, Grigoriy; Boerwinkle, Eric; Rodin, Andrei S

2017-04-01

Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology-type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types-single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite levels, epidemiological variables, endpoints, and phenotypes, etc.

Vascular tone pathway polymorphisms in relation to primary open-angle glaucoma.

PubMed

Kang, J H; Loomis, S J; Yaspan, B L; Bailey, J C; Weinreb, R N; Lee, R K; Lichter, P R; Budenz, D L; Liu, Y; Realini, T; Gaasterland, D; Gaasterland, T; Friedman, D S; McCarty, C A; Moroi, S E; Olson, L; Schuman, J S; Singh, K; Vollrath, D; Wollstein, G; Zack, D J; Brilliant, M; Sit, A J; Christen, W G; Fingert, J; Forman, J P; Buys, E S; Kraft, P; Zhang, K; Allingham, R R; Pericak-Vance, M A; Richards, J E; Hauser, M A; Haines, J L; Wiggs, J L; Pasquale, L R

2014-06-01

Vascular perfusion may be impaired in primary open-angle glaucoma (POAG); thus, we evaluated a panel of markers in vascular tone-regulating genes in relation to POAG. We used Illumina 660W-Quad array genotype data and pooled P-values from 3108 POAG cases and 3430 controls from the combined National Eye Institute Glaucoma Human Genetics Collaboration consortium and Glaucoma Genes and Environment studies. Using information from previous literature and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we compiled single-nucleotide polymorphisms (SNPs) in 186 vascular tone-regulating genes. We used the 'Pathway Analysis by Randomization Incorporating Structure' analysis software, which performed 1000 permutations to compare the overall pathway and selected genes with comparable randomly generated pathways and genes in their association with POAG. The vascular tone pathway was not associated with POAG overall or POAG subtypes, defined by the type of visual field loss (early paracentral loss (n=224 cases) or only peripheral loss (n=993 cases)) (permuted P≥0.20). In gene-based analyses, eight were associated with POAG overall at permuted P<0.001: PRKAA1, CAV1, ITPR3, EDNRB, GNB2, DNM2, HFE, and MYL9. Notably, six of these eight (the first six listed) code for factors involved in the endothelial nitric oxide synthase activity, and three of these six (CAV1, ITPR3, and EDNRB) were also associated with early paracentral loss at P<0.001, whereas none of the six genes reached P<0.001 for peripheral loss only. Although the assembled vascular tone SNP set was not associated with POAG, genes that code for local factors involved in setting vascular tone were associated with POAG.

Proteomic identification of processes and pathways characteristic of osmoregulatory tissues in spiny dogfish shark (Squalus acanthias).

PubMed

Lee, Jinoo; Valkova, Nelly; White, Mark P; Kültz, Dietmar

2006-09-01

We used dogfish shark (Squalus acanthias) as a model for proteome analysis of six different tissues to evaluate tissue-specific protein expression on a global scale and to deduce specific functions and the relatedness of multiple tissues from their proteomes. Proteomes of heart, brain, kidney, intestine, gill, and rectal gland were separated by two-dimensional gel electrophoresis (2DGE), gel images were matched using Delta 2D software and then evaluated for tissue-specific proteins. Sixty-one proteins (4%) were found to be in only a single type of tissue and 535 proteins (36%) were equally abundant in all six tissues. Relatedness between tissues was assessed based on tissue-specific expression patterns of all 1465 consistently resolved protein spots. This analysis revealed that tissues with osmoregulatory function (kidney, intestine, gill, rectal gland) were more similar in their overall proteomes than non-osmoregulatory tissues (heart, brain). Sixty-one proteins were identified by MALDI-TOF/TOF mass spectrometry and biological functions characteristic of osmoregulatory tissues were derived from gene ontology and molecular pathway analysis. Our data demonstrate that the molecular machinery for energy and urea metabolism and the Rho-GTPase/cytoskeleton pathway are enriched in osmoregulatory tissues of sharks. Our work provides a strong rationale for further study of the contribution of these mechanisms to the osmoregulation of marine sharks.

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis

PubMed Central

Luo, Shouling; Cao, Nannan; Tang, Yao; Gu, Weirong

2017-01-01

Preeclampsia is a leading cause of perinatal maternal–foetal mortality and morbidity. The aim of this study is to identify the key microRNAs and genes in preeclampsia and uncover their potential functions. We downloaded the miRNA expression profile of GSE84260 and the gene expression profile of GSE73374 from the Gene Expression Omnibus database. Differentially expressed miRNAs and genes were identified and compared to miRNA-target information from MiRWalk 2.0, and a total of 65 differentially expressed miRNAs (DEMIs), including 32 up-regulated miRNAs and 33 down-regulated miRNAs, and 91 differentially expressed genes (DEGs), including 83 up-regulated genes and 8 down-regulated genes, were identified. The pathway enrichment analyses of the DEMIs showed that the up-regulated DEMIs were enriched in the Hippo signalling pathway and MAPK signalling pathway, and the down-regulated DEMIs were enriched in HTLV-I infection and miRNAs in cancers. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses of the DEGs were performed using Multifaceted Analysis Tool for Human Transcriptome. The up-regulated DEGs were enriched in biological processes (BPs), including the response to cAMP, response to hydrogen peroxide and cell-cell adhesion mediated by integrin; no enrichment of down-regulated DEGs was identified. KEGG analysis showed that the up-regulated DEGs were enriched in the Hippo signalling pathway and pathways in cancer. A PPI network of the DEGs was constructed by using Cytoscape software, and FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36 were identified as the hub genes. The current study illustrates a characteristic microRNA profile and gene profile in preeclampsia, which may contribute to the interpretation of the progression of preeclampsia and provide novel biomarkers and therapeutic targets for preeclampsia. PMID:28594854

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

PubMed

McCormack, Theodore; Frings, Oliver; Alexeyenko, Andrey; Sonnhammer, Erik L L

2013-01-01

Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

RNA-seq Analysis Reveals Unique Transcriptome Signatures in Systemic Lupus Erythematosus Patients with Distinct Autoantibody Specificities

PubMed Central

Rai, Richa; Chauhan, Sudhir Kumar; Singh, Vikas Vikram; Rai, Madhukar; Rai, Geeta

2016-01-01

Systemic lupus erythematosus (SLE) patients exhibit immense heterogeneity which is challenging from the diagnostic perspective. Emerging high throughput sequencing technologies have been proved to be a useful platform to understand the complex and dynamic disease processes. SLE patients categorised based on autoantibody specificities are reported to have differential immuno-regulatory mechanisms. Therefore, we performed RNA-seq analysis to identify transcriptomics of SLE patients with distinguished autoantibody specificities. The SLE patients were segregated into three subsets based on the type of autoantibodies present in their sera (anti-dsDNA+ group with anti-dsDNA autoantibody alone; anti-ENA+ group having autoantibodies against extractable nuclear antigens (ENA) only, and anti-dsDNA+ENA+ group having autoantibodies to both dsDNA and ENA). Global transcriptome profiling for each SLE patients subsets was performed using Illumina® Hiseq-2000 platform. The biological relevance of dysregulated transcripts in each SLE subsets was assessed by ingenuity pathway analysis (IPA) software. We observed that dysregulation in the transcriptome expression pattern was clearly distinct in each SLE patients subsets. IPA analysis of transcripts uniquely expressed in different SLE groups revealed specific biological pathways to be affected in each SLE subsets. Multiple cytokine signaling pathways were specifically dysregulated in anti-dsDNA+ patients whereas Interferon signaling was predominantly dysregulated in anti-ENA+ patients. In anti-dsDNA+ENA+ patients regulation of actin based motility by Rho pathway was significantly affected. The granulocyte gene signature was a common feature to all SLE subsets; however, anti-dsDNA+ group showed relatively predominant expression of these genes. Dysregulation of Plasma cell related transcripts were higher in anti-dsDNA+ and anti-ENA+ patients as compared to anti-dsDNA+ ENA+. Association of specific canonical pathways with the uniquely expressed transcripts in each SLE subgroup indicates that specific immunological disease mechanisms are operative in distinct SLE patients’ subsets. This ‘sub-grouping’ approach could further be useful for clinical evaluation of SLE patients and devising targeted therapeutics. PMID:27835693

Identification of Key Pathways and Genes in the Dynamic Progression of HCC Based on WGCNA.

PubMed

Yin, Li; Cai, Zhihui; Zhu, Baoan; Xu, Cunshuan

2018-02-14

Hepatocellular carcinoma (HCC) is a devastating disease worldwide. Though many efforts have been made to elucidate the process of HCC, its molecular mechanisms of development remain elusive due to its complexity. To explore the stepwise carcinogenic process from pre-neoplastic lesions to the end stage of HCC, we employed weighted gene co-expression network analysis (WGCNA) which has been proved to be an effective method in many diseases to detect co-expressed modules and hub genes using eight pathological stages including normal, cirrhosis without HCC, cirrhosis, low-grade dysplastic, high-grade dysplastic, very early and early, advanced HCC and very advanced HCC. Among the eight consecutive pathological stages, five representative modules are selected to perform canonical pathway enrichment and upstream regulator analysis by using ingenuity pathway analysis (IPA) software. We found that cell cycle related biological processes were activated at four neoplastic stages, and the degree of activation of the cell cycle corresponded to the deterioration degree of HCC. The orange and yellow modules enriched in energy metabolism, especially oxidative metabolism, and the expression value of the genes decreased only at four neoplastic stages. The brown module, enriched in protein ubiquitination and ephrin receptor signaling pathways, correlated mainly with the very early stage of HCC. The darkred module, enriched in hepatic fibrosis/hepatic stellate cell activation, correlated with the cirrhotic stage only. The high degree hub genes were identified based on the protein-protein interaction (PPI) network and were verified by Kaplan-Meier survival analysis. The novel five high degree hub genes signature that was identified in our study may shed light on future prognostic and therapeutic approaches. Our study brings a new perspective to the understanding of the key pathways and genes in the dynamic changes of HCC progression. These findings shed light on further investigations.

VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis.

PubMed

Cornwell, MacIntosh; Vangala, Mahesh; Taing, Len; Herbert, Zachary; Köster, Johannes; Li, Bo; Sun, Hanfei; Li, Taiwen; Zhang, Jian; Qiu, Xintao; Pun, Matthew; Jeselsohn, Rinath; Brown, Myles; Liu, X Shirley; Long, Henry W

2018-04-12

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

NASA Technical Reports Server (NTRS)

Lee, Alice T.; Gunn, Todd; Pham, Tuan; Ricaldi, Ron

1994-01-01

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

Reusable, extensible, and modifiable R scripts and Kepler workflows for comprehensive single set ChIP-seq analysis.

PubMed

Cormier, Nathan; Kolisnik, Tyler; Bieda, Mark

2016-07-05

There has been an enormous expansion of use of chromatin immunoprecipitation followed by sequencing (ChIP-seq) technologies. Analysis of large-scale ChIP-seq datasets involves a complex series of steps and production of several specialized graphical outputs. A number of systems have emphasized custom development of ChIP-seq pipelines. These systems are primarily based on custom programming of a single, complex pipeline or supply libraries of modules and do not produce the full range of outputs commonly produced for ChIP-seq datasets. It is desirable to have more comprehensive pipelines, in particular ones addressing common metadata tasks, such as pathway analysis, and pipelines producing standard complex graphical outputs. It is advantageous if these are highly modular systems, available as both turnkey pipelines and individual modules, that are easily comprehensible, modifiable and extensible to allow rapid alteration in response to new analysis developments in this growing area. Furthermore, it is advantageous if these pipelines allow data provenance tracking. We present a set of 20 ChIP-seq analysis software modules implemented in the Kepler workflow system; most (18/20) were also implemented as standalone, fully functional R scripts. The set consists of four full turnkey pipelines and 16 component modules. The turnkey pipelines in Kepler allow data provenance tracking. Implementation emphasized use of common R packages and widely-used external tools (e.g., MACS for peak finding), along with custom programming. This software presents comprehensive solutions and easily repurposed code blocks for ChIP-seq analysis and pipeline creation. Tasks include mapping raw reads, peakfinding via MACS, summary statistics, peak location statistics, summary plots centered on the transcription start site (TSS), gene ontology, pathway analysis, and de novo motif finding, among others. These pipelines range from those performing a single task to those performing full analyses of ChIP-seq data. The pipelines are supplied as both Kepler workflows, which allow data provenance tracking, and, in the majority of cases, as standalone R scripts. These pipelines are designed for ease of modification and repurposing.

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.

Defining the human deubiquitinating enzyme interaction landscape.

PubMed

Sowa, Mathew E; Bennett, Eric J; Gygi, Steven P; Harper, J Wade

2009-07-23

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

Defining the Human Deubiquitinating Enzyme Interaction Landscape

PubMed Central

Sowa, Mathew E.; Bennett, Eric J.; Gygi, Steven P.; Harper, J. Wade

2009-01-01

Summary Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform, called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel non-reciprocal proteomic datasets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, sub-cellular localization and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway. PMID:19615732

Cell cycle pathway dysregulation in human keratinocytes during chronic exposure to low arsenite.

PubMed

Al-Eryani, Laila; Waigel, Sabine; Jala, Venkatakrishna; Jenkins, Samantha F; States, J Christopher

2017-09-15

Arsenic is naturally prevalent in the earth's crust and widely distributed in air and water. Chronic low arsenic exposure is associated with several cancers in vivo, including skin cancer, and with transformation in vitro of cell lines including immortalized human keratinocytes (HaCaT). Arsenic also is associated with cell cycle dysregulation at different exposure levels in multiple cell lines. In this work, we analyzed gene expression in HaCaT cells to gain an understanding of gene expression changes contributing to transformation at an early time point. HaCaT cells were exposed to 0 or 100nM NaAsO 2 for 7weeks. Total RNA was purified and analyzed by microarray hybridization. Differential expression with fold change≥|1.5| and p-value≤0.05 was determined using Partek Genomic Suite™ and pathway and network analyses using MetaCore™ software (FDR≤0.05). Cell cycle analysis was performed using flow cytometry. 644 mRNAs were differentially expressed. Cell cycle/cell cycle regulation pathways predominated in the list of dysregulated pathways. Genes involved in replication origin licensing were enriched in the network. Cell cycle assay analysis showed an increase in G2/M compartment in arsenite-exposed cells. Arsenite exposure induced differential gene expression indicating dysregulation of cell cycle control, which was confirmed by cell cycle analysis. The results suggest that cell cycle dysregulation is an early event in transformation manifested in cells unable to transit G2/M efficiently. Further study at later time points will reveal additional changes in gene expression related to transformation processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential proteome analysis of the cell differentiation regulated by BCC, CRH, CXCR4, GnRH, GPCR, IL1 signaling pathways in Chinese fire-bellied newt limb regeneration.

PubMed

Geng, Xiaofang; Xu, Tiantian; Niu, Zhipeng; Zhou, Xiaochun; Zhao, Lijun; Xie, Zhaohui; Xue, Deming; Zhang, Fuchun; Xu, Cunshuan

2014-01-01

Following amputation, the newt has the remarkable ability to regenerate its limb, and this process involves dedifferentiation, proliferation and differentiation. To investigate the potential proteome during a dynamic network of Chinese fire-bellied newt limb regeneration (CNLR), two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) and mass spectrum (MS) were applied to examine changes in the proteome that occurred at 11 time points after amputation. Meanwhile, several proteins were selected to validate their expression levels by Western blot. The results revealed that 1476 proteins had significantly changed as compared to the control group. Gene Ontology annotation and protein network analysis by Ingenuity Pathway Analysis 9.0 (IPA) software suggested that the differentially expressed proteins were involved in 33 kinds of physiological activities including signal transduction, cell proliferation, cell differentiation, etc. Among these proteins, 407 proteins participated in cell differentiation with 212 proteins in the differentiation of skin cell, myocyte, neurocyte, chondrocyte and osteocyte, and 37 proteins participated in signaling pathways of BCC, CRH, CXCR4, GnRH, GPCR and IL1 which regulated cell differentiation and redifferentiation. On the other hand, the signal transduction activity and cell differentiation activity were analyzed by IPA based on the changes in the expression of these proteins. The results showed that BCC, CRH, CXCR4, GnRH, GPCR and IL1 signaling pathways played an important role in regulating the differentiation of skin cell, myocyte, neurocyte, chondrocyte and osteocyte during CNLR. Copyright © 2014 International Society of Differentiation. Published by Elsevier B.V. All rights reserved.

Patterns and determinants of pathways to reach comprehensive emergency obstetric and neonatal care (CEmONC) in South Sudan: qualitative diagrammatic pathway analysis.

PubMed

Elmusharaf, Khalifa; Byrne, Elaine; AbuAgla, Ayat; AbdelRahim, Amal; Manandhar, Mary; Sondorp, Egbert; O'Donovan, Diarmuid

2017-08-29

Maternity referral systems have been under-documented, under-researched, and under-theorised. Responsive emergency referral systems and appropriate transportation are cornerstones in the continuum of care and central to the complex health system. The pathways that women follow to reach Emergency Obstetric and Neonatal Care (EmONC) once a decision has been made to seek care have received relatively little attention. The aim of this research was to identify patterns and determinants of the pathways pregnant women follow from the onset of labour or complications until they reach an appropriate health facility. This study was conducted in Renk County in South Sudan between 2010 and 2012. Data was collected using Critical Incident Technique (CIT) and stakeholder interviews. CIT systematically identified pathways to healthcare during labour, and factors associated with an event of maternal mortality or near miss through a series of in-depth interviews with witnesses or those involved. Face-to-face stakeholder interviews were conducted with 28 purposively identified key informants. Diagrammatic pathway and thematic analysis were conducted using NVIVO 10 software. Once the decision is made to seek emergency obstetric care, the pregnant woman may face a series of complex steps before she reaches an appropriate health facility. Four pathway patterns to CEmONC were identified of which three were associated with high rates of maternal death: late referral, zigzagging referral, and multiple referrals. Women who bypassed nonfunctional Basic EmONC facilities and went directly to CEmONC facilities (the fourth pathway pattern) were most likely to survive. Overall, the competencies of the providers and the functionality of the first point of service determine the pathway to further care. Our findings indicate that outcomes are better where there is no facility available than when the woman accesses a non-functioning facility, and the absence of a healthcare provider is better than the presence of a non-competent provider. Visiting non-functioning or partially functioning healthcare facilities on the way to competent providers places the woman at greater risk of dying. Non-functioning facilities and non-competent providers are likely to contribute to the deaths of women.

Saccharomyces cerevisiae Boulardii Reduces the Deoxynivalenol-Induced Alteration of the Intestinal Transcriptome.

PubMed

Alassane-Kpembi, Imourana; Pinton, Philippe; Hupé, Jean-François; Neves, Manon; Lippi, Yannick; Combes, Sylvie; Castex, Mathieu; Oswald, Isabelle P

2018-05-15

Type B trichothecene mycotoxin deoxynivalenol (DON) is one of the most frequently occurring food contaminants. By inducing trans-activation of a number of pro-inflammatory cytokines and increasing the stability of their mRNA, trichothecene can impair intestinal health. Several yeast products, especially Saccharomyces cerevisiae , have the potential for improving the enteric health of piglets, but little is known about the mechanisms by which the administration of yeast counteracts the DON-induced intestinal alterations. Using a pig jejunum explant model, a whole-transcriptome analysis was performed to decipher the early response of the small intestine to the deleterious effects of DON after administration of S. cerevisiae boulardii strain CNCM I-1079. Compared to the control condition, no differentially expressed gene (DE) was observed after treatment by yeast only. By contrast, 3619 probes-corresponding to 2771 genes-were differentially expressed following exposure to DON, and 32 signaling pathways were identified from the IPA software functional analysis of the set of DE genes. When the intestinal explants were treated with S. cerevisiae boulardii prior to DON exposure, the number of DE genes decreased by half (1718 probes corresponding to 1384 genes). Prototypical inflammation signaling pathways triggered by DON, including NF-κB and p38 MAPK, were reversed, although the yeast demonstrated limited efficacy toward some other pathways. S. cerevisiae boulardii also restored the lipid metabolism signaling pathway, and reversed the down-regulation of the antioxidant action of vitamin C signaling pathway. The latter effect could reduce the burden of DON-induced oxidative stress. Altogether, the results show that S. cerevisiae boulardii reduces the DON-induced alteration of intestinal transcriptome, and point to new mechanisms for the healing of tissue injury by yeast.

Saccharomyces cerevisiae boulardii Reduces the Deoxynivalenol-Induced Alteration of the Intestinal Transcriptome

PubMed Central

Alassane-Kpembi, Imourana; Hupé, Jean-François; Neves, Manon; Lippi, Yannick; Combes, Sylvie; Castex, Mathieu

2018-01-01

Type B trichothecene mycotoxin deoxynivalenol (DON) is one of the most frequently occurring food contaminants. By inducing trans-activation of a number of pro-inflammatory cytokines and increasing the stability of their mRNA, trichothecene can impair intestinal health. Several yeast products, especially Saccharomyces cerevisiae, have the potential for improving the enteric health of piglets, but little is known about the mechanisms by which the administration of yeast counteracts the DON-induced intestinal alterations. Using a pig jejunum explant model, a whole-transcriptome analysis was performed to decipher the early response of the small intestine to the deleterious effects of DON after administration of S. cerevisiae boulardii strain CNCM I-1079. Compared to the control condition, no differentially expressed gene (DE) was observed after treatment by yeast only. By contrast, 3619 probes—corresponding to 2771 genes—were differentially expressed following exposure to DON, and 32 signaling pathways were identified from the IPA software functional analysis of the set of DE genes. When the intestinal explants were treated with S. cerevisiae boulardii prior to DON exposure, the number of DE genes decreased by half (1718 probes corresponding to 1384 genes). Prototypical inflammation signaling pathways triggered by DON, including NF-κB and p38 MAPK, were reversed, although the yeast demonstrated limited efficacy toward some other pathways. S. cerevisiae boulardii also restored the lipid metabolism signaling pathway, and reversed the down-regulation of the antioxidant action of vitamin C signaling pathway. The latter effect could reduce the burden of DON-induced oxidative stress. Altogether, the results show that S. cerevisiae boulardii reduces the DON-induced alteration of intestinal transcriptome, and point to new mechanisms for the healing of tissue injury by yeast. PMID:29762474

Serum cytokine profiling and enrichment analysis reveal the involvement of immunological and inflammatory pathways in stable patients with chronic obstructive pulmonary disease.

PubMed

Bade, Geetanjali; Khan, Meraj Alam; Srivastava, Akhilesh Kumar; Khare, Parul; Solaiappan, Krishna Kumar; Guleria, Randeep; Palaniyar, Nades; Talwar, Anjana

2014-01-01

Chronic obstructive pulmonary disease (COPD) is a major global health problem. It results from chronic inflammation and causes irreversible airway damage. Levels of different serum cytokines could be surrogate biomarkers for inflammation and lung function in COPD. We aimed to determine the serum levels of different biomarkers in COPD patients, the association between cytokine levels and various prognostic parameters, and the key pathways/networks involved in stable COPD. In this study, serum levels of 48 cytokines were examined by multiplex assays in 30 subjects (control, n=9; COPD, n=21). Relationships between serum biomarkers and forced expiratory volume in 1 second, peak oxygen uptake, body mass index, dyspnea score, and smoking were assessed. Enrichment pathways and network analyses were implemented, using a list of cytokines showing differential expression between healthy controls and patients with COPD by Cytoscape and GeneGo Metacore™ software (Thomson-Reuters Corporation, New York, NY, USA). Concentrations of cutaneous T-cell attracting chemokine, eotaxin, hepatocyte growth factor, interleukin 6 (IL-6), IL-16, and stem cell factor are significantly higher in COPD patients compared with in control patients. Notably, this study identifies stem cell factor as a biomarker for COPD. Multiple regression analysis predicts that cutaneous T-cell-attracting chemokine, eotaxin, IL-6, and stem cell factor are inversely associated with forced expiratory volume in 1 second and peak oxygen uptake change, whereas smoking is related to eotaxin and hepatocyte growth factor changes. Enrichment pathways and network analyses reveal the potential involvement of specific inflammatory and immune process pathways in COPD. Identified network interaction and regulation of different cytokines would pave the way for deeper insight into mechanisms of the disease process.

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

PubMed

Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

2017-12-01

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

Geophysical Analysis of an Urban Region in Southwestern Pennsylvania

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

Harbert, W.P.; Lipinski, B.A.; Kaminski, V.

2006-12-01

The goal of this project was to categorize the subsurface beneath an urban region of Southwestern Pennsylvania and to determine geological structure and attempt to image pathways for gas migration in this area. Natural gas had been commercially produced from this region at the turn of the century but this field, with more than 100 wells drilled, was closed approximately eighty years ago. There are surface expressions of gas migration visible in the study region. We applied geophysical methods to determine geological structure in this region, which included multi frequency electromagnetic survey performed using Geophex Gem-2 system, portable reflection seismicmore » and a System I/O-based reflection seismic survey. Processing and interpretation of EM data included filtering 10 raw channels (inphase and quadrature components measured at 5 frequencies), inverting the data for apparent conductivity using EM1DFM software by University of British Columbia, Canada and further interpretation in terms of nearsurface features at a maximum depth of up to 20 meters. Analysis of the collected seismic data included standard seismic processing and the use of the SurfSeis software package developed by the Kansas Geological Survey. Standard reflection processing of these data were completed using the LandMark ProMAX 2D/3D and Parallel Geoscience Corporations software. Final stacked sections were then imported into a Seismic Micro Technologies Kingdom Suite+ geodatabase for visualization and analysis. Interpretation of these data was successful in identifying and confirming a region of unmined Freeport coal, determining regional stratigraphic structure and identifying possible S-wave lower velocity anomalies in the shallow subsurface.« less

Influence of Intracanal Materials in Vertical Root Fracture Pathway Detection with Cone-beam Computed Tomography.

PubMed

Dutra, Kamile Leonardi; Pachêco-Pereira, Camila; Bortoluzzi, Eduardo Antunes; Flores-Mir, Carlos; Lagravère, Manuel O; Corrêa, Márcio

2017-07-01

Investigating the vertical root fracture (VRF) pathway under different clinical scenarios may help to diagnose this condition properly. We aimed to determine the capability and intrareliability of VRF pathway detection through cone-beam computed tomographic (CBCT) imaging as well as analyze the influence of different intracanal and crown materials. VRFs were mechanically induced in 30 teeth, and 4 clinical situations were reproduced in vitro: no filling, gutta-percha, post, and metal crown. A Prexion (San Mateo, CA) 3-dimensional tomographic device was used to generate 104 CBCT scans. The VRF pathway was determined by using landmarks in the Avizo software (Version 8.1; FEI Visualization Sciences Group, Burlington, MA) by 1 observer repeated 3 times. Analysis of variance and post hoc tests were applied to compare groups. Intrareliability demonstrated an excellent agreement (intraclass correlation coefficient mean = 0.93). Descriptive analysis showed that the fracture line measurement was smaller in the post and metal crown groups than in the no-filling and gutta-percha groups. The 1-way analysis of variance test found statistically significant differences among the groups measurements. The Bonferroni correction showed statistically significant differences related to the no-filling and gutta-percha groups versus the post and metal crown groups. The VRF pathway can be accurately detected in a nonfilled tooth using limited field of view CBCT imaging. The presence of gutta-percha generated a low beam hardening artifact that did not hinder the VRF extent. The presence of an intracanal gold post made the fracture line appear smaller than it really was in the sagittal images; in the axial images, a VRF was only detected when the apical third was involved. The presence of a metal crown did not generate additional artifacts on the root surface compared to the intracanal gold post by itself. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Analysis of the functional aspects and seminal plasma proteomic profile of sperm from smokers.

PubMed

Antoniassi, Mariana Pereira; Intasqui, Paula; Camargo, Mariana; Zylbersztejn, Daniel Suslik; Carvalho, Valdemir Melechco; Cardozo, Karina H M; Bertolla, Ricardo Pimenta

2016-11-01

To evaluate the effect of smoking on sperm functional quality and seminal plasma proteomic profile. Sperm functional tests were performed in 20 non-smoking men with normal semen quality, according to the World Health Organization (2010) and in 20 smoking patients. These included: evaluation of DNA fragmentation by alkaline Comet assay; analysis of mitochondrial activity using DAB staining; and acrosomal integrity evaluation by PNA binding. The remaining semen was centrifuged and seminal plasma was used for proteomic analysis (liquid chromatography-tandem mass spectrometry). The quantified proteins were used for Venn diagram construction in Cytoscape 3.2.1 software, using the PINA4MS plug-in. Then, differentially expressed proteins were used for functional enrichment analysis of Gene Ontology categories, Kyoto Encyclopedia of Genes and Genomes and Reactome, using Cytoscape software and the ClueGO 2.2.0 plug-in. Smokers had a higher percentage of sperm DNA damage (Comet classes III and IV; P < 0.01), partially and fully inactive mitochondria (DAB classes III and IV; P = 0.001 and P = 0.006, respectively) and non-intact acrosomes (P < 0.01) when compared with the control group. With respect to proteomic analysis, 422 proteins were identified and quantified, of which one protein was absent, 27 proteins were under-represented and six proteins were over-represented in smokers. Functional enrichment analysis showed the enrichment of antigen processing and presentation, positive regulation of prostaglandin secretion involved in immune response, protein kinase A signalling and arachidonic acid secretion, complement activation, regulation of the cytokine-mediated signalling pathway and regulation of acute inflammatory response in the study group (smokers). In conclusion, cigarette smoking was associated with an inflammatory state in the accessory glands and in the testis, as shown by enriched proteomic pathways. This state causes an alteration in sperm functional quality, which is characterized by decreased acrosome integrity and mitochondrial activity, as well as by increased nuclear DNA fragmentation. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

Distributed and Collaborative Software Analysis

NASA Astrophysics Data System (ADS)

Ghezzi, Giacomo; Gall, Harald C.

Throughout the years software engineers have come up with a myriad of specialized tools and techniques that focus on a certain type of software analysissoftware analysis such as source code analysis, co-change analysis or bug prediction. However, easy and straight forward synergies between these analyses and tools rarely exist because of their stand-alone nature, their platform dependence, their different input and output formats and the variety of data to analyze. As a consequence, distributed and collaborative software analysiscollaborative software analysis scenarios and in particular interoperability are severely limited. We describe a distributed and collaborative software analysis platform that allows for a seamless interoperability of software analysis tools across platform, geographical and organizational boundaries. We realize software analysis tools as services that can be accessed and composed over the Internet. These distributed analysis services shall be widely accessible in our incrementally augmented Software Analysis Broker software analysis broker where organizations and tool providers can register and share their tools. To allow (semi-) automatic use and composition of these tools, they are classified and mapped into a software analysis taxonomy and adhere to specific meta-models and ontologiesontologies for their category of analysis.

High-throughput transcriptome sequencing analysis provides preliminary insights into the biotransformation mechanism of Rhodopseudomonas palustris treated with alpha-rhamnetin-3-rhamnoside.

PubMed

Bi, Lei; Guan, Chun-jie; Yang, Guan-e; Yang, Fei; Yan, Hong-yu; Li, Qing-shan

2016-04-01

The purple photosynthetic bacterium Rhodopseudomonas palustris has been widely applied to enhance the therapeutic effects of traditional Chinese medicine using novel biotransformation technology. However, comprehensive studies of the R. palustris biotransformation mechanism are rare. Therefore, investigation of the expression patterns of genes involved in metabolic pathways that are active during the biotransformation process is essential to elucidate this complicated mechanism. To promote further study of the biotransformation of R. palustris, we assembled all R. palustris transcripts using Trinity software and performed differential expression analysis of the resulting unigenes. A total of 9725, 7341 and 10,963 unigenes were obtained by assembling the alpha-rhamnetin-3-rhamnoside-treated R. palustris (RPB) reads, control R. palustris (RPS) reads and combined RPB&RPS reads, respectively. A total of 9971 unigenes assembled from the RPB&RPS reads were mapped to the nr, nt, Swiss-Prot, Gene Ontology (GO), Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (E-value <0.00001) databases using BLAST software. A total of 3360 unique differentially expressed genes (DEGs) in RPB versus RPS were identified, among which 922 unigenes were up-regulated and 2438 were down-regulated. The unigenes were mapped to the KEGG database, resulting in the identification of 7676 pathways among all annotated unigenes and 2586 pathways among the DEGs. Some sets of functional unigenes annotated to important metabolic pathways and environmental information processing were differentially expressed between the RPS and RPB samples, including those involved in energy metabolism (18.4% of total DEGs), carbohydrate metabolism (36.0% of total DEGs), ABC transport (6.0% of total DEGs), the two-component system (8.6% of total DEGs), cell motility (4.3% of total DEGs) and the cell cycle (1.5% of total DEGs). We also identified 19 transcripts annotated as hydrolytic enzymes and other enzymes involved in ARR catabolism in R. palustris. We present the first comparative transcriptome profiles of RPB and RPS samples to facilitate elucidation of the molecular mechanism of biotransformation in R. palustris. Furthermore, we propose two putative ARR biotransformation mechanisms in R. palustris. These analytical results represent a useful genomic resource for in-depth research into the molecular basis of biotransformation and genetic modification in R. palustris. Copyright © 2016 Elsevier GmbH. All rights reserved.

Gene Expression and Pathway Analysis of Effects of the CMAH Deactivation on Mouse Lung, Kidney and Heart

PubMed Central

Kwon, Deug-Nam; Chang, Byung-Soo; Kim, Jin-Hoi

2014-01-01

Background N-glycolylneuraminic acid (Neu5Gc) is generated by hydroxylation of CMP-Neu5Ac to CMP-Neu5Gc, catalyzed by CMP-Neu5Ac hydroxylase (CMAH). However, humans lack this common mammalian cell surface molecule, Neu5Gc, due to inactivation of the CMAH gene during evolution. CMAH is one of several human-specific genes whose function has been lost by disruption or deletion of the coding frame. It has been suggested that CMAH inactivation has resulted in biochemical or physiological characteristics that have resulted in human-specific diseases. Methodology/Principal Findings To identify differential gene expression profiles associated with the loss of Neu5Gc expression, we performed microarray analysis using Illumina MouseRef-8 v2 Expression BeadChip, using the main tissues (lung, kidney, and heart) from control mice and CMP-Neu5Ac hydroxylase (Cmah) gene knock-out mice, respectively. Out of a total of 25,697 genes, 204, 162, and 147 genes were found to be significantly modulated in the lung, kidney, and heart tissues of the Cmah null mouse, respectively. In this study, we examined the gene expression profiles, using three commercial pathway analysis software packages: Ingenuity Pathways Analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and Pathway Studio. The gene ontology analysis revealed that the top 6 biological processes of these genes included protein metabolism and modification, signal transduction, lipid, fatty acid, and steroid metabolism, nucleoside, nucleotide and nucleic acid metabolism, immunity and defense, and carbohydrate metabolism. Gene interaction network analysis showed a common network that was common to the different tissues of the Cmah null mouse. However, the expression of most sialytransferase mRNAs of Hanganutziu-Deicher antigen, sialy-Tn antigen, Forssman antigen, and Tn antigen was significantly down-regulated in the liver tissue of Cmah null mice. Conclusions/Significance Mice bearing a human-like deletion of the Cmah gene serve as an important model for the study of abnormal pathogenesis and/or metabolism caused by the evolutionary loss of Neu5Gc synthesis in humans. PMID:25229777

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

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

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

PubMed Central

Gao, Jianjiong; Aksoy, Bülent Arman; Dogrusoz, Ugur; Dresdner, Gideon; Gross, Benjamin; Sumer, S. Onur; Sun, Yichao; Jacobsen, Anders; Sinha, Rileen; Larsson, Erik; Cerami, Ethan; Sander, Chris; Schultz, Nikolaus

2014-01-01

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. PMID:23550210

Computational Tools for Metabolic Engineering

PubMed Central

Copeland, Wilbert B.; Bartley, Bryan A.; Chandran, Deepak; Galdzicki, Michal; Kim, Kyung H.; Sleight, Sean C.; Maranas, Costas D.; Sauro, Herbert M.

2012-01-01

A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area. PMID:22629572

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data.

PubMed

Uppal, Karan; Soltow, Quinlyn A; Strobel, Frederick H; Pittard, W Stephen; Gernert, Kim M; Yu, Tianwei; Jones, Dean P

2013-01-16

Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract m/z features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation. xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution m/z matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites. xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.

Understanding consumer and clinician preferences and decision making for rehabilitation following arthroplasty in the private sector.

PubMed

Buhagiar, Mark A; Naylor, Justine M; Simpson, Grahame; Harris, Ian A; Kohler, Friedbert

2017-06-19

To understand private consumer and clinician preferences towards different rehabilitation modes following knee or hip arthroplasty, and identify factors which influence the chosen rehabilitation pathway. Mixed methods cross-sectional study involving 95 semi-structured interviews of consumers (patients and carers) and clinicians (arthroplasty surgeons, physiotherapists and rehabilitation physicians) in Sydney, Australia, during 2014-2015. Participants were asked about the acceptability of different modes of rehabilitation provision, and factors influencing their chosen rehabilitation pathway. Interviews were in person or via the telephone. Qualitative analysis software was used to electronically manage qualitative data. An analytical approach guided data analysis. Pre-operative preferences strongly influenced the type of rehabilitation chosen by consumers. Key factors that influenced this were both intrinsic and extrinsic, including; the previous experience of self or known others, the perceived benefits of the chosen mode, a sense of entitlement, the role of orthopaedic surgeons and influence of patient preference, a patient's clinical status post-surgery, the private hospital business model and insurance provider involvement. The acceptability of rehabilitation modes varied between clinician groups. No one rehabilitation mode provided following arthroplasty is singularly preferred by stakeholders. Factors other than the belief that a particular mode was more effective than another appear to dominate the pathway followed by private arthroplasty consumers, indicating evidence-based policies around rehabilitation provision may have limited appeal in the private sector.

Prediction of functional profiles of gut microbiota from 16S rRNA metagenomic data provides a more robust evaluation of gut dysbiosis occurring in Japanese type 2 diabetic patients.

PubMed

Inoue, Ryo; Ohue-Kitano, Ryuji; Tsukahara, Takamitsu; Tanaka, Masashi; Masuda, Shinya; Inoue, Takayuki; Yamakage, Hajime; Kusakabe, Toru; Hasegawa, Koji; Shimatsu, Akira; Satoh-Asahara, Noriko

2017-11-01

We assessed whether gut microbial functional profiles predicted from 16S rRNA metagenomics differed in Japanese type 2 diabetic patients. A total of 22 Japanese subjects were recruited from our outpatient clinic in an observational study. Fecal samples were obtained from 12 control and 10 type 2 diabetic subjects. 16S rRNA metagenomic data were generated and functional profiles predicted using "Phylogenetic Investigation of Communities by Reconstruction of Unobserved States" software. We measured the parameters of glucose metabolism, gut bacterial taxonomy and functional profile, and examined the associations in a cross-sectional manner. Eleven of 288 "Kyoto Encyclopedia of Genes and Genomes" pathways were significantly enriched in diabetic patients compared with control subjects ( p <0.05, q<0.1). The relative abundance of almost all pathways, including the Insulin signaling pathway and Glycolysis/Gluconeogenesis , showed strong, positive correlations with hemoglobin A 1c (HbA 1c ) and fasting plasma glucose (FPG) levels. Bacterial taxonomic analysis showed that genus Blautia significantly differed between groups and had negative correlations with HbA 1c and FPG levels. Our findings suggest a novel pathophysiological relationship between gut microbial communities and diabetes, further highlighting the significance and utility of combining prediction of functional profiles with ordinal bacterial taxonomic analysis (UMIN Clinical Trails Registry number: UMIN000026592).

MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data.

PubMed

Lee, Sangseon; Park, Youngjune; Kim, Sun

2017-07-15

Pathway based analysis of high throughput transcriptome data is a widely used approach to investigate biological mechanisms. Since a pathway consists of multiple functions, the recent approach is to determine condition specific sub-pathways or subpaths. However, there are several challenges. First, few existing methods utilize explicit gene expression information from RNA-seq. More importantly, subpath activity is usually an average of statistical scores, e.g., correlations, of edges in a candidate subpath, which fails to reflect gene expression quantity information. In addition, none of existing methods can handle multiple phenotypes. To address these technical problems, we designed and implemented an algorithm, MIDAS, that determines condition specific subpaths, each of which has different activities across multiple phenotypes. MIDAS utilizes gene expression quantity information fully and the network centrality information to determine condition specific subpaths. To test performance of our tool, we used TCGA breast cancer RNA-seq gene expression profiles with five molecular subtypes. 36 differentially activate subpaths were determined. The utility of our method, MIDAS, was demonstrated in four ways. All 36 subpaths are well supported by the literature information. Subsequently, we showed that these subpaths had a good discriminant power for five cancer subtype classification and also had a prognostic power in terms of survival analysis. Finally, in a performance comparison of MIDAS to a recent subpath prediction method, PATHOME, our method identified more subpaths and much more genes that are well supported by the literature information. http://biohealth.snu.ac.kr/software/MIDAS/. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Examining the architecture of cellular computing through a comparative study with a computer.

PubMed

Wang, Degeng; Gribskov, Michael

2005-06-22

The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software-hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's "hardware" equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the "bandwidth" of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed.

Development of an image-based screening system for inhibitors of the plastidial MEP pathway and of protein geranylgeranylation

PubMed Central

Hartmann, Michael; Gas-Pascual, Elisabet; Hemmerlin, Andrea; Rohmer, Michel; Bach, Thomas J.

2015-01-01

In a preceding study we have recently established an in vivo visualization system for the geranylgeranylation of proteins in a stably transformed tobacco BY-2 cell line, which involves expressing a dexamethasone-inducible GFP fused to the prenylable, carboxy-terminal basic domain of the rice calmodulin CaM61, which naturally bears a CaaL geranylgeranylation motif (GFP-BD-CVIL). By using pathway-specific inhibitors it was there demonstrated that inhibition of the methylerythritol phosphate (MEP) pathway with oxoclomazone and fosmidomycin, as well as inhibition of protein geranylgeranyl transferase type 1 (PGGT-1), shifted the localization of the GFP-BD-CVIL protein from the membrane to the nucleus. In contrast, the inhibition of the mevalonate (MVA) pathway with mevinolin did not affect this localization. Furthermore, in this initial study complementation assays with pathway-specific intermediates confirmed that the precursors for the cytosolic isoprenylation of this fusion protein are predominantly provided by the MEP pathway. In order to optimize this visualization system from a more qualitative assay to a statistically trustable medium or a high-throughput screening system, we established now new conditions that permit culture and analysis in 96-well microtiter plates, followed by fluorescence microscopy. For further refinement, the existing GFP-BD-CVIL cell line was transformed with an estradiol-inducible vector driving the expression of a RFP protein, C-terminally fused to a nuclear localization signal (NLS-RFP). We are thus able to quantify the total number of viable cells versus the number of inhibited cells after various treatments. This approach also includes a semi-automatic counting system, based on the freely available image processing software. As a result, the time of image analysis as well as the risk of user-generated bias is reduced to a minimum. Moreover, there is no cross-induction of gene expression by dexamethasone and estradiol, which is an important prerequisite for this test system. PMID:26309725

Software Tool for Researching Annotations of Proteins (STRAP): Open-Source Protein Annotation Software with Data Visualization

PubMed Central

Bhatia, Vivek N.; Perlman, David H.; Costello, Catherine E.; McComb, Mark E.

2009-01-01

In order that biological meaning may be derived and testable hypotheses may be built from proteomics experiments, assignments of proteins identified by mass spectrometry or other techniques must be supplemented with additional notation, such as information on known protein functions, protein-protein interactions, or biological pathway associations. Collecting, organizing, and interpreting this data often requires the input of experts in the biological field of study, in addition to the time-consuming search for and compilation of information from online protein databases. Furthermore, visualizing this bulk of information can be challenging due to the limited availability of easy-to-use and freely available tools for this process. In response to these constraints, we have undertaken the design of software to automate annotation and visualization of proteomics data in order to accelerate the pace of research. Here we present the Software Tool for Researching Annotations of Proteins (STRAP) – a user-friendly, open-source C# application. STRAP automatically obtains gene ontology (GO) terms associated with proteins in a proteomics results ID list using the freely accessible UniProtKB and EBI GOA databases. Summarized in an easy-to-navigate tabular format, STRAP includes meta-information on the protein in addition to complimentary GO terminology. Additionally, this information can be edited by the user so that in-house expertise on particular proteins may be integrated into the larger dataset. STRAP provides a sortable tabular view for all terms, as well as graphical representations of GO-term association data in pie (biological process, cellular component and molecular function) and bar charts (cross comparison of sample sets) to aid in the interpretation of large datasets and differential analyses experiments. Furthermore, proteins of interest may be exported as a unique FASTA-formatted file to allow for customizable re-searching of mass spectrometry data, and gene names corresponding to the proteins in the lists may be encoded in the Gaggle microformat for further characterization, including pathway analysis. STRAP, a tutorial, and the C# source code are freely available from http://cpctools.sourceforge.net. PMID:19839595

Genome-wide association study meta-analysis identifies five new loci for systemic lupus erythematosus.

PubMed

Julià, Antonio; López-Longo, Francisco Javier; Pérez Venegas, José J; Bonàs-Guarch, Silvia; Olivé, Àlex; Andreu, José Luís; Aguirre-Zamorano, Mª Ángeles; Vela, Paloma; Nolla, Joan M; de la Fuente, José Luís Marenco; Zea, Antonio; Pego-Reigosa, José María; Freire, Mercedes; Díez, Elvira; Rodríguez-Almaraz, Esther; Carreira, Patricia; Blanco, Ricardo; Taboada, Víctor Martínez; López-Lasanta, María; Corbeto, Mireia López; Mercader, Josep M; Torrents, David; Absher, Devin; Marsal, Sara; Fernández-Nebro, Antonio

2018-05-30

Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with a complex genetic inheritance. Genome-wide association studies (GWAS) have significantly increased the number of significant loci associated with SLE risk. To date, however, established loci account for less than 30% of the disease heritability and additional risk variants have yet to be identified. Here we performed a GWAS followed by a meta-analysis to identify new genome-wide significant loci for SLE. We genotyped a cohort of 907 patients with SLE (cases) and 1524 healthy controls from Spain and performed imputation using the 1000 Genomes reference data. We tested for association using logistic regression with correction for the principal components of variation. Meta-analysis of the association results was subsequently performed on 7,110,321 variants using genetic data from a large cohort of 4036 patients with SLE and 6959 controls of Northern European ancestry. Genetic association was also tested at the pathway level after removing the effect of known risk loci using PASCAL software. We identified five new loci associated with SLE at the genome-wide level of significance (p < 5 × 10 - 8 ): GRB2, SMYD3, ST8SIA4, LAT2 and ARHGAP27. Pathway analysis revealed several biological processes significantly associated with SLE risk: B cell receptor signaling (p = 5.28 × 10 - 6 ), CTLA4 co-stimulation during T cell activation (p = 3.06 × 10 - 5 ), interleukin-4 signaling (p = 3.97 × 10 - 5 ) and cell surface interactions at the vascular wall (p = 4.63 × 10 - 5 ). Our results identify five novel loci for SLE susceptibility, and biologic pathways associated via multiple low-effect-size loci.

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.

Gene expression, signal transduction pathways and functional networks associated with growth of sporadic vestibular schwannomas.

PubMed

Sass, Hjalte C R; Borup, Rehannah; Alanin, Mikkel; Nielsen, Finn Cilius; Cayé-Thomasen, Per

2017-01-01

The objective of this study was to determine global gene expression in relation to Vestibular schwannomas (VS) growth rate and to identify signal transduction pathways and functional molecular networks associated with growth. Repeated magnetic resonance imaging (MRI) prior to surgery determined tumor growth rate. Following tissue sampling during surgery, mRNA was extracted from 16 sporadic VS. Double stranded cDNA was synthesized from the mRNA and used as template for in vitro transcription reaction to synthesize biotin-labeled antisense cRNA, which was hybridized to Affymetrix HG-U133A arrays and analyzed by dChip software. Differential gene expression was defined as a 1.5-fold difference between fast and slow growing tumors (><0.5 ccm/year), employing a p-value <0.01. Deregulated transcripts were matched against established gene ontology. Ingenuity Pathway Analysis was used for identification of signal transduction pathways and functional molecular networks associated with tumor growth. In total 109 genes were deregulated in relation to tumor growth rate. Genes associated with apoptosis, growth and cell proliferation were deregulated. Gene ontology included regulation of the cell cycle, cell differentiation and proliferation, among other functions. Fourteen pathways were associated with tumor growth. Five functional molecular networks were generated. This first study on global gene expression in relation to vestibular schwannoma growth rate identified several genes, signal transduction pathways and functional networks associated with tumor progression. Specific genes involved in apoptosis, cell growth and proliferation were deregulated in fast growing tumors. Fourteen pathways were associated with tumor growth. Generated functional networks underlined the importance of the PI3K family, among others.

Stochastic computing with biomolecular automata

PubMed Central

Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud

2004-01-01

Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure. PMID:15215499

Causal network analysis of head and neck keloid tissue identifies potential master regulators.

PubMed

Garcia-Rodriguez, Laura; Jones, Lamont; Chen, Kang Mei; Datta, Indrani; Divine, George; Worsham, Maria J

2016-10-01

To generate novel insights and hypotheses in keloid development from potential master regulators. Prospective cohort. Six fresh keloid and six normal skin samples from 12 anonymous donors were used in a prospective cohort study. Genome-wide profiling was done previously on the cohort using the Infinium HumanMethylation450 BeadChip (Illumina, San Diego, CA). The 190 statistically significant CpG islands between keloid and normal tissue mapped to 152 genes (P < .05). The top 10 statistically significant genes (VAMP5, ACTR3C, GALNT3, KCNAB2, LRRC61, SCML4, SYNGR1, TNS1, PLEKHG5, PPP1R13-α, false discovery rate <.015) were uploaded into the Ingenuity Pathway Analysis software's Causal Network Analysis (QIAGEN, Redwood City, CA). To reflect expected gene expression direction in the context of methylation changes, the inverse of the methylation ratio from keloid versus normal tissue was used for the analysis. Causal Network Analysis identified disease-specific master regulator molecules based on downstream differentially expressed keloid-specific genes and expected directionality of expression (hypermethylated vs. hypomethylated). Causal Network Analysis software identified four hierarchical networks that included four master regulators (pyroxamide, tributyrin, PRKG2, and PENK) and 19 intermediate regulators. Causal Network Analysis of differentiated methylated gene data of keloid versus normal skin demonstrated four causal networks with four master regulators. These hierarchical networks suggest potential driver roles for their downstream keloid gene targets in the pathogenesis of the keloid phenotype, likely triggered due to perturbation/injury to normal tissue. NA Laryngoscope, 126:E319-E324, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Computation of elementary modes: a unifying framework and the new binary approach

PubMed Central

Gagneur, Julien; Klamt, Steffen

2004-01-01

Background Metabolic pathway analysis has been recognized as a central approach to the structural analysis of metabolic networks. The concept of elementary (flux) modes provides a rigorous formalism to describe and assess pathways and has proven to be valuable for many applications. However, computing elementary modes is a hard computational task. In recent years we assisted in a multiplication of algorithms dedicated to it. We require a summarizing point of view and a continued improvement of the current methods. Results We show that computing the set of elementary modes is equivalent to computing the set of extreme rays of a convex cone. This standard mathematical representation provides a unified framework that encompasses the most prominent algorithmic methods that compute elementary modes and allows a clear comparison between them. Taking lessons from this benchmark, we here introduce a new method, the binary approach, which computes the elementary modes as binary patterns of participating reactions from which the respective stoichiometric coefficients can be computed in a post-processing step. We implemented the binary approach in FluxAnalyzer 5.1, a software that is free for academics. The binary approach decreases the memory demand up to 96% without loss of speed giving the most efficient method available for computing elementary modes to date. Conclusions The equivalence between elementary modes and extreme ray computations offers opportunities for employing tools from polyhedral computation for metabolic pathway analysis. The new binary approach introduced herein was derived from this general theoretical framework and facilitates the computation of elementary modes in considerably larger networks. PMID:15527509

Prophylactic accessory-pathway ablation in asymptomatic patients with a Wolff-Parkinson-White electrocardiographic pattern.

PubMed

Ozenc, S; Iscen, S; Kibrisli, E; Tok, D; Parlak, A; Altinel, O; Altinel, S

2014-01-01

The optimal approach is controversial in asymptomatic patients who are coincidentally found to have evidence of an accessory pathway (AP) on an ECG. The risk of sudden cardiac death (SCD) is low, and the risk of developing symptoms also appears to be low, although a wide range of incidences have been reported. In our trial, we tested the hypothesis that if prophylactic accessory-pathway ablation performed at the time of the initial electrophysiological testing would improve the long-term outcome in asymptomatic patients with a Wolff-Parkinson-White electrocardiographic pattern. Recruitment of patients began on February 1, 2004, and ended on February 5, 2009. All 110 asymptomatic patients were hospitalized and underwent electrophysiological testing the same day to assess the inducibility of atrioventricular reciprocating tachycardia. The anterograde effective refractory period of the accessory pathway was defined as the longest coupling interval at which anterograde block in the bypass tract was observed. For the statistical analysis, the statistical software SPSS version 15.0 for Windows (SPSS Inc., Chicago, IL, USA). Of 110 asymptomatic patients with a Wolff-Parkinson-White electrocardiographic pattern, 80 patients were ablated. Ablation group consisted of these patients. Control group consisted of remaining 30 and were divided into two groups according to the anterograde effective refractory period of the accessory pathway. There was no significant difference between three groups in terms of arrhythmic events (p: 0.58). Asymptomatic patients with the Wolff-Parkinson-White syndrome do not require prophylactic ablation, since they remain asymptomatic for many years.

From damage to discovery via virtual unwrapping: Reading the scroll from En-Gedi

PubMed Central

Seales, William Brent; Parker, Clifford Seth; Segal, Michael; Tov, Emanuel; Shor, Pnina; Porath, Yosef

2016-01-01

Computer imaging techniques are commonly used to preserve and share readable manuscripts, but capturing writing locked away in ancient, deteriorated documents poses an entirely different challenge. This software pipeline—referred to as “virtual unwrapping”—allows textual artifacts to be read completely and noninvasively. The systematic digital analysis of the extremely fragile En-Gedi scroll (the oldest Pentateuchal scroll in Hebrew outside of the Dead Sea Scrolls) reveals the writing hidden on its untouchable, disintegrating sheets. Our approach for recovering substantial ink-based text from a damaged object results in readable columns at such high quality that serious critical textual analysis can occur. Hence, this work creates a new pathway for subsequent textual discoveries buried within the confines of damaged materials. PMID:27679821

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

PubMed Central

2012-01-01

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods. Reviewers This article was reviewed by Arcady Mushegian, Byung-Soo Kim and Joel Bader. PMID:23227854

Tutorial: Crystal orientations and EBSD — Or which way is up?

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

Britton, T.B., E-mail: b.britton@imperial.ac.uk; Jiang, J.; Guo, Y.

2016-07-15

Electron backscatter diffraction (EBSD) is an automated technique that can measure the orientation of crystals in a sample very rapidly. There are many sophisticated software packages that present measured data. Unfortunately, due to crystal symmetry and differences in the set-up of microscope and EBSD software, there may be accuracy issues when linking the crystal orientation to a particular microstructural feature. In this paper we outline a series of conventions used to describe crystal orientations and coordinate systems. These conventions have been used to successfully demonstrate that a consistent frame of reference is used in the sample, unit cell, pole figuremore » and diffraction pattern frames of reference. We establish a coordinate system rooted in measurement of the diffraction pattern and subsequently link this to all other coordinate systems. A fundamental outcome of this analysis is to note that the beamshift coordinate system needs to be precisely defined for consistent 3D microstructure analysis. This is supported through a series of case studies examining particular features of the microscope settings and/or unambiguous crystallographic features. These case studies can be generated easily in most laboratories and represent an opportunity to demonstrate confidence in use of recorded orientation data. Finally, we include a simple software tool, written in both MATLAB® and Python, which the reader can use to compare consistency with their own microscope set-up and which may act as a springboard for further offline analysis. - Highlights: • Presentation of conventions used to describe crystal orientations • Three case studies that outline how conventions are consistent • Demonstrates a pathway for calibration and validation of EBSD based orientation measurements • EBSD computer code supplied for validation by the reader.« less

Orbiter subsystem hardware/software interaction analysis. Volume 8: AFT reaction control system, part 2

NASA Technical Reports Server (NTRS)

Becker, D. D.

1980-01-01

The orbiter subsystems and interfacing program elements which interact with the orbiter computer flight software are analyzed. The failure modes identified in the subsystem/element failure mode and effects analysis are examined. Potential interaction with the software is examined through an evaluation of the software requirements. The analysis is restricted to flight software requirements and excludes utility/checkout software. The results of the hardware/software interaction analysis for the forward reaction control system are presented.

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

PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

PubMed

Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

2017-01-04

The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3)

NASA Astrophysics Data System (ADS)

Katz, Daniel S.; Choi, Sou-Cheng T.; Niemeyer, Kyle E.; Hetherington, James; Löffler, Frank; Gunter, Dan; Idaszak, Ray; Brandt, Steven R.; Miller, Mark A.; Gesing, Sandra; Jones, Nick D.; Weber, Nic; Marru, Suresh; Allen, Gabrielle; Penzenstadler, Birgit; Venters, Colin C.; Davis, Ethan; Hwang, Lorraine; Todorov, Ilian; Patra, Abani; de Val-Borro, Miguel

2016-02-01

This report records and discusses the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3). The report includes a description of the keynote presentation of the workshop, which served as an overview of sustainable scientific software. It also summarizes a set of lightning talks in which speakers highlighted to-the-point lessons and challenges pertaining to sustaining scientific software. The final and main contribution of the report is a summary of the discussions, future steps, and future organization for a set of self-organized working groups on topics including developing pathways to funding scientific software; constructing useful common metrics for crediting software stakeholders; identifying principles for sustainable software engineering design; reaching out to research software organizations around the world; and building communities for software sustainability. For each group, we include a point of contact and a landing page that can be used by those who want to join that group's future activities. The main challenge left by the workshop is to see if the groups will execute these activities that they have scheduled, and how the WSSSPE community can encourage this to happen.

High mobility group box associated with cell proliferation appears to play an important role in hepatocellular carcinogenesis in rats and humans.

PubMed

Suzuki, Shugo; Takeshita, Kentaro; Asamoto, Makoto; Takahashi, Satoru; Kandori, Hitoshi; Tsujimura, Kazunari; Saito, Fumiyo; Masuko, Kazuo; Shirai, Tomoyuki

2009-01-31

To identify genes important in hepatocellular carcinogenesis, especially processes involved in malignant transformation, we focused on differences in gene expression between adenomas and carcinomas by DNA microarray. Eighty-one genes for which expression was specific in carcinomas were analyzed using Ingenuity Pathway Analysis software and Gene Ontology, and found to be associated with TP53 and regulators of cell proliferation. In the genes associated with TP53, we selected high mobility group box (HMGB) for detailed analysis. Immunohistochemistry revealed expression of HMGBs in carcinomas to be significantly higher than in other lesions among both human and rat liver, and a positive correlation between HMGBs and TP53 was detected in rat carcinomas. Knock-down of HMGB 2 expression in a rat hepatocellular carcinoma cell line by RNAi resulted in inhibition of cell growth, although no effects on invasion were evident in vitro. These results suggest that acquisition of malignant potential in the liver requires specific signaling pathways related to high cell proliferation associated with TP53. In particular, HMGBs appear to have an important role for progression and cell proliferation associated with loss of TP53 function in rat and in human hepatocarcinogenesis.

Systems Biology Reveals NS4B-Cyclophilin A Interaction: A New Target to Inhibit YFV Replication.

PubMed

Vidotto, Alessandra; Morais, Ana T S; Ribeiro, Milene R; Pacca, Carolina C; Terzian, Ana C B; Gil, Laura H V G; Mohana-Borges, Ronaldo; Gallay, Philippe; Nogueira, Mauricio L

2017-04-07

Yellow fever virus (YFV) replication is highly dependent on host cell factors. YFV NS4B is reported to be involved in viral replication and immune evasion. Here interactions between NS4B and human proteins were determined using a GST pull-down assay and analyzed using 1-DE and LC-MS/MS. We present a total of 207 proteins confirmed using Scaffold 3 Software. Cyclophilin A (CypA), a protein that has been shown to be necessary for the positive regulation of flavivirus replication, was identified as a possible NS4B partner. 59 proteins were found to be significantly increased when compared with a negative control, and CypA exhibited the greatest difference, with a 22-fold change. Fisher's exact test was significant for 58 proteins, and the p value of CypA was the most significant (0.000000019). The Ingenuity Systems software identified 16 pathways, and this analysis indicated sirolimus, an mTOR pathway inhibitor, as a potential inhibitor of CypA. Immunofluorescence and viral plaque assays showed a significant reduction in YFV replication using sirolimus and cyclosporine A (CsA) as inhibitors. Furthermore, YFV replication was strongly inhibited in cells treated with both inhibitors using reporter BHK-21-rep-YFV17D-LucNeoIres cells. Taken together, these data suggest that CypA-NS4B interaction regulates YFV replication. Finally, we present the first evidence that YFV inhibition may depend on NS4B-CypA interaction.

Techno-economic analysis for a sugarcane biorefinery: Colombian case.

PubMed

Moncada, Jonathan; El-Halwagi, Mahmoud M; Cardona, Carlos A

2013-05-01

In this paper a techno-economic analysis for a sugarcane biorefinery is presented for the Colombian case. It is shown two scenarios for different conversion pathways as function of feedstock distribution and technologies for sugar, fuel ethanol, PHB, anthocyanins and electricity production. These scenarios are compared with the Colombian base case which simultaneously produce sugar, fuel ethanol and electricity. A simulation procedure was used in order to evaluate biorefinery schemes for all the scenarios, using Aspen Plus software, that include productivity analysis, energy calculations and economic evaluation for each process configuration. The results showed that the configuration with the best economic, environmental and social performance is the one that considers fuel ethanol and PHB production from combined cane bagasse and molasses. This result served as the basis to draw recommendations on technological and economic feasibility as well as social aspects for the implementation of such type of biorefinery in Colombia. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Four applications of a software data collection and analysis methodology

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Selby, Richard W., Jr.

1985-01-01

The evaluation of software technologies suffers because of the lack of quantitative assessment of their effect on software development and modification. A seven-step data collection and analysis methodology couples software technology evaluation with software measurement. Four in-depth applications of the methodology are presented. The four studies represent each of the general categories of analyses on the software product and development process: blocked subject-project studies, replicated project studies, multi-project variation studies, and single project strategies. The four applications are in the areas of, respectively, software testing, cleanroom software development, characteristic software metric sets, and software error analysis.

Gene Expression Profiling Confirms the Dosage-Dependent Additive Neuroprotective Effects of Jasminoidin in a Mouse Model of Ischemia-Reperfusion Injury.

PubMed

Li, Haixia; Wang, Jingtao; Wang, Pengqian; Zhang, Yingying; Liu, Jun; Yu, Yanan; Li, Bing; Wang, Zhong

2018-01-01

Recent evidence demonstrates that a double dose of Jasminoidin (2·JA) is more effective than Jasminoidin (JA) in cerebral ischemia therapy, but its dosage-effect mechanisms are unclear. In this study, the software GeneGo MetaCore was used to perform pathway analysis of the differentially expressed genes obtained in microarrays of mice belonging to four groups (Sham, Vehicle, JA, and 2·JA), aiming to elucidate differences in JA and 2·JA's dose-dependent pharmacological mechanism from a system's perspective. The top 10 enriched pathways in the 2·JA condition were mainly involved in neuroprotection (70% of the pathways), apoptosis and survival (40%), and anti-inflammation (20%), while JA induced pathways were mainly involved in apoptosis and survival (60%), anti-inflammation (20%), and lipid metabolism (20%). Regarding shared pathways and processes, 3, 1, and 3 pathways overlapped between the Vehicle and JA, Vehicle and 2·JA, and JA and 2·JA conditions, respectively; for the top ten overlapped processes these numbers were 3, 0, and 4, respectively. The common pathways and processes in the 2·JA condition included differentially expressed genes significantly different from those in JA. Seven representative pathways were only activated by 2·JA, such as Gamma-Secretase regulation of neuronal cell development. Process network comparison indicated that significant nodes, such as alpha-MSH , ACTH , PKR1 , and WNT , were involved in the pharmacological mechanism of 2·JA. Function distribution was different between JA and 2·JA groups, indicating a dosage additive mechanism in cerebral ischemia treatment. Such systemic approach based on whole-genome multiple pathways and networks may provide an effective and alternative approach to identify alterations underlining dosage-dependent therapeutic benefits of pharmacological compounds on complex disease processes.

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Harnessing cell-to-cell variations to probe bacterial structure and biophysics

NASA Astrophysics Data System (ADS)

Cass, Julie A.

Advances in microscopy and biotechnology have given us novel insights into cellular biology and physics. While bacteria were long considered to be relatively unstructured, the development of fluorescence microscopy techniques, and spatially and temporally resolved high-throughput quantitative studies, have uncovered that the bacterial cell is highly organized, and its structure rigorously maintained. In this thesis I will describe our gateTool software, designed to harness cell-to-cell variations to probe bacterial structure, and discuss two exciting aspects of structure that we have employed gateTool to investigate: (i) chromosome organization and the cellular mechanisms for controlling DNA dynamics, and (ii) the study of cell wall synthesis, and how the genes in the synthesis pathway impact cellular shape. In the first project, we develop a spatial and temporal mapping of cell-cycle-dependent chromosomal organization, and use this quantitative map to discover that chromosomal loci segregate from midcell with universal dynamics. In the second project, I describe preliminary time- lapse and snapshot imaging analysis suggesting phentoypical coherence across peptidoglycan synthesis pathways.

The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

DOE PAGES

Walsh, Jesse R.; Schaeffer, Mary L.; Zhang, Peifen; ...

2016-11-29

As metabolic pathway resources become more commonly available, researchers have unprecedented access to information about their organism of interest. Despite efforts to ensure consistency between various resources, information content and quality can vary widely. Two maize metabolic pathway resources for the B73 inbred line, CornCyc 4.0 and MaizeCyc 2.2, are based on the same gene model set and were developed using Pathway Tools software. These resources differ in their initial enzymatic function assignments and in the extent of manual curation. Here, we present an in-depth comparison between CornCyc and MaizeCyc to demonstrate the effect of initial computational enzymatic function assignmentsmore » on the quality and content of metabolic pathway resources.« less

The quality of metabolic pathway resources depends on initial enzymatic function assignments: a case for maize

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

Walsh, Jesse R.; Schaeffer, Mary L.; Zhang, Peifen

As metabolic pathway resources become more commonly available, researchers have unprecedented access to information about their organism of interest. Despite efforts to ensure consistency between various resources, information content and quality can vary widely. Two maize metabolic pathway resources for the B73 inbred line, CornCyc 4.0 and MaizeCyc 2.2, are based on the same gene model set and were developed using Pathway Tools software. These resources differ in their initial enzymatic function assignments and in the extent of manual curation. Here, we present an in-depth comparison between CornCyc and MaizeCyc to demonstrate the effect of initial computational enzymatic function assignmentsmore » on the quality and content of metabolic pathway resources.« less

SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases

PubMed Central

Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A

2018-01-01

Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this strategy will significantly advance the curation status of all organism-specific databases in SolCyc resulting in the improvement on database accuracy, data analysis and visualization of biochemical networks in those species. Database URL https://solgenomics.net/tools/solcyc/ PMID:29762652

Efficacy of a Newly Designed Cephalometric Analysis Software for McNamara Analysis in Comparison with Dolphin Software.

PubMed

Nouri, Mahtab; Hamidiaval, Shadi; Akbarzadeh Baghban, Alireza; Basafa, Mohammad; Fahim, Mohammad

2015-01-01

Cephalometric norms of McNamara analysis have been studied in various populations due to their optimal efficiency. Dolphin cephalometric software greatly enhances the conduction of this analysis for orthodontic measurements. However, Dolphin is very expensive and cannot be afforded by many clinicians in developing countries. A suitable alternative software program in Farsi/English will greatly help Farsi speaking clinicians. The present study aimed to develop an affordable Iranian cephalometric analysis software program and compare it with Dolphin, the standard software available on the market for cephalometric analysis. In this diagnostic, descriptive study, 150 lateral cephalograms of normal occlusion individuals were selected in Mashhad and Qazvin, two major cities of Iran mainly populated with Fars ethnicity, the main Iranian ethnic group. After tracing the cephalograms, the McNamara analysis standards were measured both with Dolphin and the new software. The cephalometric software was designed using Microsoft Visual C++ program in Windows XP. Measurements made with the new software were compared with those of Dolphin software on both series of cephalograms. The validity and reliability were tested using intra-class correlation coefficient. Calculations showed a very high correlation between the results of the Iranian cephalometric analysis software and Dolphin. This confirms the validity and optimal efficacy of the newly designed software (ICC 0.570-1.0). According to our results, the newly designed software has acceptable validity and reliability and can be used for orthodontic diagnosis, treatment planning and assessment of treatment outcome.

Protein-protein interaction analysis of Alzheimer`s disease and NAFLD based on systems biology methods unhide common ancestor pathways.

PubMed

Karbalaei, Reza; Allahyari, Marzieh; Rezaei-Tavirani, Mostafa; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza

2018-01-01

Analysis reconstruction networks from two diseases, NAFLD and Alzheimer`s diseases and their relationship based on systems biology methods. NAFLD and Alzheimer`s diseases are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on relation and same spreading pathways of these two diseases. In addition, they have some similar risk factors, exclusively lifestyle such as feeding, exercises and so on. Therefore, systems biology approach can help to discover their relationship. DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. An R package used to define best centrality method. Finally, based on degree and Betweenness, hubs and bottleneck nodes were defined. Common genes between NAFLD and Alzheimer`s disease were 190 genes that used construct a network with STRING database. The resulting network contained 182 nodes and 2591 edges and comprises from four clusters. Enrichment of these clusters separately lead to carbohydrate metabolism, long chain fatty acid and regulation of JAK-STAT and IL-17 signaling pathways, respectively. Also seven genes selected as hub-bottleneck include: IL6, AKT1, TP53, TNF, JUN, VEGFA and PPARG. Enrichment of these proteins and their first neighbors in network by OMIM database lead to diabetes and obesity as ancestors of NAFLD and AD. Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

TIde: a software for the systematic scanning of drug targets in kinetic network models

PubMed Central

Schulz, Marvin; Bakker, Barbara M; Klipp, Edda

2009-01-01

Background During the stages of the development of a potent drug candidate compounds can fail for several reasons. One of them, the efficacy of a candidate, can be estimated in silico if an appropriate ordinary differential equation model of the affected pathway is available. With such a model at hand it is also possible to detect reactions having a large effect on a certain variable such as a substance concentration. Results We show an algorithm that systematically tests the influence of activators and inhibitors of different type and strength acting at different positions in the network. The effect on a quantity to be selected (e.g. a steady state flux or concentration) is calculated. Moreover, combinations of two inhibitors or one inhibitor and one activator targeting different network positions are analysed. Furthermore, we present TIde (Target Identification), an open source, platform independent tool to investigate ordinary differential equation models in the common systems biology markup language format. It automatically assigns the respectively altered kinetics to the inhibited or activated reactions, performs the necessary calculations, and provides a graphical output of the analysis results. For illustration, TIde is used to detect optimal inhibitor positions in simple branched networks, a signalling pathway, and a well studied model of glycolysis in Trypanosoma brucei. Conclusion Using TIde, we show in the branched models under which conditions inhibitions in a certain pathway can affect a molecule concentrations in a different. In the signalling pathway we illuminate which inhibitions have an effect on the signalling characteristics of the last active kinase. Finally, we compare our set of best targets in the glycolysis model with a similar analysis showing the applicability of our tool. PMID:19840374

Plasma metabolomic study in Chinese patients with wet age-related macular degeneration.

PubMed

Luo, Dan; Deng, Tingting; Yuan, Wei; Deng, Hui; Jin, Ming

2017-09-06

Age-related macular degeneration (AMD) is a leading disease associated with blindness. It has a high incidence and complex pathogenesis. We aimed to study the metabolomic characteristics in Chinese patients with wet AMD by analyzing the morning plasma of 20 healthy controls and 20 wet AMD patients for metabolic differences. We used ultra-high-pressure liquid chromatography and quadrupole-time-of-flight mass spectrometry for this analysis. The relationship of these differences with AMD pathophysiology was also assessed. Remaining data were normalized using Pareto scaling, and then valid data were handled using multivariate data analysis with MetaboAnalysis software, including unsupervised principal component analysis and supervised partial least squares-discriminate analysis. The purpose of the present work was to identify significant metabolites for the analyses. Hierarchical clustering was conducted to identify metabolites that differed between the two groups. Significant metabolites were then identified using the established database, and features were mapped on the Kyoto Encyclopedia of Genes and Genomes. A total of 5443 ion peaks were detected, all of them attributable to the same 10 metabolites. These included some amino acids, isomaltose, hydrocortisone, and biliverdin. The heights of these peaks differed significantly between the two groups. The biosynthesis of amino acids pathways also differed profoundly between patients with wet AMD and controls. These findings suggested that metabolic profiles and and pathways differed between wet AMD and controls and may provide promising new targets for AMD-directed therapeutics and diagnostics.

Condor-COPASI: high-throughput computing for biochemical networks

PubMed Central

2012-01-01

Background Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. Results We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays. Conclusions Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage. PMID:22834945

Health information technology and implementation science: partners in progress in the VHA.

PubMed

Hynes, Denise M; Whittier, Erika R; Owens, Arika

2013-03-01

The Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has demonstrated how implementation science can enhance the quality of health care. During this time an increasing number of implementation research projects have developed or utilized health information technology (HIT) innovations to leverage the VA's electronic health record and information systems. To describe the HIT approaches used and to characterize the facilitators and barriers to progress within implementation research projects in the VA QUERI program. Nine case studies were selected from among 88 projects and represented 8 of 14 HIT categories identified. Each case study included key informants whose roles on the project were principal investigator, implementation science and informatics development. We conducted documentation analysis and semistructured in-person interviews with key informants for each of the 9 case studies. We used qualitative analysis software to identify and thematically code information and interview responses. : Thematic analyses revealed 3 domains or pathways critical to progression through the QUERI steps. These pathways addressed: (1) compliance and collaboration with information technology policies and procedures; (2) operating within organizational policies and building collaborations with end users, clinicians, and administrators; and (3) obtaining and maintaining research resources and approvals. Sustained efforts in HIT innovation and in implementation science in the Veterans Health Administration demonstrates the interdependencies of these initiatives and the critical pathways that can contribute to progress. Other health care quality improvement efforts that rely on HIT can learn from the Veterans Health Administration experience.

Identification of Key Pathways and Genes in L4 Dorsal Root Ganglion (DRG) After Sciatic Nerve Injury via Microarray Analysis.

PubMed

Zhao, He; Duan, Li-Jun; Sun, Qing-Ling; Gao, Yu-Shan; Yang, Yong-Dong; Tang, Xiang-Sheng; Zhao, Ding-Yan; Xiong, Yang; Hu, Zhen-Guo; Li, Chuan-Hong; Chen, Si-Xue; Liu, Tao; Yu, Xing

2018-04-19

Peripheral nerve injury (PNI) has devastating consequences. Dorsal root ganglion as a pivotal locus participates in the process of neuropathic pain and nerve regeneration. In recent years, gene sequencing technology has seen rapid rise in the biomedicine field. So, we attempt to gain insight into in the mechanism of neuropathic pain and nerve regeneration in the transcriptional level and to explore novel genes through bioinformatics analysis. The gene expression profiles of GSE96051 were downloaded from GEO database. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed by Cytoscape software. Our results showed that both IL-6 and Jun genes and the signaling pathway of MAPK, apoptosis, P53 present their vital modulatory role in nerve regeneration and neuropathic pain. Noteworthy, 13 hub genes associated with neuropathic pain and nerve regeneration, including Ccl12, Ppp1r15a, Cdkn1a, Atf3, Nts, Dusp1, Ccl7, Csf, Gadd45a, Serpine1, Timp1 were rarely reported in PubMed database, these genes may provide us the new orientation in experimental research and clinical study. Our results may provide more deep insight into the mechanism and a promising therapeutic target. The next step is to put our emphasis on an experiment level and to verify the novel genes from 13 hub genes.

A Research Roadmap for Computation-Based Human Reliability Analysis

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

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is oftenmore » secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.« less

RNA Seq analysis for transcriptome profiling in response to classical swine fever vaccination in indigenous and crossbred pigs.

PubMed

Pathak, Shalu Kumari; Kumar, Amit; Bhuwana, G; Sah, Vaishali; Upmanyu, Vikramadiya; Tiwari, A K; Sahoo, A P; Sahoo, A R; Wani, Sajjad A; Panigrahi, Manjit; Sahoo, N R; Kumar, Ravi

2017-09-01

In present investigation, differential expression of transcriptome after classical swine fever (CSF) vaccination has been explored at the cellular level in crossbred and indigenous (desi) piglets. RNA Sequencing by Expectation-Maximization (RSEM) package was used to quantify gene expression from RNA Sequencing data, and differentially expressed genes (DEGs) were identified using EBSeq, DESeq2, and edgeR softwares. After analysis, 5222, 6037, and 6210 common DEGs were identified in indigenous post-vaccinated verses pre-vaccinated, crossbred post-vaccinated verses pre-vaccinated, and post-vaccinated crossbred verses indigenous pigs, respectively. Functional annotation of these DEGs showed enrichment of antigen processing-cross presentation, B cell receptor signaling, T cell receptor signaling, NF-κB signaling, and TNF signaling pathways. The interaction network among the immune genes included more number of genes with greater connectivity in vaccinated crossbred than the indigenous piglets. Higher expression of IRF3, IL1β, TAP1, CSK, SLA2, SLADM, and NF-kB in crossbred piglets in comparison to indigenous explains the better humoral response observed in crossbred piglets. Here, we predicted that the processed CSFV antigen through the T cell receptor signaling cascade triggers the B cell receptor-signaling pathway to finally activate MAPK kinase and NF-κB signaling pathways in B cell. This activation results in expression of genes/transcription factors that lead to B cell ontogeny, auto immunity and immune response through antibody production. Further, immunologically important genes were validated by qRT-PCR.

Automated analysis of calcium spiking profiles with CaSA software: two case studies from root-microbe symbioses.

PubMed

Russo, Giulia; Spinella, Salvatore; Sciacca, Eva; Bonfante, Paola; Genre, Andrea

2013-12-26

Repeated oscillations in intracellular calcium (Ca2+) concentration, known as Ca2+ spiking signals, have been described in plants for a limited number of cellular responses to biotic or abiotic stimuli and most notably the common symbiotic signaling pathway (CSSP) which mediates the recognition by their plant hosts of two endosymbiotic microbes, arbuscular mycorrhizal (AM) fungi and nitrogen fixing rhizobia. The detailed analysis of the complexity and variability of the Ca2+ spiking patterns which have been revealed in recent studies requires both extensive datasets and sophisticated statistical tools. As a contribution, we have developed automated Ca2+ spiking analysis (CaSA) software that performs i) automated peak detection, ii) statistical analyses based on the detected peaks, iii) autocorrelation analysis of peak-to-peak intervals to highlight major traits in the spiking pattern.We have evaluated CaSA in two experimental studies. In the first, CaSA highlighted unpredicted differences in the spiking patterns induced in Medicago truncatula root epidermal cells by exudates of the AM fungus Gigaspora margarita as a function of the phosphate concentration in the growth medium of both host and fungus. In the second study we compared the spiking patterns triggered by either AM fungal or rhizobial symbiotic signals. CaSA revealed the existence of different patterns in signal periodicity, which are thought to contribute to the so-called Ca2+ signature. We therefore propose CaSA as a useful tool for characterizing oscillatory biological phenomena such as Ca2+ spiking.

OptFlux: an open-source software platform for in silico metabolic engineering.

PubMed

Rocha, Isabel; Maia, Paulo; Evangelista, Pedro; Vilaça, Paulo; Soares, Simão; Pinto, José P; Nielsen, Jens; Patil, Kiran R; Ferreira, Eugénio C; Rocha, Miguel

2010-04-19

Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community. Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.

OptFlux: an open-source software platform for in silico metabolic engineering

PubMed Central

2010-01-01

Background Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. Results OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. Conclusions The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community. Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models. PMID:20403172

Debugging and Performance Analysis Software Tools for Peregrine System |

Science.gov Websites

High-Performance Computing | NREL Debugging and Performance Analysis Software Tools for Peregrine System Debugging and Performance Analysis Software Tools for Peregrine System Learn about debugging and performance analysis software tools available to use with the Peregrine system. Allinea

Formal analysis of the surgical pathway and development of a new software tool to assist surgeons in the decision making in primary breast surgery.

PubMed

Catanuto, Giuseppe; Pappalardo, Francesco; Rocco, Nicola; Leotta, Marco; Ursino, Venera; Chiodini, Paolo; Buggi, Federico; Folli, Secondo; Catalano, Francesca; Nava, Maurizio B

2016-10-01

The increased complexity of the decisional process in breast cancer surgery is well documented. With this study we aimed to create a software tool able to assist patients and surgeons in taking proper decisions. We hypothesized that the endpoints of breast cancer surgery could be addressed combining a set of decisional drivers. We created a decision support system software tool (DSS) and an interactive decision tree. A formal analysis estimated the information gain derived from each feature in the process. We tested the DSS on 52 patients and we analyzed the concordance of decisions obtained by different users and between the DSS suggestions and the actual surgery. We also tested the ability of the system to prevent post breast conservation deformities. The information gain revealed that patients preferences are the root of our decision tree. An observed concordance respectively of 0.98 and 0.88 was reported when the DSS was used twice by an expert operator or by a newly trained operator vs. an expert one. The observed concordance between the DSS suggestion and the actual decision was 0.69. A significantly higher incidence of post breast conservation defects was reported among patients who did not follow the DSS decision (Type III of Fitoussi, N = 4; 33.3%, p = 0.004). The DSS decisions can be reproduced by operators with different experience. The concordance between suggestions and actual decision is quite low, however the DSS is able to prevent post- breast conservation deformities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Services for children with developmental co-ordination disorder: an evaluation against best practice principles.

PubMed

Pentland, Jacqueline; Maciver, Donald; Owen, Christine; Forsyth, Kirsty; Irvine, Linda; Walsh, Mike; Crowe, Miriam

2016-01-01

The National Health Service in Scotland published a best practice framework to support occupational therapists and physiotherapists to deliver effective services for children with developmental co-ordination disorder (DCD); however, adherence is variable. To highlight areas for development, this study compared the care pathway within a paediatric DCD service against the NHS Scotland framework. A partnership of researchers and clinicians based in the United Kingdom conducted a qualitative study with 37 participants (N = 13 interview participants, N = 24 workshop participants). In-depth interviews and/or workshops were used to map the DCD service against the NHS framework. Identified gaps were aligned with four key stages of the care pathway. Qualitative analysis software was used to analyse the data. Core principles to guide future development were identified for each phase of the pathway. These core principles related to the NHS framework and focused on issues such as involving the family, defining clear pathways and enhancing children's participation. Participants identified potential strategies for service improvement such as developing community-based interventions and information provision. Challenges when providing services for children with DCD include confusing service pathways and poor partnership working. It is, therefore, important that clinicians utilise collaborative working strategies that support children's participation. There are numerous challenges related to the implementation of best practice principles into the provision of therapy services for children with developmental coordination disorder (DCD). It is important that AHPs seek ways of engaging parents and educational professionals at all stages of the care pathway in order to ensure optimum service provision for the child. Addressing participation is an important aspect and community-based strategies may be particularly beneficial, both as a preventative activity and as an intervention approach.

‘N-of-1-pathways’ unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine

PubMed Central

Gardeux, Vincent; Achour, Ikbel; Li, Jianrong; Maienschein-Cline, Mark; Li, Haiquan; Pesce, Lorenzo; Parinandi, Gurunadh; Bahroos, Neil; Winn, Robert; Foster, Ian; Garcia, Joe G N; Lussier, Yves A

2014-01-01

Background The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery. Method ‘N-of-1-pathways’ is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient. Results Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03). Conclusions The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies. Software http://lussierlab.org/publications/N-of-1-pathways PMID:25301808

A program in global biology. [biota-environment interaction important to life

NASA Technical Reports Server (NTRS)

Mooneyhan, D. W.

1983-01-01

NASA's Global Biology Research Program and its goals for greater understanding of planetary biological processes are discussed. Consideration is given to assessing major pathways and rates of exchange of elements such as carbon and nitrogen, extrapolating local rates of anaerobic activities, determining exchange rates of ocean nutrients, and developing models for the global cycles of carbon, nitrogen, sulfur, and phosphorus. Satellites and sensors operating today are covered: the Nimbus, NOAA, and Landsat series. Block diagrams of the software and hardware for a typical ground data processing and analysis system are provided. Samples of the surface cover data achieved with the Advanced Very High Resolution Radiometer, the Multispectral Scanner, and the Thematic Mapper are presented, as well as a productive capacity model for coastal wetlands. Finally, attention is given to future goals, their engineering requirements, and the necessary data analysis system.

[Selection of reference genes of Siraitia grosvenorii by real-time PCR].

PubMed

Tu, Dong-ping; Mo, Chang-ming; Ma, Xiao-jun; Zhao, Huan; Tang, Qi; Huang, Jie; Pan, Li-mei; Wei, Rong-chang

2015-01-01

Siraitia grosvenorii is a traditional Chinese medicine also as edible food. This study selected six candidate reference genes by real-time quantitative PCR, the expression stability of the candidate reference genes in the different samples was analyzed by using the software and methods of geNorm, NormFinder, BestKeeper, Delta CT method and RefFinder, reference genes for S. grosvenorii were selected for the first time. The results showed that 18SrRNA expressed most stable in all samples, was the best reference gene in the genetic analysis. The study has a guiding role for the analysis of gene expression using qRT-PCR methods, providing a suitable reference genes to ensure the results in the study on differential expressed gene in synthesis and biological pathways, also other genes of S. grosvenorii.

Microarray evaluation of gene expression profiles in inflamed and healthy human dental pulp: the role of IL1beta and CD40 in pulp inflammation.

PubMed

Gatta, V; Zizzari, V L; Dd ' Amico, V; Salini, L; D' Aurora, M; Franchi, S; Antonucci, I; Sberna, M T; Gherlone, E; Stuppia, L; Tetè, S

2012-01-01

Dental pulp undergoes a number of changes passing from healthy status to inflammation due to deep decay. These changes are regulated by several genes resulting differently expressed in inflamed and healthy dental pulp, and the knowledge of the processes underlying this differential expression is of great relevance in the identification of the pathogenesis of the disease. In this study, the gene expression profile of inflamed and healthy dental pulps were compared by microarray analysis, and data obtained were analyzed by Ingenuity Pathway Analysis (IPA) software. This analysis allows to focus on a variety of genes, typically expressed in inflamed tissues. The comparison analysis showed an increased expression of several genes in inflamed pulp, among which IL1β and CD40 resulted of particular interest. These results indicate that gene expression profile of human dental pulp in different physiological and pathological conditions may become an useful tool for improving our knowledge about processes regulating pulp inflammation.

Emsoft User's Guide and Modeling Software (1997)

EPA Science Inventory

Chemicals that readily vaporize at relatively low temperatures can migrate from contaminated soils into the atmosphere via a process called volatilization. Volatilization represents a potentially significant exposure pathway because humans can come in contact with volatilized com...

Emsoft User's Guide and Modeling Software (2002 Update)

EPA Science Inventory

Chemicals that readily vaporize at relatively low temperatures can migrate from contaminated soils into the atmosphere via a process called volatilization. Volatilization represents a potentially significant exposure pathway because humans can come in contact with volatilized com...

Data analysis software for the autoradiographic enhancement process. Volumes 1, 2, and 3, and appendix

NASA Technical Reports Server (NTRS)

Singh, S. P.

1979-01-01

The computer software developed to set up a method for Wiener spectrum analysis of photographic films is presented. This method is used for the quantitative analysis of the autoradiographic enhancement process. The software requirements and design for the autoradiographic enhancement process are given along with the program listings and the users manual. A software description and program listings modification of the data analysis software are included.

CRISPR library designer (CLD): software for multispecies design of single guide RNA libraries.

PubMed

Heigwer, Florian; Zhan, Tianzuo; Breinig, Marco; Winter, Jan; Brügemann, Dirk; Leible, Svenja; Boutros, Michael

2016-03-24

Genetic screens using CRISPR/Cas9 are a powerful method for the functional analysis of genomes. Here we describe CRISPR library designer (CLD), an integrated bioinformatics application for the design of custom single guide RNA (sgRNA) libraries for all organisms with annotated genomes. CLD is suitable for the design of libraries using modified CRISPR enzymes and targeting non-coding regions. To demonstrate its utility, we perform a pooled screen for modulators of the TNF-related apoptosis inducing ligand (TRAIL) pathway using a custom library of 12,471 sgRNAs. CLD predicts a high fraction of functional sgRNAs and is publicly available at https://github.com/boutroslab/cld.

MicroRNA profiling reveals dysregulated microRNAs and their target gene regulatory networks in cemento-ossifying fibroma.

PubMed

Pereira, Thaís Dos Santos Fontes; Brito, João Artur Ricieri; Guimarães, André Luiz Sena; Gomes, Carolina Cavaliéri; de Lacerda, Júlio Cesar Tanos; de Castro, Wagner Henriques; Coimbra, Roney Santos; Diniz, Marina Gonçalves; Gomez, Ricardo Santiago

2018-01-01

Cemento-ossifying fibroma (COF) is a benign fibro-osseous neoplasm of uncertain pathogenesis, and its treatment results in morbidity. MicroRNAs (miRNA) are small non-coding RNAs that regulate gene expression and may represent therapeutic targets. The purpose of the study was to generate a comprehensive miRNA profile of COF compared to normal bone. Additionally, the most relevant pathways and target genes of differentially expressed miRNA were investigated by in silico analysis. Nine COF and ten normal bone samples were included in the study. miRNA profiling was carried out by using TaqMan® OpenArray® Human microRNA panel containing 754 validated human miRNAs. We identified the most relevant miRNAs target genes through the leader gene approach, using STRING and Cytoscape software. Pathways enrichment analysis was performed using DIANA-miRPath. Eleven miRNAs were downregulated (hsa-miR-95-3p, hsa-miR-141-3p, hsa-miR-205-5p, hsa-miR-223-3p, hsa-miR-31-5p, hsa-miR-944, hsa-miR-200b-3p, hsa-miR-135b-5p, hsa-miR-31-3p, hsa-miR-223-5p and hsa-miR-200c-3p), and five were upregulated (hsa-miR-181a-5p, hsa-miR-181c-5p, hsa-miR-149-5p, hsa-miR-138-5p and hsa-miR-199a-3p) in COF compared to normal bone. Eighteen common target genes were predicted, and the leader genes approach identified the following genes involved in human COF: EZH2, XIAP, MET and TGFBR1. According to the biology of bone and COF, the most relevant KEGG pathways revealed by enrichment analysis were proteoglycans in cancer, miRNAs in cancer, pathways in cancer, p53-, PI3K-Akt-, FoxO- and TGF-beta signalling pathways, which were previously found to be differentially regulated in bone neoplasms, odontogenic tumours and osteogenesis. miRNA dysregulation occurs in COF, and EZH2, XIAP, MET and TGFBR1 are potential targets for functional analysis validation. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Construction and completion of flux balance models from pathway databases.

PubMed

Latendresse, Mario; Krummenacker, Markus; Trupp, Miles; Karp, Peter D

2012-02-01

Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand. We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens. Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml. mario.latendresse@sri.com Supplementary data are available at Bioinformatics online.

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

KEGGtranslator: visualizing and converting the KEGG PATHWAY database to various formats.

PubMed

Wrzodek, Clemens; Dräger, Andreas; Zell, Andreas

2011-08-15

The KEGG PATHWAY database provides a widely used service for metabolic and nonmetabolic pathways. It contains manually drawn pathway maps with information about the genes, reactions and relations contained therein. To store these pathways, KEGG uses KGML, a proprietary XML-format. Parsers and translators are needed to process the pathway maps for usage in other applications and algorithms. We have developed KEGGtranslator, an easy-to-use stand-alone application that can visualize and convert KGML formatted XML-files into multiple output formats. Unlike other translators, KEGGtranslator supports a plethora of output formats, is able to augment the information in translated documents (e.g. MIRIAM annotations) beyond the scope of the KGML document, and amends missing components to fragmentary reactions within the pathway to allow simulations on those. KEGGtranslator is freely available as a Java(™) Web Start application and for download at http://www.cogsys.cs.uni-tuebingen.de/software/KEGGtranslator/. KGML files can be downloaded from within the application. clemens.wrzodek@uni-tuebingen.de Supplementary data are available at Bioinformatics online.

TOOTHPASTEV6.11.3

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

Sankel, David J.; Clair, Aaron B. St.; Langsfield, Joshua D.

2006-11-01

Toothpaste is a graphical user interface and Computer Aided Drafting/Manufacturing (CAD/CAM) software package used to plan tool paths for Galil Motion Control hardware. The software is a tool for computer controlled dispensing of materials. The software may be used for solid freeform fabrication of components or the precision printing of inks. Mathematical calculations are used to produce a set of segments and arcs that when coupled together will fill space. The paths of the segments and arcs are then translated into a machine language that controls the motion of motors and translational stages to produce tool paths in three dimensions.more » As motion begins material(s) are dispensed or printed along the three-dimensional pathway.« less

Infusing Reliability Techniques into Software Safety Analysis

NASA Technical Reports Server (NTRS)

Shi, Ying

2015-01-01

Software safety analysis for a large software intensive system is always a challenge. Software safety practitioners need to ensure that software related hazards are completely identified, controlled, and tracked. This paper discusses in detail how to incorporate the traditional reliability techniques into the entire software safety analysis process. In addition, this paper addresses how information can be effectively shared between the various practitioners involved in the software safety analyses. The author has successfully applied the approach to several aerospace applications. Examples are provided to illustrate the key steps of the proposed approach.

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

The SCEC Community Modeling Environment(SCEC/CME): A Collaboratory for Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Jordan, T. H.; Minster, J. B.; Moore, R.; Kesselman, C.

2005-12-01

The SCEC Community Modeling Environment (SCEC/CME) Project is an NSF-supported Geosciences/IT partnership that is actively developing an advanced information infrastructure for system-level earthquake science in Southern California. This partnership includes SCEC, USC's Information Sciences Institute (ISI), the San Diego Supercomputer Center (SDSC), the Incorporated Institutions for Research in Seismology (IRIS), and the U.S. Geological Survey. The goal of the SCEC/CME is to develop seismological applications and information technology (IT) infrastructure to support the development of Seismic Hazard Analysis (SHA) programs and other geophysical simulations. The SHA application programs developed on the Project include a Probabilistic Seismic Hazard Analysis system called OpenSHA. OpenSHA computational elements that are currently available include a collection of attenuation relationships, and several Earthquake Rupture Forecasts (ERFs). Geophysicists in the collaboration have also developed Anelastic Wave Models (AWMs) using both finite-difference and finite-element approaches. Earthquake simulations using these codes have been run for a variety of earthquake sources. Rupture Dynamic Model (RDM) codes have also been developed that simulate friction-based fault slip. The SCEC/CME collaboration has also developed IT software and hardware infrastructure to support the development, execution, and analysis of these SHA programs. To support computationally expensive simulations, we have constructed a grid-based scientific workflow system. Using the SCEC grid, project collaborators can submit computations from the SCEC/CME servers to High Performance Computers at USC and TeraGrid High Performance Computing Centers. Data generated and archived by the SCEC/CME is stored in a digital library system, the Storage Resource Broker (SRB). This system provides a robust and secure system for maintaining the association between the data seta and their metadata. To provide an easy-to-use system for constructing SHA computations, a browser-based workflow assembly web portal has been developed. Users can compose complex SHA calculations, specifying SCEC/CME data sets as inputs to calculations, and calling SCEC/CME computational programs to process the data and the output. Knowledge-based software tools have been implemented that utilize ontological descriptions of SHA software and data can validate workflows created with this pathway assembly tool. Data visualization software developed by the collaboration supports analysis and validation of data sets. Several programs have been developed to visualize SCEC/CME data including GMT-based map making software for PSHA codes, 4D wavefield propagation visualization software based on OpenGL, and 3D Geowall-based visualization of earthquakes, faults, and seismic wave propagation. The SCEC/CME Project also helps to sponsor the SCEC UseIT Intern program. The UseIT Intern Program provides research opportunities in both Geosciences and Information Technology to undergraduate students in a variety of fields. The UseIT group has developed a 3D data visualization tool, called SCEC-VDO, as a part of this undergraduate research program.

Inflammatory response in rat lungs with recurrent exposure to welding fumes: a transcriptomic approach.

PubMed

Oh, Jung-Hwa; Yang, Mi-Jin; Heo, Jeong-Doo; Yang, Young-Su; Park, Han-Jin; Park, Se-Myo; Kwon, Myung-Sang; Song, Chang-Woo; Yoon, Seokjoo; Yu, Il Je

2012-04-01

As chronic exposure to welding fumes causes pulmonary diseases, such as pneumoconiosis, public concern has increased regarding continued exposure to these hazardous gases in the workplace. In a previous study, the inflammatory response to welding fume exposure was analysed in rat lungs in the case of recurrent exposure and recovery periods. Thus using lung samples, well-annotated by histological observation and biochemical analysis, this study examines the gene expression profiles to identify phenotype-anchored genes corresponding to lung inflammation and the repair phenomenon after recurrent welding fume exposure. Seven genes (Mmp12, Cd5l, LOC50101, LOC69183, Spp1, and Slc26a4) were found to be significantly up-regulated according to the severity of the lung injury. In addition, the transcription and translation of Trem2, which was up-regulated in response to the repair process, were validated using a real-time polymerase chain reaction, Western blotting, and immunohistochemistry. The differentially expressed genes in the exposure and recovery groups were also classified using k-means and hierarchical clustering, plus their toxicological function and canonical pathways were further analysed using Ingenuity Pathways Analysis Software. As a result, this comprehensive and integrative analysis of the transcriptional changes that occur during repeated exposure provides important information on the inflammation and repair processes after welding-fume-induced lung injury.

Genetic Analysis of Mice Skin Exposed by Hyper-Gravity

NASA Astrophysics Data System (ADS)

Takahashi, Rika; Terada, Masahiro; Seki, Masaya; Higashibata, Akira; Majima, Hideyuki J.; Ohira, Yoshinobu; Mukai, Chiaki; Ishioka, Noriaki

2013-02-01

In the space environment, physiological alterations, such as low bone density, muscle weakness and decreased immunity, are caused by microgravity and cosmic radiation. On the other hand, it is known that the leg muscles are hypertrophy by 2G-gravity. An understanding of the effects on human body from microgravity to hyper-gravity is very important. Recently, the Japan Aerospace Exploration Agency (JAXA) has started a project to detect the changes on gene expression and mineral metabolism caused by microgravity by analyzing the hair of astronauts who stay in the international Space Station (ISS) for a long time. From these results of human hair’s research, the genetic effects of human hair roots by microgravity will become clear. However, it is unclear how the gene expression of hair roots was effected by hypergravity. Therefore, in this experiment, we analyzed the effect on mice skin contained hair roots by comparing microgravity or hypergravity exposed mice. The purpose of this experiment is to evaluate the genetic effects on mice skin by microgravity or 2G-gravity. The samples were taken from mice exposed to space flight (FL) or hypergravity environment (2G) for 3-months, respectively. The extracted and amplified RNA from these mice skin was used to DNA microarray analysis. in this experiment, we analyzed the effect of gravity by using mice skin contained hair roots, which exposed space (FL) and hyper-gravity (2G) for 3 months and each control. By DNA microarray analysis, we found the common 98 genes changed in both FL and 2G. Among these 98 genes, the functions and pathways were identified by Gene Ontology (GO) analysis and Ingenuity Pathways Analysis (IPA) software. Next, we focused the one of the identified pathways and compared the effects on each molecules in this pathways by the different environments, such as FL and 2G. As the results, we could detect some interesting molecules, which might be depended on the gravity levels. In addition, to investigate the relationships between genes and protein expression, the proteome analysis was performed. From the result of 2-dimentional electrophoresis, we could detect the some different spots between FL and 2G. These identifications are now in progress using by MALDI-TOF-MS/MS. These results suggested that many genes or proteins on the mice skin might be effected by the different gravity levels.

Transcriptomic Analysis of Metabolic Pathways in Milkfish That Respond to Salinity and Temperature Changes.

PubMed

Hu, Yau-Chung; Kang, Chao-Kai; Tang, Cheng-Hao; Lee, Tsung-Han

2015-01-01

Milkfish (Chanos chanos), an important marine aquaculture species in southern Taiwan, show considerable euryhalinity but have low tolerance to sudden drops in water temperatures in winter. Here, we used high throughput next-generation sequencing (NGS) to identify molecular and biological processes involved in the responses to environmental changes. Preliminary tests revealed that seawater (SW)-acclimated milkfish tolerated lower temperatures than the fresh water (FW)-acclimated group. Although FW- and SW-acclimated milkfish have different levels of tolerance for hypothermal stress, to date, the molecular physiological basis of this difference has not been elucidated. Here, we performed a next-generation sequence analysis of mRNAs from four groups of milkfish. We obtained 29669 unigenes with an average length of approximately 1936 base pairs. Gene ontology (GO) analysis was performed after gene annotation. A large number of genes for molecular regulation were identified through a transcriptomic comparison in a KEGG analysis. Basal metabolic pathways involved in hypothermal tolerance, such as glycolysis, fatty acid metabolism, amino acid catabolism and oxidative phosphorylation, were analyzed using PathVisio and Cytoscape software. Our results indicate that in response to hypothermal stress, genes for oxidative phosphorylation, e.g., succinate dehydrogenase, were more highly up-regulated in SW than FW fish. Moreover, SW and FW milkfish used different strategies when exposed to hypothermal stress: SW milkfish up-regulated oxidative phosphorylation and catabolism genes to produce more energy budget, whereas FW milkfish down-regulated genes related to basal metabolism to reduce energy loss.

Transcriptomic Analysis of Metabolic Pathways in Milkfish That Respond to Salinity and Temperature Changes

PubMed Central

Hu, Yau-Chung; Kang, Chao-Kai; Tang, Cheng-Hao; Lee, Tsung-Han

2015-01-01

Milkfish (Chanos chanos), an important marine aquaculture species in southern Taiwan, show considerable euryhalinity but have low tolerance to sudden drops in water temperatures in winter. Here, we used high throughput next-generation sequencing (NGS) to identify molecular and biological processes involved in the responses to environmental changes. Preliminary tests revealed that seawater (SW)-acclimated milkfish tolerated lower temperatures than the fresh water (FW)-acclimated group. Although FW- and SW-acclimated milkfish have different levels of tolerance for hypothermal stress, to date, the molecular physiological basis of this difference has not been elucidated. Here, we performed a next-generation sequence analysis of mRNAs from four groups of milkfish. We obtained 29669 unigenes with an average length of approximately 1936 base pairs. Gene ontology (GO) analysis was performed after gene annotation. A large number of genes for molecular regulation were identified through a transcriptomic comparison in a KEGG analysis. Basal metabolic pathways involved in hypothermal tolerance, such as glycolysis, fatty acid metabolism, amino acid catabolism and oxidative phosphorylation, were analyzed using PathVisio and Cytoscape software. Our results indicate that in response to hypothermal stress, genes for oxidative phosphorylation, e.g., succinate dehydrogenase, were more highly up-regulated in SW than FW fish. Moreover, SW and FW milkfish used different strategies when exposed to hypothermal stress: SW milkfish up-regulated oxidative phosphorylation and catabolism genes to produce more energy budget, whereas FW milkfish down-regulated genes related to basal metabolism to reduce energy loss. PMID:26263550

Identification of potential transcriptomic markers in developing pediatric sepsis: a weighted gene co-expression network analysis and a case-control validation study.

PubMed

Li, Yiping; Li, Yanhong; Bai, Zhenjiang; Pan, Jian; Wang, Jian; Fang, Fang

2017-12-13

Sepsis represents a complex disease with the dysregulated inflammatory response and high mortality rate. The goal of this study was to identify potential transcriptomic markers in developing pediatric sepsis by a co-expression module analysis of the transcriptomic dataset. Using the R software and Bioconductor packages, we performed a weighted gene co-expression network analysis to identify co-expression modules significantly associated with pediatric sepsis. Functional interpretation (gene ontology and pathway analysis) and enrichment analysis with known transcription factors and microRNAs of the identified candidate modules were then performed. In modules significantly associated with sepsis, the intramodular analysis was further performed and "hub genes" were identified and validated by quantitative real-time PCR (qPCR) in this study. 15 co-expression modules in total were detected, and four modules ("midnight blue", "cyan", "brown", and "tan") were most significantly associated with pediatric sepsis and suggested as potential sepsis-associated modules. Gene ontology analysis and pathway analysis revealed that these four modules strongly associated with immune response. Three of the four sepsis-associated modules were also enriched with known transcription factors (false discovery rate-adjusted P < 0.05). Hub genes were identified in each of the four modules. Four of the identified hub genes (MYB proto-oncogene like 1, killer cell lectin like receptor G1, stomatin, and membrane spanning 4-domains A4A) were further validated to be differentially expressed between septic children and controls by qPCR. Four pediatric sepsis-associated co-expression modules were identified in this study. qPCR results suggest that hub genes in these modules are potential transcriptomic markers for pediatric sepsis diagnosis. These results provide novel insights into the pathogenesis of pediatric sepsis and promote the generation of diagnostic gene sets.

A method for generating new datasets based on copy number for cancer analysis.

PubMed

Kim, Shinuk; Kon, Mark; Kang, Hyunsik

2015-01-01

New data sources for the analysis of cancer data are rapidly supplementing the large number of gene-expression markers used for current methods of analysis. Significant among these new sources are copy number variation (CNV) datasets, which typically enumerate several hundred thousand CNVs distributed throughout the genome. Several useful algorithms allow systems-level analyses of such datasets. However, these rich data sources have not yet been analyzed as deeply as gene-expression data. To address this issue, the extensive toolsets used for analyzing expression data in cancerous and noncancerous tissue (e.g., gene set enrichment analysis and phenotype prediction) could be redirected to extract a great deal of predictive information from CNV data, in particular those derived from cancers. Here we present a software package capable of preprocessing standard Agilent copy number datasets into a form to which essentially all expression analysis tools can be applied. We illustrate the use of this toolset in predicting the survival time of patients with ovarian cancer or glioblastoma multiforme and also provide an analysis of gene- and pathway-level deletions in these two types of cancer.

Inertial Upper Stage (IUS) software analysis

NASA Technical Reports Server (NTRS)

Grayson, W. L.; Nickel, C. E.; Rose, P. L.; Singh, R. P.

1979-01-01

The Inertial Upper Stage (IUS) System, an extension of the Space Transportation System (STS) operating regime to include higher orbits, orbital plane changes, geosynchronous orbits, and interplanetary trajectories is presented. The IUS software design, the IUS software interfaces with other systems, and the cost effectiveness in software verification are described. Tasks of the IUS discussed include: (1) design analysis; (2) validation requirements analysis; (3) interface analysis; and (4) requirements analysis.

PATHWAYS - ELECTRON TUNNELING PATHWAYS IN PROTEINS

NASA Technical Reports Server (NTRS)

Beratan, D. N.

1994-01-01

The key to understanding the mechanisms of many important biological processes such as photosynthesis and respiration is a better understanding of the electron transfer processes which take place between metal atoms (and other groups) fixed within large protein molecules. Research is currently focused on the rate of electron transfer and the factors that influence it, such as protein composition and the distance between metal atoms. Current models explain the swift transfer of electrons over considerable distances by postulating bridge-mediated tunneling, or physical tunneling pathways, made up of interacting bonds in the medium around and between donor and acceptor sites. The program PATHWAYS is designed to predict the route along which electrons travel in the transfer processes. The basic strategy of PATHWAYS is to begin by recording each possible path element on a connectivity list, including in each entry which two atoms are connected and what contribution the connection would make to the overall rate if it were included in a pathway. The list begins with the bonded molecular structure (including the backbone sequence and side chain connectivity), and then adds probable hydrogen bond links and through-space contacts. Once this list is completed, the program runs a tree search from the donor to the acceptor site to find the dominant pathways. The speed and efficiency of the computer search offers an improvement over manual techniques. PATHWAYS is written in FORTRAN 77 for execution on DEC VAX series computers running VMS. The program inputs data from four data sets and one structure file. The software was written to input BIOGRAF (old format) structure files based on x-ray crystal structures and outputs ASCII files listing the best pathways and BIOGRAF vector files containing the paths. Relatively minor changes could be made in the input format statements for compatibility with other graphics software. The executable and source code are included with the distribution. The main memory requirement for execution is 2.6 Mb. This program is available in DEC VAX BACKUP format on a 9-track 1600 BPI magnetic tape (standard distribution) or on a TK50 tape cartridge. PATHWAYS was developed in 1988. PATHWAYS is a copyrighted work with all copyright vested in NASA. DEC, VAX, VMS, and TK50 are trademarks of Digital Equipment Corporation. BIOGRAF is a trademark of Molecular Simulations, Inc., Sunnyvale, CA.

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Software Safety Progress in NASA

NASA Technical Reports Server (NTRS)

Radley, Charles F.

1995-01-01

NASA has developed guidelines for development and analysis of safety-critical software. These guidelines have been documented in a Guidebook for Safety Critical Software Development and Analysis. The guidelines represent a practical 'how to' approach, to assist software developers and safety analysts in cost effective methods for software safety. They provide guidance in the implementation of the recent NASA Software Safety Standard NSS-1740.13 which was released as 'Interim' version in June 1994, scheduled for formal adoption late 1995. This paper is a survey of the methods in general use, resulting in the NASA guidelines for safety critical software development and analysis.

Power calculation for overall hypothesis testing with high-dimensional commensurate outcomes.

PubMed

Chi, Yueh-Yun; Gribbin, Matthew J; Johnson, Jacqueline L; Muller, Keith E

2014-02-28

The complexity of system biology means that any metabolic, genetic, or proteomic pathway typically includes so many components (e.g., molecules) that statistical methods specialized for overall testing of high-dimensional and commensurate outcomes are required. While many overall tests have been proposed, very few have power and sample size methods. We develop accurate power and sample size methods and software to facilitate study planning for high-dimensional pathway analysis. With an account of any complex correlation structure between high-dimensional outcomes, the new methods allow power calculation even when the sample size is less than the number of variables. We derive the exact (finite-sample) and approximate non-null distributions of the 'univariate' approach to repeated measures test statistic, as well as power-equivalent scenarios useful to generalize our numerical evaluations. Extensive simulations of group comparisons support the accuracy of the approximations even when the ratio of number of variables to sample size is large. We derive a minimum set of constants and parameters sufficient and practical for power calculation. Using the new methods and specifying the minimum set to determine power for a study of metabolic consequences of vitamin B6 deficiency helps illustrate the practical value of the new results. Free software implementing the power and sample size methods applies to a wide range of designs, including one group pre-intervention and post-intervention comparisons, multiple parallel group comparisons with one-way or factorial designs, and the adjustment and evaluation of covariate effects. Copyright © 2013 John Wiley & Sons, Ltd.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

PubMed Central

Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

2012-01-01

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

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

Fucosterol activates the insulin signaling pathway in insulin resistant HepG2 cells via inhibiting PTP1B.

PubMed

Jung, Hyun Ah; Bhakta, Himanshu Kumar; Min, Byung-Sun; Choi, Jae Sue

2016-10-01

Insulin resistance is a characteristic feature of type 2 diabetes mellitus (T2DM) and is characterized by defects in insulin signaling. This study investigated the modulatory effects of fucosterol on the insulin signaling pathway in insulin-resistant HepG2 cells by inhibiting protein tyrosine phosphatase 1B (PTP1B). In addition, molecular docking simulation studies were performed to predict binding energies, the specific binding site of fucosterol to PTP1B, and to identify interacting residues using Autodock 4.2 software. Glucose uptake was determined using a fluorescent D-glucose analogue and the glucose tracer 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) amino]-2-deoxyglucose, and the signaling pathway was detected by Western blot analysis. We found that fucosterol enhanced insulin-provoked glucose uptake and conjointly decreased PTP1B expression level in insulin-resistant HepG2 cells. Moreover, fucosterol significantly reduced insulin-stimulated serine (Ser307) phosphorylation of insulin receptor substrate 1 (IRS1) and increased phosphorylation of Akt, phosphatidylinositol-3-kinase, and extracellular signal- regulated kinase 1 at concentrations of 12.5, 25, and 50 µM in insulin-resistant HepG2 cells. Fucosterol inhibited caspase-3 activation and nuclear factor kappa B in insulin-resistant hepatocytes. These results suggest that fucosterol stimulates glucose uptake and improves insulin resistance by downregulating expression of PTP1B and activating the insulin signaling pathway. Thus, fucosterol has potential for development as an anti-diabetic agent.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses

PubMed Central

Serbus, Laura R.; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A. J. M. Zehadee; Christensen, Steen

2017-01-01

The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. PMID:28455417

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

The PluriNetWork: An Electronic Representation of the Network Underlying Pluripotency in Mouse, and Its Applications

PubMed Central

Greber, Boris; Siatkowski, Marcin; Paudel, Yogesh; Warsow, Gregor; Cap, Clemens; Schöler, Hans; Fuellen, Georg

2010-01-01

Background Analysis of the mechanisms underlying pluripotency and reprogramming would benefit substantially from easy access to an electronic network of genes, proteins and mechanisms. Moreover, interpreting gene expression data needs to move beyond just the identification of the up-/downregulation of key genes and of overrepresented processes and pathways, towards clarifying the essential effects of the experiment in molecular terms. Methodology/Principal Findings We have assembled a network of 574 molecular interactions, stimulations and inhibitions, based on a collection of research data from 177 publications until June 2010, involving 274 mouse genes/proteins, all in a standard electronic format, enabling analyses by readily available software such as Cytoscape and its plugins. The network includes the core circuit of Oct4 (Pou5f1), Sox2 and Nanog, its periphery (such as Stat3, Klf4, Esrrb, and c-Myc), connections to upstream signaling pathways (such as Activin, WNT, FGF, BMP, Insulin, Notch and LIF), and epigenetic regulators as well as some other relevant genes/proteins, such as proteins involved in nuclear import/export. We describe the general properties of the network, as well as a Gene Ontology analysis of the genes included. We use several expression data sets to condense the network to a set of network links that are affected in the course of an experiment, yielding hypotheses about the underlying mechanisms. Conclusions/Significance We have initiated an electronic data repository that will be useful to understand pluripotency and to facilitate the interpretation of high-throughput data. To keep up with the growth of knowledge on the fundamental processes of pluripotency and reprogramming, we suggest to combine Wiki and social networking software towards a community curation system that is easy to use and flexible, and tailored to provide a benefit for the scientist, and to improve communication and exchange of research results. A PluriNetWork tutorial is available at http://www.ibima.med.uni-rostock.de/IBIMA/PluriNetWork/. PMID:21179244

Protein Expression Profile of Twenty-Week-Old Diabetic db/db and Non-Diabetic Mice Livers: A Proteomic and Bioinformatic Analysis.

PubMed

Guzmán-Flores, Juan Manuel; Flores-Pérez, Elsa Cristina; Hernández-Ortiz, Magdalena; Vargas-Ortiz, Katya; Ramírez-Emiliano, Joel; Encarnación-Guevara, Sergio; Pérez-Vázquez, Victoriano

2018-06-01

Type 2 diabetes mellitus is characterized by insulin resistance in the liver. Insulin is not only involved in carbohydrate metabolism, it also regulates protein synthesis. This work describes the expression of proteins in the liver of a diabetic mouse and identifies the metabolic pathways involved. Twenty-week-old diabetic db/db mice were hepatectomized, after which proteins were separated by 2D-Polyacrylamide Gel Electrophoresis (2D-PAGE). Spots varying in intensity were analyzed using mass spectrometry, and biological function was assigned by the Database for Annotation, Visualization and Integrated Discovery (DAVID) software. A differential expression of 26 proteins was identified; among these were arginase-1, pyruvate carboxylase, peroxiredoxin-1, regucalcin, and sorbitol dehydrogenase. Bioinformatics analysis indicated that many of these proteins are mitochondrial and participate in metabolic pathways, such as the citrate cycle, the fructose and mannose metabolism, and glycolysis or gluconeogenesis. In addition, these proteins are related to oxidation⁻reduction reactions and molecular function of vitamin binding and amino acid metabolism. In conclusion, the proteomic profile of the liver of diabetic mouse db/db exhibited mainly alterations in the metabolism of carbohydrates and nitrogen. These differences illustrate the heterogeneity of diabetes in its different stages and under different conditions and highlights the need to improve treatments for this disease.

Using software security analysis to verify the secure socket layer (SSL) protocol

NASA Technical Reports Server (NTRS)

Powell, John D.

2004-01-01

nal Aeronautics and Space Administration (NASA) have tens of thousands of networked computer systems and applications. Software Security vulnerabilities present risks such as lost or corrupted data, information the3, and unavailability of critical systems. These risks represent potentially enormous costs to NASA. The NASA Code Q research initiative 'Reducing Software Security Risk (RSSR) Trough an Integrated Approach '' offers, among its capabilities, formal verification of software security properties, through the use of model based verification (MBV) to address software security risks. [1,2,3,4,5,6] MBV is a formal approach to software assurance that combines analysis of software, via abstract models, with technology, such as model checkers, that provide automation of the mechanical portions of the analysis process. This paper will discuss: The need for formal analysis to assure software systems with respect to software and why testing alone cannot provide it. The means by which MBV with a Flexible Modeling Framework (FMF) accomplishes the necessary analysis task. An example of FMF style MBV in the verification of properties over the Secure Socket Layer (SSL) communication protocol as a demonstration.

Development of Automated Image Analysis Software for Suspended Marine Particle Classification

DTIC Science & Technology

2003-09-30

Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...REPORT TYPE 3. DATES COVERED 00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE Development of Automated Image Analysis Software for Suspended...objective is to develop automated image analysis software to reduce the effort and time required for manual identification of plankton images. Automated

A tool to include gamma analysis software into a quality assurance program.

PubMed

Agnew, Christina E; McGarry, Conor K

2016-03-01

To provide a tool to enable gamma analysis software algorithms to be included in a quality assurance (QA) program. Four image sets were created comprising two geometric images to independently test the distance to agreement (DTA) and dose difference (DD) elements of the gamma algorithm, a clinical step and shoot IMRT field and a clinical VMAT arc. The images were analysed using global and local gamma analysis with 2 in-house and 8 commercially available software encompassing 15 software versions. The effect of image resolution on gamma pass rates was also investigated. All but one software accurately calculated the gamma passing rate for the geometric images. Variation in global gamma passing rates of 1% at 3%/3mm and over 2% at 1%/1mm was measured between software and software versions with analysis of appropriately sampled images. This study provides a suite of test images and the gamma pass rates achieved for a selection of commercially available software. This image suite will enable validation of gamma analysis software within a QA program and provide a frame of reference by which to compare results reported in the literature from various manufacturers and software versions. Copyright © 2015. Published by Elsevier Ireland Ltd.

The Role of Data Analysis Software in Graduate Programs in Education and Post-Graduate Research

ERIC Educational Resources Information Center

Harwell, Michael

2018-01-01

The importance of data analysis software in graduate programs in education and post-graduate educational research is self-evident. However the role of this software in facilitating supererogated statistical practice versus "cookbookery" is unclear. The need to rigorously document the role of data analysis software in students' graduate…

Identification of disease specific pathways using in vivo SILAC proteomics in dystrophin deficient mdx mouse.

PubMed

Rayavarapu, Sree; Coley, William; Cakir, Erdinc; Jahnke, Vanessa; Takeda, Shin'ichi; Aoki, Yoshitsugu; Grodish-Dressman, Heather; Jaiswal, Jyoti K; Hoffman, Eric P; Brown, Kristy J; Hathout, Yetrib; Nagaraju, Kanneboyina

2013-05-01

Duchenne muscular dystrophy (DMD) is an X-linked neuromuscular disorder caused by a mutation in the dystrophin gene. DMD is characterized by progressive weakness of skeletal, cardiac, and respiratory muscles. The molecular mechanisms underlying dystrophy-associated muscle weakness and damage are not well understood. Quantitative proteomics techniques could help to identify disease-specific pathways. Recent advances in the in vivo labeling strategies such as stable isotope labeling in mouse (SILAC mouse) with (13)C6-lysine or stable isotope labeling in mammals (SILAM) with (15)N have enabled accurate quantitative analysis of the proteomes of whole organs and tissues as a function of disease. Here we describe the use of the SILAC mouse strategy to define the underlying pathological mechanisms in dystrophin-deficient skeletal muscle. Differential SILAC proteome profiling was performed on the gastrocnemius muscles of 3-week-old (early stage) dystrophin-deficient mdx mice and wild-type (normal) mice. The generated data were further confirmed in an independent set of mdx and normal mice using a SILAC spike-in strategy. A total of 789 proteins were quantified; of these, 73 were found to be significantly altered between mdx and normal mice (p < 0.05). Bioinformatics analyses using Ingenuity Pathway software established that the integrin-linked kinase pathway, actin cytoskeleton signaling, mitochondrial energy metabolism, and calcium homeostasis are the pathways initially affected in dystrophin-deficient muscle at early stages of pathogenesis. The key proteins involved in these pathways were validated by means of immunoblotting and immunohistochemistry in independent sets of mdx mice and in human DMD muscle biopsies. The specific involvement of these molecular networks early in dystrophic pathology makes them potential therapeutic targets. In sum, our findings indicate that SILAC mouse strategy has uncovered previously unidentified pathological pathways in mouse models of human skeletal muscle disease.

Identification of Disease Specific Pathways Using in Vivo SILAC Proteomics in Dystrophin Deficient mdx Mouse*

PubMed Central

Rayavarapu, Sree; Coley, William; Cakir, Erdinc; Jahnke, Vanessa; Takeda, Shin'ichi; Aoki, Yoshitsugu; Grodish-Dressman, Heather; Jaiswal, Jyoti K.; Hoffman, Eric P.; Brown, Kristy J.; Hathout, Yetrib; Nagaraju, Kanneboyina

2013-01-01

Duchenne muscular dystrophy (DMD) is an X-linked neuromuscular disorder caused by a mutation in the dystrophin gene. DMD is characterized by progressive weakness of skeletal, cardiac, and respiratory muscles. The molecular mechanisms underlying dystrophy-associated muscle weakness and damage are not well understood. Quantitative proteomics techniques could help to identify disease-specific pathways. Recent advances in the in vivo labeling strategies such as stable isotope labeling in mouse (SILAC mouse) with 13C6-lysine or stable isotope labeling in mammals (SILAM) with 15N have enabled accurate quantitative analysis of the proteomes of whole organs and tissues as a function of disease. Here we describe the use of the SILAC mouse strategy to define the underlying pathological mechanisms in dystrophin-deficient skeletal muscle. Differential SILAC proteome profiling was performed on the gastrocnemius muscles of 3-week-old (early stage) dystrophin-deficient mdx mice and wild-type (normal) mice. The generated data were further confirmed in an independent set of mdx and normal mice using a SILAC spike-in strategy. A total of 789 proteins were quantified; of these, 73 were found to be significantly altered between mdx and normal mice (p < 0.05). Bioinformatics analyses using Ingenuity Pathway software established that the integrin-linked kinase pathway, actin cytoskeleton signaling, mitochondrial energy metabolism, and calcium homeostasis are the pathways initially affected in dystrophin-deficient muscle at early stages of pathogenesis. The key proteins involved in these pathways were validated by means of immunoblotting and immunohistochemistry in independent sets of mdx mice and in human DMD muscle biopsies. The specific involvement of these molecular networks early in dystrophic pathology makes them potential therapeutic targets. In sum, our findings indicate that SILAC mouse strategy has uncovered previously unidentified pathological pathways in mouse models of human skeletal muscle disease. PMID:23297347

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

Computational annotation of genes differentially expressed along olive fruit development

PubMed Central

Galla, Giulio; Barcaccia, Gianni; Ramina, Angelo; Collani, Silvio; Alagna, Fiammetta; Baldoni, Luciana; Cultrera, Nicolò GM; Martinelli, Federico; Sebastiani, Luca; Tonutti, Pietro

2009-01-01

Background Olea europaea L. is a traditional tree crop of the Mediterranean basin with a worldwide economical high impact. Differently from other fruit tree species, little is known about the physiological and molecular basis of the olive fruit development and a few sequences of genes and gene products are available for olive in public databases. This study deals with the identification of large sets of differentially expressed genes in developing olive fruits and the subsequent computational annotation by means of different software. Results mRNA from fruits of the cv. Leccino sampled at three different stages [i.e., initial fruit set (stage 1), completed pit hardening (stage 2) and veraison (stage 3)] was used for the identification of differentially expressed genes putatively involved in main processes along fruit development. Four subtractive hybridization libraries were constructed: forward and reverse between stage 1 and 2 (libraries A and B), and 2 and 3 (libraries C and D). All sequenced clones (1,132 in total) were analyzed through BlastX against non-redundant NCBI databases and about 60% of them showed similarity to known proteins. A total of 89 out of 642 differentially expressed unique sequences was further investigated by Real-Time PCR, showing a validation of the SSH results as high as 69%. Library-specific cDNA repertories were annotated according to the three main vocabularies of the gene ontology (GO): cellular component, biological process and molecular function. BlastX analysis, GO terms mapping and annotation analysis were performed using the Blast2GO software, a research tool designed with the main purpose of enabling GO based data mining on sequence sets for which no GO annotation is yet available. Bioinformatic analysis pointed out a significantly different distribution of the annotated sequences for each GO category, when comparing the three fruit developmental stages. The olive fruit-specific transcriptome dataset was used to query all known KEGG (Kyoto Encyclopaedia of Genes and Genomes) metabolic pathways for characterizing and positioning retrieved EST records. The integration of the olive sequence datasets within the MapMan platform for microarray analysis allowed the identification of specific biosynthetic pathways useful for the definition of key functional categories in time course analyses for gene groups. Conclusion The bioinformatic annotation of all gene sequences was useful to shed light on metabolic pathways and transcriptional aspects related to carbohydrates, fatty acids, secondary metabolites, transcription factors and hormones as well as response to biotic and abiotic stresses throughout olive drupe development. These results represent a first step toward both functional genomics and systems biology research for understanding the gene functions and regulatory networks in olive fruit growth and ripening. PMID:19852839

Usability study of clinical exome analysis software: top lessons learned and recommendations.

PubMed

Shyr, Casper; Kushniruk, Andre; Wasserman, Wyeth W

2014-10-01

New DNA sequencing technologies have revolutionized the search for genetic disruptions. Targeted sequencing of all protein coding regions of the genome, called exome analysis, is actively used in research-oriented genetics clinics, with the transition to exomes as a standard procedure underway. This transition is challenging; identification of potentially causal mutation(s) amongst ∼10(6) variants requires specialized computation in combination with expert assessment. This study analyzes the usability of user interfaces for clinical exome analysis software. There are two study objectives: (1) To ascertain the key features of successful user interfaces for clinical exome analysis software based on the perspective of expert clinical geneticists, (2) To assess user-system interactions in order to reveal strengths and weaknesses of existing software, inform future design, and accelerate the clinical uptake of exome analysis. Surveys, interviews, and cognitive task analysis were performed for the assessment of two next-generation exome sequence analysis software packages. The subjects included ten clinical geneticists who interacted with the software packages using the "think aloud" method. Subjects' interactions with the software were recorded in their clinical office within an urban research and teaching hospital. All major user interface events (from the user interactions with the packages) were time-stamped and annotated with coding categories to identify usability issues in order to characterize desired features and deficiencies in the user experience. We detected 193 usability issues, the majority of which concern interface layout and navigation, and the resolution of reports. Our study highlights gaps in specific software features typical within exome analysis. The clinicians perform best when the flow of the system is structured into well-defined yet customizable layers for incorporation within the clinical workflow. The results highlight opportunities to dramatically accelerate clinician analysis and interpretation of patient genomic data. We present the first application of usability methods to evaluate software interfaces in the context of exome analysis. Our results highlight how the study of user responses can lead to identification of usability issues and challenges and reveal software reengineering opportunities for improving clinical next-generation sequencing analysis. While the evaluation focused on two distinctive software tools, the results are general and should inform active and future software development for genome analysis software. As large-scale genome analysis becomes increasingly common in healthcare, it is critical that efficient and effective software interfaces are provided to accelerate clinical adoption of the technology. Implications for improved design of such applications are discussed. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Identification of novel mutations in endometrial cancer patients by whole-exome sequencing.

PubMed

Chang, Ya-Sian; Huang, Hsien-Da; Yeh, Kun-Tu; Chang, Jan-Gowth

2017-05-01

The aim of the present study was to identify genomic alterations in Taiwanese endometrial cancer patients. This information is vitally important in Taiwan, where endometrial cancer is the second most common gynecological cancer. We performed whole-exome sequencing on DNA from 14 tumor tissue samples from Taiwanese endometrial cancer patients. We used the Genome Analysis Tool kit software package for data analysis, and the dbSNP, Catalogue of Somatic Mutations in Cancer (COSMIC) and The Cancer Genome Atlas (TCGA) databases for comparisons. Variants were validated via Sanger sequencing. We identified 143 non-synonymous mutations in 756 canonical cancer-related genes and 1,271 non-synonymous mutations in non-canonical cancer-related genes in 14 endometrial samples. PTEN, KRAS and PIK3R1 were the most frequently mutated canonical cancer-related genes. Our results revealed nine potential driver genes (MAPT, IL24, MCM6, TSC1, BIRC2, CIITA, DST, CASP8 and NOTCH2) and 21 potential passenger genes (ARMCX4, IGSF10, VPS13C, DCT, DNAH14, TLN1, ZNF605, ZSCAN29, MOCOS, CMYA5, PCDH17, UGT1A8, CYFIP2, MACF1, NUDT5, JAKMIP1, PCDHGB4, FAM178A, SNX6, IMP4 and PCMTD1). The detected molecular aberrations led to putative activation of the mTOR, Wnt, MAPK, VEGF and ErbB pathways, as well as aberrant DNA repair, cell cycle control and apoptosis pathways. We characterized the mutational landscape and genetic alterations in multiple cellular pathways of endometrial cancer in the Taiwanese population.

Combining biophysical methods for the analysis of protein complex stoichiometry and affinity in SEDPHAT

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

Zhao, Huaying, E-mail: zhaoh3@mail.nih.gov; Schuck, Peter, E-mail: zhaoh3@mail.nih.gov

2015-01-01

Global multi-method analysis for protein interactions (GMMA) can increase the precision and complexity of binding studies for the determination of the stoichiometry, affinity and cooperativity of multi-site interactions. The principles and recent developments of biophysical solution methods implemented for GMMA in the software SEDPHAT are reviewed, their complementarity in GMMA is described and a new GMMA simulation tool set in SEDPHAT is presented. Reversible macromolecular interactions are ubiquitous in signal transduction pathways, often forming dynamic multi-protein complexes with three or more components. Multivalent binding and cooperativity in these complexes are often key motifs of their biological mechanisms. Traditional solution biophysicalmore » techniques for characterizing the binding and cooperativity are very limited in the number of states that can be resolved. A global multi-method analysis (GMMA) approach has recently been introduced that can leverage the strengths and the different observables of different techniques to improve the accuracy of the resulting binding parameters and to facilitate the study of multi-component systems and multi-site interactions. Here, GMMA is described in the software SEDPHAT for the analysis of data from isothermal titration calorimetry, surface plasmon resonance or other biosensing, analytical ultracentrifugation, fluorescence anisotropy and various other spectroscopic and thermodynamic techniques. The basic principles of these techniques are reviewed and recent advances in view of their particular strengths in the context of GMMA are described. Furthermore, a new feature in SEDPHAT is introduced for the simulation of multi-method data. In combination with specific statistical tools for GMMA in SEDPHAT, simulations can be a valuable step in the experimental design.« less

Automated analysis of calcium spiking profiles with CaSA software: two case studies from root-microbe symbioses

PubMed Central

2013-01-01

Background Repeated oscillations in intracellular calcium (Ca2+) concentration, known as Ca2+ spiking signals, have been described in plants for a limited number of cellular responses to biotic or abiotic stimuli and most notably the common symbiotic signaling pathway (CSSP) which mediates the recognition by their plant hosts of two endosymbiotic microbes, arbuscular mycorrhizal (AM) fungi and nitrogen fixing rhizobia. The detailed analysis of the complexity and variability of the Ca2+ spiking patterns which have been revealed in recent studies requires both extensive datasets and sophisticated statistical tools. Results As a contribution, we have developed automated Ca2+ spiking analysis (CaSA) software that performs i) automated peak detection, ii) statistical analyses based on the detected peaks, iii) autocorrelation analysis of peak-to-peak intervals to highlight major traits in the spiking pattern. We have evaluated CaSA in two experimental studies. In the first, CaSA highlighted unpredicted differences in the spiking patterns induced in Medicago truncatula root epidermal cells by exudates of the AM fungus Gigaspora margarita as a function of the phosphate concentration in the growth medium of both host and fungus. In the second study we compared the spiking patterns triggered by either AM fungal or rhizobial symbiotic signals. CaSA revealed the existence of different patterns in signal periodicity, which are thought to contribute to the so-called Ca2+ signature. Conclusions We therefore propose CaSA as a useful tool for characterizing oscillatory biological phenomena such as Ca2+ spiking. PMID:24369773

Fault Tree Analysis Application for Safety and Reliability

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

Many commercial software tools exist for fault tree analysis (FTA), an accepted method for mitigating risk in systems. The method embedded in the tools identifies a root as use in system components, but when software is identified as a root cause, it does not build trees into the software component. No commercial software tools have been built specifically for development and analysis of software fault trees. Research indicates that the methods of FTA could be applied to software, but the method is not practical without automated tool support. With appropriate automated tool support, software fault tree analysis (SFTA) may be a practical technique for identifying the underlying cause of software faults that may lead to critical system failures. We strive to demonstrate that existing commercial tools for FTA can be adapted for use with SFTA, and that applied to a safety-critical system, SFTA can be used to identify serious potential problems long before integrator and system testing.

RELAP-7 Software Verification and Validation Plan

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

Smith, Curtis L.; Choi, Yong-Joon; Zou, Ling

This INL plan comprehensively describes the software for RELAP-7 and documents the software, interface, and software design requirements for the application. The plan also describes the testing-based software verification and validation (SV&V) process—a set of specially designed software models used to test RELAP-7. The RELAP-7 (Reactor Excursion and Leak Analysis Program) code is a nuclear reactor system safety analysis code being developed at Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework – MOOSE (Multi-Physics Object-Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty yearsmore » of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s capability and extends the analysis capability for all reactor system simulation scenarios.« less

Handwriting analysis indicates spontaneous dyskinesias in neuroleptic naïve adolescents at high risk for psychosis.

PubMed

Dean, Derek J; Teulings, Hans-Leo; Caligiuri, Michael; Mittal, Vijay A

2013-11-21

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of impaired neuromodulation of dopamine in fronto-striatal pathways. The traditional methods for identifying movement abnormalities include observer-based reports and force stability gauges. The drawbacks of these methods are long training times for raters, experimenter bias, large site differences in instrumental apparatus, and suboptimal reliability. Taking these drawbacks into account has guided the development of better standardized and more efficient procedures to examine movement abnormalities through handwriting analysis software and tablet. Individuals at risk for psychosis showed significantly more dysfluent pen movements (a proximal measure for dyskinesia) in a handwriting task. Handwriting kinematics offers a great advance over previous methods of assessing dyskinesia, which could clearly be beneficial for understanding the etiology of psychosis.

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Naïve Adolescents at High Risk for Psychosis

PubMed Central

Dean, Derek J.; Teulings, Hans-Leo; Caligiuri, Michael; Mittal, Vijay A.

2013-01-01

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of impaired neuromodulation of dopamine in fronto-striatal pathways. The traditional methods for identifying movement abnormalities include observer-based reports and force stability gauges. The drawbacks of these methods are long training times for raters, experimenter bias, large site differences in instrumental apparatus, and suboptimal reliability. Taking these drawbacks into account has guided the development of better standardized and more efficient procedures to examine movement abnormalities through handwriting analysis software and tablet. Individuals at risk for psychosis showed significantly more dysfluent pen movements (a proximal measure for dyskinesia) in a handwriting task. Handwriting kinematics offers a great advance over previous methods of assessing dyskinesia, which could clearly be beneficial for understanding the etiology of psychosis. PMID:24300590

Transcriptome analysis and related databases of Lactococcus lactis.

PubMed

Kuipers, Oscar P; de Jong, Anne; Baerends, Richard J S; van Hijum, Sacha A F T; Zomer, Aldert L; Karsens, Harma A; den Hengst, Chris D; Kramer, Naomi E; Buist, Girbe; Kok, Jan

2002-08-01

Several complete genome sequences of Lactococcus lactis and their annotations will become available in the near future, next to the already published genome sequence of L. lactis ssp. lactis IL 1403. This will allow intraspecies comparative genomics studies as well as functional genomics studies aimed at a better understanding of physiological processes and regulatory networks operating in lactococci. This paper describes the initial set-up of a DNA-microarray facility in our group, to enable transcriptome analysis of various Gram-positive bacteria, including a ssp. lactis and a ssp. cremoris strain of Lactococcus lactis. Moreover a global description will be given of the hardware and software requirements for such a set-up, highlighting the crucial integration of relevant bioinformatics tools and methods. This includes the development of MolGenIS, an information system for transcriptome data storage and retrieval, and LactococCye, a metabolic pathway/genome database of Lactococcus lactis.

Ruminal Transcriptomic Analysis of Grass-Fed and Grain-Fed Angus Beef Cattle

PubMed Central

Li, Yaokun; Carrillo, José A.; Ding, Yi; He, YangHua; Zhao, Chunping; Zan, Linsen; Song, Jiuzhou

2015-01-01

Beef represents a major diet component and one of the major sources of protein in human. The beef industry in the United States is currently undergoing changes and is facing increased demands especially for natural grass-fed beef. The grass-fed beef obtained their nutrients directly from pastures, which contained limited assimilable energy but abundant amount of fiber. On the contrary, the grain-fed steers received a grain-based regime that served as an efficient source of high-digestible energy. Lately, ruminant animals have been accused to be a substantial contributor for the green house effect. Therefore, the concerns from environmentalism, animal welfare and public health have driven consumers to choose grass-fed beef. Rumen is one of the key workshops to digest forage constituting a critical step to supply enough nutrients for animals’ growth and production. We hypothesize that rumen may function differently in grass- and grain-fed regimes. The objective of this study was to find the differentially expressed genes in the ruminal wall of grass-fed and grain-fed steers, and then explore the potential biopathways. In this study, the RNA Sequencing (RNA-Seq) method was used to measure the gene expression level in the ruminal wall. The total number of reads per sample ranged from 24,697,373 to 36,714,704. The analysis detected 342 differentially expressed genes between ruminal wall samples of animals raised under different regimens. The Fisher’s exact test performed in the Ingenuity Pathway Analysis (IPA) software found 16 significant molecular networks. Additionally, 13 significantly enriched pathways were identified, most of which were related to cell development and biosynthesis. Our analysis demonstrated that most of the pathways enriched with the differentially expressed genes were related to cell development and biosynthesis. Our results provided valuable insights into the molecular mechanisms resulting in the phenotype difference between grass-fed and grain-fed cattle. PMID:26090810

Proceedings of the 14th Annual Software Engineering Workshop

NASA Technical Reports Server (NTRS)

1989-01-01

Several software related topics are presented. Topics covered include studies and experiment at the Software Engineering Laboratory at the Goddard Space Flight Center, predicting project success from the Software Project Management Process, software environments, testing in a reuse environment, domain directed reuse, and classification tree analysis using the Amadeus measurement and empirical analysis.

Design and validation of Segment--freely available software for cardiovascular image analysis.

PubMed

Heiberg, Einar; Sjögren, Jane; Ugander, Martin; Carlsson, Marcus; Engblom, Henrik; Arheden, Håkan

2010-01-11

Commercially available software for cardiovascular image analysis often has limited functionality and frequently lacks the careful validation that is required for clinical studies. We have already implemented a cardiovascular image analysis software package and released it as freeware for the research community. However, it was distributed as a stand-alone application and other researchers could not extend it by writing their own custom image analysis algorithms. We believe that the work required to make a clinically applicable prototype can be reduced by making the software extensible, so that researchers can develop their own modules or improvements. Such an initiative might then serve as a bridge between image analysis research and cardiovascular research. The aim of this article is therefore to present the design and validation of a cardiovascular image analysis software package (Segment) and to announce its release in a source code format. Segment can be used for image analysis in magnetic resonance imaging (MRI), computed tomography (CT), single photon emission computed tomography (SPECT) and positron emission tomography (PET). Some of its main features include loading of DICOM images from all major scanner vendors, simultaneous display of multiple image stacks and plane intersections, automated segmentation of the left ventricle, quantification of MRI flow, tools for manual and general object segmentation, quantitative regional wall motion analysis, myocardial viability analysis and image fusion tools. Here we present an overview of the validation results and validation procedures for the functionality of the software. We describe a technique to ensure continued accuracy and validity of the software by implementing and using a test script that tests the functionality of the software and validates the output. The software has been made freely available for research purposes in a source code format on the project home page http://segment.heiberg.se. Segment is a well-validated comprehensive software package for cardiovascular image analysis. It is freely available for research purposes provided that relevant original research publications related to the software are cited.

User-driven integrated software lives: ``Paleomag'' paleomagnetics analysis on the Macintosh

NASA Astrophysics Data System (ADS)

Jones, Craig H.

2002-12-01

"PaleoMag," a paleomagnetics analysis package originally developed for the Macintosh operating system in 1988, allows examination of demagnetization of individual samples and analysis of directional data from collections of samples. Prior to recent reinvigorated development of the software for both Macintosh and Windows, it was widely used despite not running properly on machines and operating systems sold after 1995. This somewhat surprising situation demonstrates that there is a continued need for integrated analysis software within the earth sciences, in addition to well-developed scripting and batch-mode software. One distinct advantage of software like PaleoMag is in the ability to combine quality control with analysis within a unique graphical environment. Because such demands are frequent within the earth sciences, means of nurturing the development of similar software should be found.

A digital model individual template and CT-guided 125I seed implants for malignant tumors of the head and neck.

PubMed

Huang, Ming-Wei; Liu, Shu-Ming; Zheng, Lei; Shi, Yan; Zhang, Jie; Li, Yan-Sheng; Yu, Guang-Yan; Zhang, Jian-Guo

2012-11-01

To enhance the accuracy of radioactive seed implants in the head and neck, a digital model individual template, containing information simultaneously on needle pathway and facial features, was designed to guide implantation with CT imaging. Thirty-one patients with recurrent and local advanced malignant tumors of head and neck after prior surgery and radiotherapy were involved in this study. Before (125)I implants, patients received CT scans based on 0.75mm thickness. And the brachytherapy treatment planning system (BTPS) software was used to make the implantation plan based on the CT images. Mimics software and Geomagic software were used to read the data containing CT images and implantation plan, and to design the individual template. Then the individual template containing the information of needle pathway and face features simultaneously was made through rapid prototyping (RP) technique. All patients received (125)I seeds interstitial implantation under the guide of the individual template and CT. The individual templates were positioned easily and accurately, and were stable. After implants, treatment quality evaluation was made by CT and TPS. The seeds and dosages distribution (D(90),V(100),V(150)) were well meet the treatment requirement. Clinical practice confirms that this approach can facilitate easier and more accurate implantation.

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.

Alterations in mRNA profiles of trastuzumab‑resistant Her‑2‑positive breast cancer.

PubMed

Zhao, Bin; Zhao, Yang; Sun, Yan; Niu, Haitao; Sheng, Long; Huang, Dongfang; Li, Li

2018-05-07

Breast cancer is one of the most common malignancies in women. Neoadjuvant trastuzumab therapy improves the prognosis of certain Her‑2‑positive breast cancer patients, however around two‑thirds of patients with Her‑2‑positive breast cancer do not benefit from Her‑2‑targeted therapy. To investigate the key mechanisms in trastuzumab resistance, potential biomarkers for neoadjuvant trastuzumab sensitivity were investigated using the gene expression omnibus (GEO) database for mRNA microarray data of Her‑2‑positive breast cancer patients who received neoadjuvant trastuzumab therapy. GEO profiles of 22 patients with a complete response and 48 patients with a partial response were identified in the GSE22358, GSE62327 and GSE66305 datasets. A total of 2,376, 1,000 and 1,152 differentially expressed genes in GSE22358, GSE62327 and GSE66305 datasets were demonstrated, respectively, utilizing GEO2R software. Furthermore, enriched gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways were analyzed using the Database for Annotation, Visualization and Integrated Discovery software. Subsequently, a protein‑protein interaction network was established using STRING software. The results demonstrated that low sex‑determining region Y‑box 11 and high Bcl‑2 expression may be employed as markers for neoadjuvant trastuzumab therapy for Her‑2‑positive breast cancer. More importantly, phosphoinositide 3‑kinase/Akt and angiogenesis pathways, which are known to be the key targets of trastuzumab, were activated at a lower level in the partial response patients, while the Wnt and estrogen receptor signaling pathways were activated in these patients. Therefore, combination therapy of trastuzumab and anti‑Wnt or hormone therapy may be a promising treatment modality and should be tested in further studies.

Examining the architecture of cellular computing through a comparative study with a computer

PubMed Central

Wang, Degeng; Gribskov, Michael

2005-01-01

The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software–hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's ‘hardware’ equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the ‘bandwidth’ of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed. PMID:16849179

Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis

PubMed Central

Ţălu, Ştefan; Călugăru, Dan Mihai; Lupaşcu, Carmen Alina

2015-01-01

AIM To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method. METHODS This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal (24 images) and pathological (148 images) states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software ImageJ. Statistical analyses were performed for these groups using Microsoft Office Excel 2003 and GraphPad InStat software. RESULTS It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy (DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR (NPDR) images (segmented and skeletonized versions). The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images (segmented and skeletonized versions). The lowest values were found for the corresponding values of severe NPDR images (segmented and skeletonized versions). CONCLUSION The fractal analysis of fundus photographs may be used for a more complete undeTrstanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension. Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from healthy individuals. PMID:26309878

Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis.

PubMed

Ţălu, Ştefan; Călugăru, Dan Mihai; Lupaşcu, Carmen Alina

2015-01-01

To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method. This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal (24 images) and pathological (148 images) states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software ImageJ. Statistical analyses were performed for these groups using Microsoft Office Excel 2003 and GraphPad InStat software. It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy (DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR (NPDR) images (segmented and skeletonized versions). The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images (segmented and skeletonized versions). The lowest values were found for the corresponding values of severe NPDR images (segmented and skeletonized versions). The fractal analysis of fundus photographs may be used for a more complete undeTrstanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension. Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from healthy individuals.

Oscillation of Angiogenesis and Vascular Dropout in Progressive Human Vascular Disease. [Vascular Pattern as Useful Read-Out of Complex Molecular Signaling

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia

2010-01-01

When analyzed by VESsel GENeration Analysis (VESGEN) software, vascular patterns provide useful integrative read-outs of complex, interacting molecular signaling pathways. Using VESGEN, we recently discovered and published our innovative, surprising findings that angiogenesis oscillated with vascular dropout throughout progression of diabetic retinopathy, a blinding vascular disease. Our findings provide a potential paradigm shift in the current prevailing view on progression and treatment of this disease, and a new early-stage window of regenerative therapeutic opportunities. The findings also suggest that angiogenesis may oscillate with vascular disease in a homeostatic-like manner during early stages of other inflammatory progressive diseases such as cancer and coronary vascular disease.

Genome-wide genetic analyses highlight mitogen-activated protein kinase (MAPK) signaling in the pathogenesis of endometriosis.

PubMed

Uimari, Outi; Rahmioglu, Nilufer; Nyholt, Dale R; Vincent, Katy; Missmer, Stacey A; Becker, Christian; Morris, Andrew P; Montgomery, Grant W; Zondervan, Krina T

2017-04-01

Do genome-wide association study (GWAS) data for endometriosis provide insight into novel biological pathways associated with its pathogenesis? GWAS analysis uncovered multiple pathways that are statistically enriched for genetic association signals, analysis of Stage A disease highlighted a novel variant in MAP3K4, while top pathways significantly associated with all endometriosis and Stage A disease included several mitogen-activated protein kinase (MAPK)-related pathways. Endometriosis is a complex disease with an estimated heritability of 50%. To date, GWAS revealed 10 genomic regions associated with endometriosis, explaining <4% of heritability, while half of the heritability is estimated to be due to common risk variants. Pathway analyses combine the evidence of single variants into gene-based measures, leveraging the aggregate effect of variants in genes and uncovering biological pathways involved in disease pathogenesis. Pathway analysis was conducted utilizing the International Endogene Consortium GWAS data, comprising 3194 surgically confirmed endometriosis cases and 7060 controls of European ancestry with genotype data imputed up to 1000 Genomes Phase three reference panel. GWAS was performed for all endometriosis cases and for Stage A (revised American Fertility Society (rAFS) I/II, n = 1686) and B (rAFS III/IV, n = 1364) cases separately. The identified significant pathways were compared with pathways previously investigated in the literature through candidate association studies. The most comprehensive biological pathway databases, MSigDB (including BioCarta, KEGG, PID, SA, SIG, ST and GO) and PANTHER were utilized to test for enrichment of genetic variants associated with endometriosis. Statistical enrichment analysis was performed using the MAGENTA (Meta-Analysis Gene-set Enrichment of variaNT Associations) software. The first genome-wide association analysis for Stage A endometriosis revealed a novel locus, rs144240142 (P = 6.45 × 10-8, OR = 1.71, 95% CI = 1.23-2.37), an intronic single-nucleotide polymorphism (SNP) within MAP3K4. This SNP was not associated with Stage B disease (P = 0.086). MAP3K4 was also shown to be differentially expressed in eutopic endometrium between Stage A endometriosis cases and controls (P = 3.8 × 10-4), but not with Stage B disease (P = 0.26). A total of 14 pathways enriched with genetic endometriosis associations were identified (false discovery rate (FDR)-P < 0.05). The pathways associated with any endometriosis were Grb2-Sos provides linkage to MAPK signaling for integrins pathway (P = 2.8 × 10-5, FDR-P = 3.0 × 10-3), Wnt signaling (P = 0.026, FDR-P = 0.026) and p130Cas linkage to MAPK signaling for integrins pathway (P = 6.0 × 10-4, FDR-P = 0.029); with Stage A endometriosis: extracellular signal-regulated kinase (ERK)1 ERK2 MAPK (P = 5.0 × 10-4, FDR-P = 5.0 × 10-4) and with Stage B endometriosis: two overlapping pathways that related to extracellular matrix biology-Core matrisome (P = 1.4 × 10-3, FDR-P = 0.013) and ECM glycoproteins (P = 1.8 × 10-3, FDR-P = 7.1 × 10-3). Genes arising from endometriosis candidate gene studies performed to date were enriched for Interleukin signaling pathway (P = 2.3 × 10-12), Apoptosis signaling pathway (P = 9.7 × 10-9) and Gonadotropin releasing hormone receptor pathway (P = 1.2 × 10-6); however, these pathways did not feature in the results based on GWAS data. Not applicable. The analysis is restricted to (i) variants in/near genes that can be assigned to pathways, excluding intergenic variants; (ii) the gene-based pathway definition as registered in the databases; (iii) women of European ancestry. The top ranked pathways associated with overall and Stage A endometriosis in particular involve integrin-mediated MAPK activation and intracellular ERK/MAPK acting downstream in the MAPK cascade, both acting in the control of cell division, gene expression, cell movement and survival. Other top enriched pathways in Stage B disease include ECM glycoprotein pathways important for extracellular structure and biochemical support. The results highlight the need for increased efforts to understand the functional role of these pathways in endometriosis pathogenesis, including the investigation of the biological effects of the genetic variants on downstream molecular processes in tissue relevant to endometriosis. Additionally, our results offer further support for the hypothesis of at least partially distinct causal pathophysiology for minimal/mild (rAFS I/II) vs. moderate/severe (rAFS III/IV) endometriosis. The genome-wide association data and Wellcome Trust Case Control Consortium (WTCCC) were generated through funding from the Wellcome Trust (WT084766/Z/08/Z, 076113 and 085475) and the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485 and 552498). N.R. was funded by a grant from the Medical Research Council UK (MR/K011480/1). A.P.M. is a Wellcome Trust Senior Fellow in Basic Biomedical Science (grant WT098017). All authors declare there are no conflicts of interest. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

Genome-wide genetic analyses highlight mitogen-activated protein kinase (MAPK) signaling in the pathogenesis of endometriosis

PubMed Central

Uimari, Outi; Rahmioglu, Nilufer; Nyholt, Dale R.; Vincent, Katy; Missmer, Stacey A.; Becker, Christian; Morris, Andrew P.; Montgomery, Grant W.

2017-01-01

Abstract STUDY QUESTION Do genome-wide association study (GWAS) data for endometriosis provide insight into novel biological pathways associated with its pathogenesis? SUMMARY ANSWER GWAS analysis uncovered multiple pathways that are statistically enriched for genetic association signals, analysis of Stage A disease highlighted a novel variant in MAP3K4, while top pathways significantly associated with all endometriosis and Stage A disease included several mitogen-activated protein kinase (MAPK)-related pathways. WHAT IS KNOWN ALREADY Endometriosis is a complex disease with an estimated heritability of 50%. To date, GWAS revealed 10 genomic regions associated with endometriosis, explaining <4% of heritability, while half of the heritability is estimated to be due to common risk variants. Pathway analyses combine the evidence of single variants into gene-based measures, leveraging the aggregate effect of variants in genes and uncovering biological pathways involved in disease pathogenesis. STUDY DESIGN, SIZE, DURATION Pathway analysis was conducted utilizing the International Endogene Consortium GWAS data, comprising 3194 surgically confirmed endometriosis cases and 7060 controls of European ancestry with genotype data imputed up to 1000 Genomes Phase three reference panel. GWAS was performed for all endometriosis cases and for Stage A (revised American Fertility Society (rAFS) I/II, n = 1686) and B (rAFS III/IV, n = 1364) cases separately. The identified significant pathways were compared with pathways previously investigated in the literature through candidate association studies. PARTICIPANTS/MATERIALS, SETTING, METHODS The most comprehensive biological pathway databases, MSigDB (including BioCarta, KEGG, PID, SA, SIG, ST and GO) and PANTHER were utilized to test for enrichment of genetic variants associated with endometriosis. Statistical enrichment analysis was performed using the MAGENTA (Meta-Analysis Gene-set Enrichment of variaNT Associations) software. MAIN RESULTS AND THE ROLE OF CHANCE The first genome-wide association analysis for Stage A endometriosis revealed a novel locus, rs144240142 (P = 6.45 × 10−8, OR = 1.71, 95% CI = 1.23–2.37), an intronic single-nucleotide polymorphism (SNP) within MAP3K4. This SNP was not associated with Stage B disease (P = 0.086). MAP3K4 was also shown to be differentially expressed in eutopic endometrium between Stage A endometriosis cases and controls (P = 3.8 × 10−4), but not with Stage B disease (P = 0.26). A total of 14 pathways enriched with genetic endometriosis associations were identified (false discovery rate (FDR)-P < 0.05). The pathways associated with any endometriosis were Grb2-Sos provides linkage to MAPK signaling for integrins pathway (P = 2.8 × 10−5, FDR-P = 3.0 × 10−3), Wnt signaling (P = 0.026, FDR-P = 0.026) and p130Cas linkage to MAPK signaling for integrins pathway (P = 6.0 × 10−4, FDR-P = 0.029); with Stage A endometriosis: extracellular signal-regulated kinase (ERK)1 ERK2 MAPK (P = 5.0 × 10−4, FDR-P = 5.0 × 10−4) and with Stage B endometriosis: two overlapping pathways that related to extracellular matrix biology—Core matrisome (P = 1.4 × 10−3, FDR-P = 0.013) and ECM glycoproteins (P = 1.8 × 10−3, FDR-P = 7.1 × 10−3). Genes arising from endometriosis candidate gene studies performed to date were enriched for Interleukin signaling pathway (P = 2.3 × 10−12), Apoptosis signaling pathway (P = 9.7 × 10−9) and Gonadotropin releasing hormone receptor pathway (P = 1.2 × 10−6); however, these pathways did not feature in the results based on GWAS data. LARGE SCALE DATA Not applicable. LIMITATIONS, REASONS FOR CAUTION The analysis is restricted to (i) variants in/near genes that can be assigned to pathways, excluding intergenic variants; (ii) the gene-based pathway definition as registered in the databases; (iii) women of European ancestry. WIDER IMPLICATIONS OF THE FINDINGS The top ranked pathways associated with overall and Stage A endometriosis in particular involve integrin-mediated MAPK activation and intracellular ERK/MAPK acting downstream in the MAPK cascade, both acting in the control of cell division, gene expression, cell movement and survival. Other top enriched pathways in Stage B disease include ECM glycoprotein pathways important for extracellular structure and biochemical support. The results highlight the need for increased efforts to understand the functional role of these pathways in endometriosis pathogenesis, including the investigation of the biological effects of the genetic variants on downstream molecular processes in tissue relevant to endometriosis. Additionally, our results offer further support for the hypothesis of at least partially distinct causal pathophysiology for minimal/mild (rAFS I/II) vs. moderate/severe (rAFS III/IV) endometriosis. STUDY FUNDING/COMPETING INTEREST(S) The genome-wide association data and Wellcome Trust Case Control Consortium (WTCCC) were generated through funding from the Wellcome Trust (WT084766/Z/08/Z, 076113 and 085475) and the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485 and 552498). N.R. was funded by a grant from the Medical Research Council UK (MR/K011480/1). A.P.M. is a Wellcome Trust Senior Fellow in Basic Biomedical Science (grant WT098017). All authors declare there are no conflicts of interest. PMID:28333195

Semantic Metrics for Analysis of Software

NASA Technical Reports Server (NTRS)

Etzkorn, Letha H.; Cox, Glenn W.; Farrington, Phil; Utley, Dawn R.; Ghalston, Sampson; Stein, Cara

2005-01-01

A recently conceived suite of object-oriented software metrics focus is on semantic aspects of software, in contradistinction to traditional software metrics, which focus on syntactic aspects of software. Semantic metrics represent a more human-oriented view of software than do syntactic metrics. The semantic metrics of a given computer program are calculated by use of the output of a knowledge-based analysis of the program, and are substantially more representative of software quality and more readily comprehensible from a human perspective than are the syntactic metrics.

Software Reliability Analysis of NASA Space Flight Software: A Practical Experience

PubMed Central

Sukhwani, Harish; Alonso, Javier; Trivedi, Kishor S.; Mcginnis, Issac

2017-01-01

In this paper, we present the software reliability analysis of the flight software of a recently launched space mission. For our analysis, we use the defect reports collected during the flight software development. We find that this software was developed in multiple releases, each release spanning across all software life-cycle phases. We also find that the software releases were developed and tested for four different hardware platforms, spanning from off-the-shelf or emulation hardware to actual flight hardware. For releases that exhibit reliability growth or decay, we fit Software Reliability Growth Models (SRGM); otherwise we fit a distribution function. We find that most releases exhibit reliability growth, with Log-Logistic (NHPP) and S-Shaped (NHPP) as the best-fit SRGMs. For the releases that experience reliability decay, we investigate the causes for the same. We find that such releases were the first software releases to be tested on a new hardware platform, and hence they encountered major hardware integration issues. Also such releases seem to have been developed under time pressure in order to start testing on the new hardware platform sooner. Such releases exhibit poor reliability growth, and hence exhibit high predicted failure rate. Other problems include hardware specification changes and delivery delays from vendors. Thus, our analysis provides critical insights and inputs to the management to improve the software development process. As NASA has moved towards a product line engineering for its flight software development, software for future space missions will be developed in a similar manner and hence the analysis results for this mission can be considered as a baseline for future flight software missions. PMID:29278255

Software Reliability Analysis of NASA Space Flight Software: A Practical Experience.

PubMed

Sukhwani, Harish; Alonso, Javier; Trivedi, Kishor S; Mcginnis, Issac

2016-01-01

In this paper, we present the software reliability analysis of the flight software of a recently launched space mission. For our analysis, we use the defect reports collected during the flight software development. We find that this software was developed in multiple releases, each release spanning across all software life-cycle phases. We also find that the software releases were developed and tested for four different hardware platforms, spanning from off-the-shelf or emulation hardware to actual flight hardware. For releases that exhibit reliability growth or decay, we fit Software Reliability Growth Models (SRGM); otherwise we fit a distribution function. We find that most releases exhibit reliability growth, with Log-Logistic (NHPP) and S-Shaped (NHPP) as the best-fit SRGMs. For the releases that experience reliability decay, we investigate the causes for the same. We find that such releases were the first software releases to be tested on a new hardware platform, and hence they encountered major hardware integration issues. Also such releases seem to have been developed under time pressure in order to start testing on the new hardware platform sooner. Such releases exhibit poor reliability growth, and hence exhibit high predicted failure rate. Other problems include hardware specification changes and delivery delays from vendors. Thus, our analysis provides critical insights and inputs to the management to improve the software development process. As NASA has moved towards a product line engineering for its flight software development, software for future space missions will be developed in a similar manner and hence the analysis results for this mission can be considered as a baseline for future flight software missions.

Learn by Yourself: The Self-Learning Tools for Qualitative Analysis Software Packages

ERIC Educational Resources Information Center

Freitas, Fábio; Ribeiro, Jaime; Brandão, Catarina; Reis, Luís Paulo; de Souza, Francislê Neri; Costa, António Pedro

2017-01-01

Computer Assisted Qualitative Data Analysis Software (CAQDAS) are tools that help researchers to develop qualitative research projects. These software packages help the users with tasks such as transcription analysis, coding and text interpretation, writing and annotation, content search and analysis, recursive abstraction, grounded theory…

Kubios HRV--heart rate variability analysis software.

PubMed

Tarvainen, Mika P; Niskanen, Juha-Pekka; Lipponen, Jukka A; Ranta-Aho, Perttu O; Karjalainen, Pasi A

2014-01-01

Kubios HRV is an advanced and easy to use software for heart rate variability (HRV) analysis. The software supports several input data formats for electrocardiogram (ECG) data and beat-to-beat RR interval data. It includes an adaptive QRS detection algorithm and tools for artifact correction, trend removal and analysis sample selection. The software computes all the commonly used time-domain and frequency-domain HRV parameters and several nonlinear parameters. There are several adjustable analysis settings through which the analysis methods can be optimized for different data. The ECG derived respiratory frequency is also computed, which is important for reliable interpretation of the analysis results. The analysis results can be saved as an ASCII text file (easy to import into MS Excel or SPSS), Matlab MAT-file, or as a PDF report. The software is easy to use through its compact graphical user interface. The software is available free of charge for Windows and Linux operating systems at http://kubios.uef.fi. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

An online database for plant image analysis software tools.

PubMed

Lobet, Guillaume; Draye, Xavier; Périlleux, Claire

2013-10-09

Recent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research. We present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions. The plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.

GWAMA: software for genome-wide association meta-analysis.

PubMed

Mägi, Reedik; Morris, Andrew P

2010-05-28

Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies. We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genome-wide meta-analysis results. The GWAMA (Genome-Wide Association Meta-Analysis) software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.

Software Engineering Improvement Activities/Plan

NASA Technical Reports Server (NTRS)

2003-01-01

bd Systems personnel accomplished the technical responsibilities for this reporting period, as planned. A close working relationship was maintained with personnel of the MSFC Avionics Department Software Group (ED14). Work accomplishments included development, evaluation, and enhancement of a software cost model, performing literature search and evaluation of software tools available for code analysis and requirements analysis, and participating in other relevant software engineering activities. Monthly reports were submitted. This support was provided to the Flight Software Group/ED 1 4 in accomplishing the software engineering improvement engineering activities of the Marshall Space Flight Center (MSFC) Software Engineering Improvement Plan.

Expression profiles of miRNAs from bovine mammary glands in response to Streptococcus agalactiae-induced mastitis.

PubMed

Pu, Junhua; Li, Rui; Zhang, Chenglong; Chen, Dan; Liao, Xiangxiang; Zhu, Yihui; Geng, Xiaohan; Ji, Dejun; Mao, Yongjiang; Gong, Yunchen; Yang, Zhangping

2017-08-01

This study aimed to describe the expression profiles of microRNAs (miRNAs) from mammary gland tissues collected from dairy cows with Streptococcus agalactiae-induced mastitis and to identify differentially expressed miRNAs related to mastitis. The mammary glands of Chinese Holstein cows were challenged with Streptococcus agalactiae to induce mastitis. Small RNAs were isolated from the mammary tissues of the test and control groups and then sequenced using the Solexa sequencing technology to construct two small RNA libraries. Potential target genes of these differentially expressed miRNAs were predicted using the RNAhybrid software, and KEGG pathways associated with these genes were analysed. A total of 18 555 913 and 20 847 000 effective reads were obtained from the test and control groups, respectively. In total, 373 known and 399 novel miRNAs were detected in the test group, and 358 known and 232 novel miRNAs were uncovered in the control group. A total of 35 differentially expressed miRNAs were identified in the test group compared to the control group, including 10 up-regulated miRNAs and 25 down-regulated miRNAs. Of these miRNAs, miR-223 exhibited the highest degree of up-regulation with an approximately 3-fold increase in expression, whereas miR-26a exhibited the most decreased expression level (more than 2-fold). The RNAhybrid software predicted 18 801 genes as potential targets of these 35 miRNAs. Furthermore, several immune response and signal transduction pathways, including the RIG-I-like receptor signalling pathway, cytosolic DNA sensing pathway and Notch signal pathway, were enriched in these predicted targets. In summary, this study provided experimental evidence for the mechanism underlying the regulation of bovine mastitis by miRNAs and showed that miRNAs might be involved in signal pathways during S. agalactiae-induced mastitis.

Activation of Wnt/β-Catenin Pathway in Monocytes Derived from Chronic Kidney Disease Patients

PubMed Central

Al-Chaqmaqchi, Heevy Abdulkareem Musa; Moshfegh, Ali; Dadfar, Elham; Paulsson, Josefin; Hassan, Moustapha; Jacobson, Stefan H.; Lundahl, Joachim

2013-01-01

Patients with chronic kidney disease (CKD) have significantly increased morbidity and mortality resulting from infections and cardiovascular diseases. Since monocytes play an essential role in host immunity, this study was directed to explore the gene expression profile in order to identify differences in activated pathways in monocytes relevant to the pathophysiology of atherosclerosis and increased susceptibility to infections. Monocytes from CKD patients (stages 4 and 5, estimated GFR <20 ml/min/1.73 m2) and healthy donors were collected from peripheral blood. Microarray gene expression profile was performed and data were interpreted by GeneSpring software and by PANTHER tool. Western blot was done to validate the pathway members. The results demonstrated that 600 and 272 genes were differentially up- and down regulated respectively in the patient group. Pathways involved in the inflammatory response were highly expressed and the Wnt/β-catenin signaling pathway was the most significant pathway expressed in the patient group. Since this pathway has been attributed to a variety of inflammatory manifestations, the current findings may contribute to dysfunctional monocytes in CKD patients. Strategies to interfere with this pathway may improve host immunity and prevent cardiovascular complications in CKD patients. PMID:23935909

Validating the Effectiveness of Switching the Vancomycin TDM Analysis Software Based on the Predictive Accuracy.

PubMed

Imai, Shungo; Yamada, Takehiro; Ishiguro, Nobuhisa; Miyamoto, Takenori; Kagami, Keisuke; Tomiyama, Naoki; Niinuma, Yusuke; Nagasaki, Daisuke; Suzuki, Koji; Yamagami, Akira; Kasashi, Kumiko; Kobayashi, Masaki; Iseki, Ken

2017-01-01

Based on the predictive performance in our previous study, we switched the therapeutic drug monitoring (TDM) analysis software for dose setting of vancomycin (VCM) from "Vancomycin MEEK TDM analysis software Ver2.0" (MEEK) to "SHIONOGI-VCM-TDM ver.2009" (VCM-TDM) in January 2015. In the present study, our aim was to validate the effectiveness of the changing VCM TDM analysis software in initial dose setting of VCM. The enrolled patients were divided into two groups, each having 162 patients in total, who received VCM with the initial dose set using MEEK (MEEK group) or VCM-TDM (VCM-TDM group). We compared the rates of attaining the therapeutic range (trough value; 10-20 μg/mL) of serum VCM concentration between the groups. Multivariate logistic regression analysis was performed to confirm that changing the VCM TDM analysis software was an independent factor related to attaining the therapeutic range. Switching the VCM TDM analysis software from MEEK to VCM-TDM improved the rate of attaining the therapeutic range by 21.6% (MEEK group: 42.6% vs. VCM-TDM group: 64.2%, p<0.01). Patient age ≥65 years, concomitant medication (furosemide) and the TDM analysis software used VCM-TDM were considered to be independent factors for attaining the therapeutic range. These results demonstrated the effectiveness of switching the VCM TDM analysis software from MEEK to VCM-TDM for initial dose setting of VCM.

[Urine metabonomic study on hypertension patients of ascendant hyperactivity of gan yang syndrome by high performance liquid chromatography coupled with time of flight mass spectrometry].

PubMed

Jiang, Hai-Qiang; Li, Yun-Lun; Xie, Jun

2012-03-01

To study the changes of urine metabolites in hypertension patients of ascendant hyperactivity of Gan yang syndrome (AHGYS), and to explore its essence in hypertension patients. Ten typical hypertension patients of AHGYS were recruited as the patient group, and the other twelve healthy volunteers were recruited as the normal group. The metabolite profiling in the urine were collected using by high performance liquid chromatography coupled with time of flight mass spectrometry (HPLC-TOFMS). The principal component analysis (PCA) and partial least-square discriminant analysis (PLS-DA) were analyzed using SIMCA-P Software. The differential metabolites in the urine were found out and identified. The possible relevant metabolic pathways were explained. The data from the analysis by PCA in the urine samples of the patient group and the normal group showed, two sets of data could be obviously classified in the score plot. Compared with the normal group, significant changes happened to the body metabolism in the patient group. The metabolites relevant to hypertension patients of AHGYS were determined using the PLS-DA. Fifteen compounds of the structure and metabolic pathways had been confirmed through inquiring KEGG Database, mainly including amino acids, free fatty acids, sphingosine, and so on. The hypertension patients of AHGYS were studied using HPLC-TOFMS combined with pattern recognition, thus finding out small molecular metabolic markers from the microscopic field, which was advantageous in probing the biological nature of Chinese medicine syndromes.

Development of a New VLBI Data Analysis Software

NASA Technical Reports Server (NTRS)

Bolotin, Sergei; Gipson, John M.; MacMillan, Daniel S.

2010-01-01

We present an overview of a new VLBI analysis software under development at NASA GSFC. The new software will replace CALC/SOLVE and many related utility programs. It will have the capabilities of the current system as well as incorporate new models and data analysis techniques. In this paper we give a conceptual overview of the new software. We formulate the main goals of the software. The software should be flexible and modular to implement models and estimation techniques that currently exist or will appear in future. On the other hand it should be reliable and possess production quality for processing standard VLBI sessions. Also, it needs to be capable of processing observations from a fully deployed network of VLBI2010 stations in a reasonable time. We describe the software development process and outline the software architecture.

Development of Automated Image Analysis Software for Suspended Marine Particle Classification

DTIC Science & Technology

2002-09-30

Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...and global water column. 1 OBJECTIVES The project’s objective is to develop automated image analysis software to reduce the effort and time

ABC transporters and the proteasome complex are implicated in susceptibility to Stevens-Johnson syndrome and toxic epidermal necrolysis across multiple drugs.

PubMed

Nicoletti, Paola; Bansal, Mukesh; Lefebvre, Celine; Guarnieri, Paolo; Shen, Yufeng; Pe'er, Itsik; Califano, Andrea; Floratos, Aris

2015-01-01

Stevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) represent rare but serious adverse drug reactions (ADRs). Both are characterized by distinctive blistering lesions and significant mortality rates. While there is evidence for strong drug-specific genetic predisposition related to HLA alleles, recent genome wide association studies (GWAS) on European and Asian populations have failed to identify genetic susceptibility alleles that are common across multiple drugs. We hypothesize that this is a consequence of the low to moderate effect size of individual genetic risk factors. To test this hypothesis we developed Pointer, a new algorithm that assesses the aggregate effect of multiple low risk variants on a pathway using a gene set enrichment approach. A key advantage of our method is the capability to associate SNPs with genes by exploiting physical proximity as well as by using expression quantitative trait loci (eQTLs) that capture information about both cis- and trans-acting regulatory effects. We control for known bias-inducing aspects of enrichment based analyses, such as: 1) gene length, 2) gene set size, 3) presence of biologically related genes within the same linkage disequilibrium (LD) region, and, 4) genes shared among multiple gene sets. We applied this approach to publicly available SJS/TEN genome-wide genotype data and identified the ABC transporter and Proteasome pathways as potentially implicated in the genetic susceptibility of non-drug-specific SJS/TEN. We demonstrated that the innovative SNP-to-gene mapping phase of the method was essential in detecting the significant enrichment for those pathways. Analysis of an independent gene expression dataset provides supportive functional evidence for the involvement of Proteasome pathways in SJS/TEN cutaneous lesions. These results suggest that Pointer provides a useful framework for the integrative analysis of pharmacogenetic GWAS data, by increasing the power to detect aggregate effects of multiple low risk variants. The software is available for download at https://sourceforge.net/projects/pointergsa/.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

PubMed

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.

Computer-assisted qualitative data analysis software.

PubMed

Cope, Diane G

2014-05-01

Advances in technology have provided new approaches for data collection methods and analysis for researchers. Data collection is no longer limited to paper-and-pencil format, and numerous methods are now available through Internet and electronic resources. With these techniques, researchers are not burdened with entering data manually and data analysis is facilitated by software programs. Quantitative research is supported by the use of computer software and provides ease in the management of large data sets and rapid analysis of numeric statistical methods. New technologies are emerging to support qualitative research with the availability of computer-assisted qualitative data analysis software (CAQDAS).CAQDAS will be presented with a discussion of advantages, limitations, controversial issues, and recommendations for this type of software use.

Orbiter subsystem hardware/software interaction analysis. Volume 8: Forward reaction control system

NASA Technical Reports Server (NTRS)

Becker, D. D.

1980-01-01

The results of the orbiter hardware/software interaction analysis for the AFT reaction control system are presented. The interaction between hardware failure modes and software are examined in order to identify associated issues and risks. All orbiter subsystems and interfacing program elements which interact with the orbiter computer flight software are analyzed. The failure modes identified in the subsystem/element failure mode and effects analysis are discussed.

Sneak Analysis Application Guidelines

DTIC Science & Technology

1982-06-01

Hardware Program Change Cost Trend, Airborne Environment ....... ....................... 111 3-11 Relative Software Program Change Costs...113 3-50 Derived Software Program Change Cost by Phase,* Airborne Environment ..... ............... 114 3-51 Derived Software Program Change...Cost by Phase, Ground/Water Environment ... ............. .... 114 3-52 Total Software Program Change Costs ................ 115 3-53 Sneak Analysis

Software Users Manual (SUM): Extended Testability Analysis (ETA) Tool

NASA Technical Reports Server (NTRS)

Maul, William A.; Fulton, Christopher E.

2011-01-01

This software user manual describes the implementation and use the Extended Testability Analysis (ETA) Tool. The ETA Tool is a software program that augments the analysis and reporting capabilities of a commercial-off-the-shelf (COTS) testability analysis software package called the Testability Engineering And Maintenance System (TEAMS) Designer. An initial diagnostic assessment is performed by the TEAMS Designer software using a qualitative, directed-graph model of the system being analyzed. The ETA Tool utilizes system design information captured within the diagnostic model and testability analysis output from the TEAMS Designer software to create a series of six reports for various system engineering needs. The ETA Tool allows the user to perform additional studies on the testability analysis results by determining the detection sensitivity to the loss of certain sensors or tests. The ETA Tool was developed to support design and development of the NASA Ares I Crew Launch Vehicle. The diagnostic analysis provided by the ETA Tool was proven to be valuable system engineering output that provided consistency in the verification of system engineering requirements. This software user manual provides a description of each output report generated by the ETA Tool. The manual also describes the example diagnostic model and supporting documentation - also provided with the ETA Tool software release package - that were used to generate the reports presented in the manual

Software for quantitative analysis of radiotherapy: overview, requirement analysis and design solutions.

PubMed

Zhang, Lanlan; Hub, Martina; Mang, Sarah; Thieke, Christian; Nix, Oliver; Karger, Christian P; Floca, Ralf O

2013-06-01

Radiotherapy is a fast-developing discipline which plays a major role in cancer care. Quantitative analysis of radiotherapy data can improve the success of the treatment and support the prediction of outcome. In this paper, we first identify functional, conceptional and general requirements on a software system for quantitative analysis of radiotherapy. Further we present an overview of existing radiotherapy analysis software tools and check them against the stated requirements. As none of them could meet all of the demands presented herein, we analyzed possible conceptional problems and present software design solutions and recommendations to meet the stated requirements (e.g. algorithmic decoupling via dose iterator pattern; analysis database design). As a proof of concept we developed a software library "RTToolbox" following the presented design principles. The RTToolbox is available as open source library and has already been tested in a larger-scale software system for different use cases. These examples demonstrate the benefit of the presented design principles. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Annotation-based inference of transporter function.

PubMed

Lee, Thomas J; Paulsen, Ian; Karp, Peter

2008-07-01

We present a method for inferring and constructing transport reactions for transporter proteins based primarily on the analysis of the names of individual proteins in the genome annotation of an organism. Transport reactions are declarative descriptions of transporter activities, and thus can be manipulated computationally, unlike free-text protein names. Once transporter activities are encoded as transport reactions, a number of computational analyses are possible including database queries by transporter activity; inclusion of transporters into an automatically generated metabolic-map diagram that can be painted with omics data to aid in their interpretation; detection of anomalies in the metabolic and transport networks, such as substrates that are transported into the cell but are not inputs to any metabolic reaction or pathway; and comparative analyses of the transport capabilities of different organisms. On randomly selected organisms, the method achieves precision and recall rates of 0.93 and 0.90, respectively in identifying transporter proteins by name within the complete genome. The method obtains 67.5% accuracy in predicting complete transport reactions; if allowance is made for predictions that are overly general yet not incorrect, reaction prediction accuracy is 82.5%. The method is implemented as part of PathoLogic, the inference component of the Pathway Tools software. Pathway Tools is freely available to researchers at non-commercial institutions, including source code; a fee applies to commercial institutions. Supplementary data are available at Bioinformatics online.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses.

PubMed

Serbus, Laura R; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A J M Zehadee; Christensen, Steen

2017-06-07

The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. Copyright © 2017 Serbus et al.

The chemokine receptor CCR1 is identified in mast cell-derived exosomes.

PubMed

Liang, Yuting; Qiao, Longwei; Peng, Xia; Cui, Zelin; Yin, Yue; Liao, Huanjin; Jiang, Min; Li, Li

2018-01-01

Mast cells are important effector cells of the immune system, and mast cell-derived exosomes carrying RNAs play a role in immune regulation. However, the molecular function of mast cell-derived exosomes is currently unknown, and here, we identify differentially expressed genes (DEGs) in mast cells and exosomes. We isolated mast cells derived exosomes through differential centrifugation and screened the DEGs from mast cell-derived exosomes, using the GSE25330 array dataset downloaded from the Gene Expression Omnibus database. Biochemical pathways were analyzed by Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the online tool DAVID. DEGs-associated protein-protein interaction networks (PPIs) were constructed using the STRING database and Cytoscape software. The genes identified from these bioinformatics analyses were verified by qRT-PCR and Western blot in mast cells and exosomes. We identified 2121 DEGs (843 up and 1278 down-regulated genes) in HMC-1 cell-derived exosomes and HMC-1 cells. The up-regulated DEGs were classified into two significant modules. The chemokine receptor CCR1 was screened as a hub gene and enriched in cytokine-mediated signaling pathway in module one. Seven genes, including CCR1, CD9, KIT, TGFBR1, TLR9, TPSAB1 and TPSB2 were screened and validated through qRT-PCR analysis. We have achieved a comprehensive view of the pivotal genes and pathways in mast cells and exosomes and identified CCR1 as a hub gene in mast cell-derived exosomes. Our results provide novel clues with respect to the biological processes through which mast cell-derived exosomes modulate immune responses.

In vitro porcine blood-brain barrier model for permeability studies: pCEL-X software pKa(FLUX) method for aqueous boundary layer correction and detailed data analysis.

PubMed

Yusof, Siti R; Avdeef, Alex; Abbott, N Joan

2014-12-18

In vitro blood-brain barrier (BBB) models from primary brain endothelial cells can closely resemble the in vivo BBB, offering valuable models to assay BBB functions and to screen potential central nervous system drugs. We have recently developed an in vitro BBB model using primary porcine brain endothelial cells. The model shows expression of tight junction proteins and high transendothelial electrical resistance, evidence for a restrictive paracellular pathway. Validation studies using small drug-like compounds demonstrated functional uptake and efflux transporters, showing the suitability of the model to assay drug permeability. However, one limitation of in vitro model permeability measurement is the presence of the aqueous boundary layer (ABL) resulting from inefficient stirring during the permeability assay. The ABL can be a rate-limiting step in permeation, particularly for lipophilic compounds, causing underestimation of the permeability. If the ABL effect is ignored, the permeability measured in vitro will not reflect the permeability in vivo. To address the issue, we explored the combination of in vitro permeability measurement using our porcine model with the pKa(FLUX) method in pCEL-X software to correct for the ABL effect and allow a detailed analysis of in vitro (transendothelial) permeability data, Papp. Published Papp using porcine models generated by our group and other groups are also analyzed. From the Papp, intrinsic transcellular permeability (P0) is derived by simultaneous refinement using a weighted nonlinear regression, taking into account permeability through the ABL, paracellular permeability and filter restrictions on permeation. The in vitro P0 derived for 22 compounds (35 measurements) showed good correlation with P0 derived from in situ brain perfusion data (r(2)=0.61). The analysis also gave evidence for carrier-mediated uptake of naloxone, propranolol and vinblastine. The combination of the in vitro porcine model and the software analysis provides a useful tool to better predict BBB permeability in vivo and gain better mechanistic information about BBB permeation. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

MONALISA for stochastic simulations of Petri net models of biochemical systems.

PubMed

Balazki, Pavel; Lindauer, Klaus; Einloft, Jens; Ackermann, Jörg; Koch, Ina

2015-07-10

The concept of Petri nets (PN) is widely used in systems biology and allows modeling of complex biochemical systems like metabolic systems, signal transduction pathways, and gene expression networks. In particular, PN allows the topological analysis based on structural properties, which is important and useful when quantitative (kinetic) data are incomplete or unknown. Knowing the kinetic parameters, the simulation of time evolution of such models can help to study the dynamic behavior of the underlying system. If the number of involved entities (molecules) is low, a stochastic simulation should be preferred against the classical deterministic approach of solving ordinary differential equations. The Stochastic Simulation Algorithm (SSA) is a common method for such simulations. The combination of the qualitative and semi-quantitative PN modeling and stochastic analysis techniques provides a valuable approach in the field of systems biology. Here, we describe the implementation of stochastic analysis in a PN environment. We extended MONALISA - an open-source software for creation, visualization and analysis of PN - by several stochastic simulation methods. The simulation module offers four simulation modes, among them the stochastic mode with constant firing rates and Gillespie's algorithm as exact and approximate versions. The simulator is operated by a user-friendly graphical interface and accepts input data such as concentrations and reaction rate constants that are common parameters in the biological context. The key features of the simulation module are visualization of simulation, interactive plotting, export of results into a text file, mathematical expressions for describing simulation parameters, and up to 500 parallel simulations of the same parameter sets. To illustrate the method we discuss a model for insulin receptor recycling as case study. We present a software that combines the modeling power of Petri nets with stochastic simulation of dynamic processes in a user-friendly environment supported by an intuitive graphical interface. The program offers a valuable alternative to modeling, using ordinary differential equations, especially when simulating single-cell experiments with low molecule counts. The ability to use mathematical expressions provides an additional flexibility in describing the simulation parameters. The open-source distribution allows further extensions by third-party developers. The software is cross-platform and is licensed under the Artistic License 2.0.

A Comparative Study of Pathways to Care for Children with Specific Learning Disability and Mental Retardation

PubMed Central

Chakraborty, Suhash; Kommu, John Vijay Sagar; Srinath, Shoba; Seshadri, Shekhar P.; Girimaji, Satish C.

2014-01-01

Context: Early intervention in specific learning disability (SpLD) results in better outcome and prevents comorbidity. Understanding the pathways is therefore important. Aims: To study and compare the pathways to care for children with SpLD and mental retardation (MR) before reaching a tertiary care center. Settings and Design, Material and Methods: A cross-sectional study was conducted for pathways to care of two groups: SpLD and MR with 50 children in each group from 8 to 16 years. MINI-KID for comorbidity and Goldberg's pathway to care instrument was used. The groups were divided into early contact (up to three carers) and late contact (more than three carers) and compared. Statistical Analysis: Data were analyzed using Statistical Packages for Social Sciences (SPSS) version 10.0 software. Results: Majority (n = 24 or 48%) of SpLD children visited “others” (teachers, neighbors, relatives, and guardians of fellow classmates) as first carer. Allopathic practitioners were the first choice for MR children (n = 31 or 62%). Six children (12%) in SpLD group and 10 of MR (20%) group have seen either traditional practitioner or healer as first carer. Maximum referral to the tertiary center in both groups was done by others (62% in SpLD and 56% in MR group). Early contacts in SpLD group belonged to younger age group (P = 0.01). While comparing both groups on the basis of early and late contact, mother's education was found to be significant in early contact group (P = 0.036) and having comorbidity was significant among late contacts (P = 0.038). Conclusions: The pathways to care for SpLD children are more or less similar to MR children whose parents recognize MR late. Both the groups visit multiple carers including traditional healers substantiating the strong belief for supernatural causation of developmental disorders in India. PMID:24701006

Theoretical and software considerations for nonlinear dynamic analysis

NASA Technical Reports Server (NTRS)

Schmidt, R. J.; Dodds, R. H., Jr.

1983-01-01

In the finite element method for structural analysis, it is generally necessary to discretize the structural model into a very large number of elements to accurately evaluate displacements, strains, and stresses. As the complexity of the model increases, the number of degrees of freedom can easily exceed the capacity of present-day software system. Improvements of structural analysis software including more efficient use of existing hardware and improved structural modeling techniques are discussed. One modeling technique that is used successfully in static linear and nonlinear analysis is multilevel substructuring. This research extends the use of multilevel substructure modeling to include dynamic analysis and defines the requirements for a general purpose software system capable of efficient nonlinear dynamic analysis. The multilevel substructuring technique is presented, the analytical formulations and computational procedures for dynamic analysis and nonlinear mechanics are reviewed, and an approach to the design and implementation of a general purpose structural software system is presented.

Using recurrence plot analysis for software execution interpretation and fault detection

NASA Astrophysics Data System (ADS)

Mosdorf, M.

2015-09-01

This paper shows a method targeted at software execution interpretation and fault detection using recurrence plot analysis. In in the proposed approach recurrence plot analysis is applied to software execution trace that contains executed assembly instructions. Results of this analysis are subject to further processing with PCA (Principal Component Analysis) method that simplifies number coefficients used for software execution classification. This method was used for the analysis of five algorithms: Bubble Sort, Quick Sort, Median Filter, FIR, SHA-1. Results show that some of the collected traces could be easily assigned to particular algorithms (logs from Bubble Sort and FIR algorithms) while others are more difficult to distinguish.

Personalized Guideline-Based Treatment Recommendations Using Natural Language Processing Techniques.

PubMed

Becker, Matthias; Böckmann, Britta

2017-01-01

Clinical guidelines and clinical pathways are accepted and proven instruments for quality assurance and process optimization. Today, electronic representation of clinical guidelines exists as unstructured text, but is not well-integrated with patient-specific information from electronic health records. Consequently, generic content of the clinical guidelines is accessible, but it is not possible to visualize the position of the patient on the clinical pathway, decision support cannot be provided by personalized guidelines for the next treatment step. The Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) provides common reference terminology as well as the semantic link for combining the pathways and the patient-specific information. This paper proposes a model-based approach to support the development of guideline-compliant pathways combined with patient-specific structured and unstructured information using SNOMED CT. To identify SNOMED CT concepts, a software was developed to extract SNOMED CT codes out of structured and unstructured German data to map these with clinical pathways annotated in accordance with the systematized nomenclature.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

PubMed

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait networks if the edges can be anchored to genetic marker data. R software tutorials, data, and supplementary material can be downloaded from: http://www.genetics.ucla.edu/labs/horvath/aten/NEO.

Performing Quantitative Imaging Acquisition, Analysis and Visualization Using the Best of Open Source and Commercial Software Solutions.

PubMed

Shenoy, Shailesh M

2016-07-01

A challenge in any imaging laboratory, especially one that uses modern techniques, is to achieve a sustainable and productive balance between using open source and commercial software to perform quantitative image acquisition, analysis and visualization. In addition to considering the expense of software licensing, one must consider factors such as the quality and usefulness of the software's support, training and documentation. Also, one must consider the reproducibility with which multiple people generate results using the same software to perform the same analysis, how one may distribute their methods to the community using the software and the potential for achieving automation to improve productivity.

Analyzing qualitative data with computer software.

PubMed Central

Weitzman, E A

1999-01-01

OBJECTIVE: To provide health services researchers with an overview of the qualitative data analysis process and the role of software within it; to provide a principled approach to choosing among software packages to support qualitative data analysis; to alert researchers to the potential benefits and limitations of such software; and to provide an overview of the developments to be expected in the field in the near future. DATA SOURCES, STUDY DESIGN, METHODS: This article does not include reports of empirical research. CONCLUSIONS: Software for qualitative data analysis can benefit the researcher in terms of speed, consistency, rigor, and access to analytic methods not available by hand. Software, however, is not a replacement for methodological training. PMID:10591282

An Analysis of Mission Critical Computer Software in Naval Aviation

DTIC Science & Technology

1991-03-01

No. Task No. Work Unit Accesion Number 11. TITLE (Include Security Classification) AN ANALYSIS OF MISSION CRITICAL COMPUTER SOFTWARE IN NAVAL AVIATION...software development schedules were sustained without a milestone change being made. Also, software that was released to the fleet had no major...fleet contain any major defects? This research has revealed that only about half of the original software development schedules were sustained without a

LV software support for supersonic flow analysis

NASA Technical Reports Server (NTRS)

Bell, W. A.; Lepicovsky, J.

1992-01-01

The software for configuring an LV counter processor system has been developed using structured design. The LV system includes up to three counter processors and a rotary encoder. The software for configuring and testing the LV system has been developed, tested, and included in an overall software package for data acquisition, analysis, and reduction. Error handling routines respond to both operator and instrument errors which often arise in the course of measuring complex, high-speed flows. The use of networking capabilities greatly facilitates the software development process by allowing software development and testing from a remote site. In addition, high-speed transfers allow graphics files or commands to provide viewing of the data from a remote site. Further advances in data analysis require corresponding advances in procedures for statistical and time series analysis of nonuniformly sampled data.

LV software support for supersonic flow analysis

NASA Technical Reports Server (NTRS)

Bell, William A.

1992-01-01

The software for configuring a Laser Velocimeter (LV) counter processor system was developed using structured design. The LV system includes up to three counter processors and a rotary encoder. The software for configuring and testing the LV system was developed, tested, and included in an overall software package for data acquisition, analysis, and reduction. Error handling routines respond to both operator and instrument errors which often arise in the course of measuring complex, high-speed flows. The use of networking capabilities greatly facilitates the software development process by allowing software development and testing from a remote site. In addition, high-speed transfers allow graphics files or commands to provide viewing of the data from a remote site. Further advances in data analysis require corresponding advances in procedures for statistical and time series analysis of nonuniformly sampled data.

Spacelab user implementation assessment study. (Software requirements analysis). Volume 2: Technical report

NASA Technical Reports Server (NTRS)

1976-01-01

The engineering analyses and evaluation studies conducted for the Software Requirements Analysis are discussed. Included are the development of the study data base, synthesis of implementation approaches for software required by both mandatory onboard computer services and command/control functions, and identification and implementation of software for ground processing activities.

Microarray analysis of gene expression alteration in human middle ear epithelial cells induced by micro particle.

PubMed

Song, Jae-Jun; Kwon, Jee Young; Park, Moo Kyun; Seo, Young Rok

2013-10-01

The primary aim of this study is to reveal the effect of particulate matter (PM) on the human middle ear epithelial cell (HMEEC). The HMEEC was treated with PM (300 μg/ml) for 24 h. Total RNA was extracted and used for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed by using Pathway Studio 9.0 software. For selected genes, the changes in gene expression were confirmed by real-time PCR. A total of 611 genes were regulated by PM. Among them, 366 genes were up-regulated, whereas 245 genes were down-regulated. Up-regulated genes were mainly involved in cellular processes, including reactive oxygen species generation, cell proliferation, apoptosis, cell differentiation, inflammatory response and immune response. Down-regulated genes affected several cellular processes, including cell differentiation, cell cycle, proliferation, apoptosis and cell migration. A total of 21 genes were discovered as crucial components in potential signaling networks containing 2-fold up regulated genes. Four genes, VEGFA, IL1B, CSF2 and HMOX1 were revealed as key mediator genes among the up-regulated genes. A total of 25 genes were revealed as key modulators in the signaling pathway associated with 2-fold down regulated genes. Four genes, including IGF1R, TIMP1, IL6 and FN1, were identified as the main modulator genes. We identified the differentially expressed genes in PM-treated HMEEC, whose expression profile may provide a useful clue for the understanding of environmental pathophysiology of otitis media. Our work indicates that air pollution, like PM, plays an important role in the pathogenesis of otitis media. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Escin Chemosensitizes Human Pancreatic Cancer Cells and Inhibits the Nuclear Factor-kappaB Signaling Pathway

PubMed Central

Rimmon, A.; Vexler, A.; Berkovich, L.; Earon, G.; Ron, I.; Lev-Ari, S.

2013-01-01

Background. There is an urgent need to develop new treatment strategies and drugs for pancreatic cancer that is highly resistant to radio-chemotherapy. Aesculus hippocastanum (the horse chestnut) known in Chinese medicine as a plant with anti-inflammatory, antiedema, antianalgesic, and antipyretic activities. The main active compound of this plant is Escin (C54H84O23). Objective. To evaluate the effect of Escin alone and combined with chemotherapy on pancreatic cancer cell survival and to unravel mechanism(s) of Escin anticancer activity. Methods. Cell survival was measured by XTT colorimetric assay. Synergistic effect of combined therapy was determined by CalcuSyn software. Cell cycle and induction of apoptosis were evaluated by FACS analysis. Expression of NF-κB-related proteins (p65, IκBα, and p-IκBα) and cyclin D was evaluated by western blot analysis. Results. Escin decreased the survival of pancreatic cancer cells with IC50 = 10–20 M. Escin combined with gemcitabine showed only additive effect, while its combination with cisplatin resulted in a significant synergistic cytotoxic effect in Panc-1 cells. High concentrations of Escin induced apoptosis and decreased NF-κB-related proteins and cyclin D expression. Conclusions. Escin decreased pancreatic cancer cell survival, induced apoptosis, and downregulated NF-κB signaling pathway. Moreover, Escin sensitized pancreatic cancer cells to chemotherapy. Further translational research is required. PMID:24282639

Aberrant DNA methylation of miR-219 promoter in long-term night shiftworkers.

PubMed

Shi, Fengqin; Chen, Xinyi; Fu, Alan; Hansen, Johnni; Stevens, Richard; Tjonneland, Anne; Vogel, Ulla B; Zheng, Tongzhang; Zhu, Yong

2013-07-01

The idea that shiftwork may be carcinogenic in humans has gained widespread attention since the pioneering work linking shiftwork to breast cancer over two decades ago. However, the biomolecular consequences of long-term shiftwork exposure have not been fully explored. In this study, we performed a genome-wide CpG island methylation assay of microRNA (miRNA) promoters in long-term night shiftworkers and day workers. This analysis indicated that 50 CpG loci corresponding to 31 miRNAs were differentially methylated in night shiftworkers compared to day workers, including the circadian-relevant miR-219, the expression of which has been implicated in several cancers. A genome-wide expression microarray assay was carried out in a miR-219-overexpressed MCF-7 breast cancer cell line, which identified 319 differentially expressed transcripts. The identified transcriptional targets were analyzed for network and functional interrelatedness using the Ingenuity Pathway Analysis (IPA) software. Overexpression of miR-219 in MCF-7 breast cancer cells resulted in accentuated expression of apoptosis- and proliferation-related anti-viral immunodulators of the Jak-STAT and NF-κβ pathways. These findings suggest that long-term night shiftwork exposure may lead to the methylation-dependent downregulation of miR-219, which may in turn lead to the downregulation of immunomediated antitumor activity and increased breast cancer risk. © 2013 Wiley Periodicals, Inc.

A comparative analysis of optical and conventional axiography for the analysis of temporomandibular joint movements.

PubMed

Wagner, Arne; Seemann, Rudolf; Schicho, Kurt; Ewers, Rolf; Piehslinger, Eva

2003-11-01

Currently available systems for pantographic tracing are heavy, bulky, and can interfere with jaw movements. This study describes the development and clinical application of optoelectronic axiography designed to overcome system inherent problems of conventional bulky frame-based registration axiography. The purpose of this study is the comparison of the newly developed system and conventional axiography. Three-dimensional recordings of condylar pathways were acquired by means of infrared digitizers interfaced to newly developed software. Ten distinct curves in each of 10 subjects were recorded by synchronous optoelectronic axiography (100 tracings) and by conventional axiography (100 tracings). Usually, two 3-dimensional (3D) light weight sensors are provisionally fixed to the facial surface of a maxillary and mandibular incisor by means of a single orthodontic bracket. To allow for direct comparison of all 100 pairs of curves in this study, the 3D sensors of the optoelectronic system were attached to the bulky double face-bow system of the axiograph. The conformity of tracings (protrusion, opening/closing, mediotrusion, and laterotrusion) was evaluated by means of correlation analysis. Resulting axiographic recordings from both systems were evaluated by 3 experts (dentists, experienced in axiographic investigations, who were blind to the source of the data), focusing on standardized qualitative criteria of the recordings (homogeneity/smoothness, pathway-characteristics, excursion, and left/right-symmetry). After testing for normal distribution of the ratio scaled data (length of pathway, horizontal condylar inclination [HCI], Bennett angle) with the Kolmogoroff-Smirnov test (alpha=.01), axiographic curves were quantitatively compared by means of an intraclass correlation coefficient ([ICC] alpha =.01). The Wilcoxon test (alpha=.01) was used to evaluate equivalence of ordinally scaled values (homogeneity of tracings) and Cohen's Kappa was used to compare excursion and left/right symmetry. High correspondence between curves recorded by conventional and optoelectronic axiography was observed. The mean differences of lengths between the protrusive, opening/closing, and mediotrusive pathways were 0.0 mm, 0.6 mm, and 0.1 mm, respectively. Pathways and values for HCI were found highly correlated (pathways: 95% CI of ICC 0.9776-0.9908; HCI: 95% CI of ICC 0.8641-0.9597). The 95% CIs for differences of pathways, HCI-value, and Bennett angle were -0.1mm/0.3mm, -3.4 degrees/1.9 degrees, and -2.8 degrees/4.8 degrees, respectively. Pathway characteristics also corresponded well (Cohen's Kappa: 0.73 for symmetric and 0.72 for asymmetric movements), 0.77 for left/right symmetry, whereas other characteristics showed less significant correlation (Cohen's Kappa of excursion: 0.21 for symmetric and 0.09 for asymmetric movements, homogeneity: 0.08 for symmetric and 0.15 for asymmetric movements). Within the limitations of this study, optoelectronic axiography proved to be an applicable, promising technique, leading to diagnostic interpretations equivalent (with respect to the CIs) to conventional axiography.

Functional annotation of regulatory pathways.

PubMed

Pandey, Jayesh; Koyutürk, Mehmet; Kim, Yohan; Szpankowski, Wojciech; Subramaniam, Shankar; Grama, Ananth

2007-07-01

Standardized annotations of biomolecules in interaction networks (e.g. Gene Ontology) provide comprehensive understanding of the function of individual molecules. Extending such annotations to pathways is a critical component of functional characterization of cellular signaling at the systems level. We propose a framework for projecting gene regulatory networks onto the space of functional attributes using multigraph models, with the objective of deriving statistically significant pathway annotations. We first demonstrate that annotations of pairwise interactions do not generalize to indirect relationships between processes. Motivated by this result, we formalize the problem of identifying statistically overrepresented pathways of functional attributes. We establish the hardness of this problem by demonstrating the non-monotonicity of common statistical significance measures. We propose a statistical model that emphasizes the modularity of a pathway, evaluating its significance based on the coupling of its building blocks. We complement the statistical model by an efficient algorithm and software, Narada, for computing significant pathways in large regulatory networks. Comprehensive results from our methods applied to the Escherichia coli transcription network demonstrate that our approach is effective in identifying known, as well as novel biological pathway annotations. Narada is implemented in Java and is available at http://www.cs.purdue.edu/homes/jpandey/narada/.

GammaLib and ctools. A software framework for the analysis of astronomical gamma-ray data

NASA Astrophysics Data System (ADS)

Knödlseder, J.; Mayer, M.; Deil, C.; Cayrou, J.-B.; Owen, E.; Kelley-Hoskins, N.; Lu, C.-C.; Buehler, R.; Forest, F.; Louge, T.; Siejkowski, H.; Kosack, K.; Gerard, L.; Schulz, A.; Martin, P.; Sanchez, D.; Ohm, S.; Hassan, T.; Brau-Nogué, S.

2016-08-01

The field of gamma-ray astronomy has seen important progress during the last decade, yet to date no common software framework has been developed for the scientific analysis of gamma-ray telescope data. We propose to fill this gap by means of the GammaLib software, a generic library that we have developed to support the analysis of gamma-ray event data. GammaLib was written in C++ and all functionality is available in Python through an extension module. Based on this framework we have developed the ctools software package, a suite of software tools that enables flexible workflows to be built for the analysis of Imaging Air Cherenkov Telescope event data. The ctools are inspired by science analysis software available for existing high-energy astronomy instruments, and they follow the modular ftools model developed by the High Energy Astrophysics Science Archive Research Center. The ctools were written in Python and C++, and can be either used from the command line via shell scripts or directly from Python. In this paper we present the GammaLib and ctools software versions 1.0 that were released at the end of 2015. GammaLib and ctools are ready for the science analysis of Imaging Air Cherenkov Telescope event data, and also support the analysis of Fermi-LAT data and the exploitation of the COMPTEL legacy data archive. We propose using ctools as the science tools software for the Cherenkov Telescope Array Observatory.

Elements of strategic capability for software outsourcing enterprises based on the resource

NASA Astrophysics Data System (ADS)

Shi, Wengeng

2011-10-01

Software outsourcing enterprises as an emerging high-tech enterprises, the rise of the speed and the number was very amazing. In addition to Chinese software outsourcing for giving preferential policies, the software outsourcing business has its ability to upgrade, and in general the software companies have not had the related characteristics. View from the resource base of the theory, the analysis software outsourcing companies have the ability and resources of rare and valuable and non-mimic, we try to give an initial framework for theoretical analysis based on this.

Quantitation of the phosphoproteome using the library-assisted extracted ion chromatogram (LAXIC) strategy.

PubMed

Arrington, Justine V; Xue, Liang; Tao, W Andy

2014-01-01

Phosphorylation is a key posttranslational modification that regulates many signaling pathways, but quantifying changes in phosphorylation between samples can be challenging due to its low stoichiometry within cells. We have introduced a mass spectrometry-based label-free quantitation strategy termed LAXIC for the analysis of the phosphoproteome. This method uses a spiked-in synthetic peptide library designed to elute across the entire chromatogram for local normalization of phosphopeptides within complex samples. Normalization of phosphopeptides by library peptides that co-elute within a small time frame accounts for fluctuating ion suppression effects, allowing more accurate quantitation even when LC-MS performance varies. Here we explain the premise of LAXIC, the design of a suitable peptide library, and how the LAXIC algorithm can be implemented with software developed in-house.

Reaction Decoder Tool (RDT): extracting features from chemical reactions.

PubMed

Rahman, Syed Asad; Torrance, Gilliean; Baldacci, Lorenzo; Martínez Cuesta, Sergio; Fenninger, Franz; Gopal, Nimish; Choudhary, Saket; May, John W; Holliday, Gemma L; Steinbeck, Christoph; Thornton, Janet M

2016-07-01

Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder : asad@ebi.ac.uk or s9asad@gmail.com. © The Author 2016. Published by Oxford University Press.

The Comparison of VLBI Data Analysis Using Software Globl and Globk

NASA Astrophysics Data System (ADS)

Guangli, W.; Xiaoya, W.; Jinling, L.; Wenyao, Z.

The comparison of different geodetic data analysis software is one of the quite of- ten mentioned topics. In this paper we try to find out the difference between software GLOBL and GLOBK when use them to process the same set of VLBI data. GLOBL is a software developed by VLBI team, geodesy branch, GSFC/NASA to process geode- tic VLBI data using algorithm of arc-parameter-elimination, while GLOBK using al- gorithm of kalman filtering is mainly used in GPS data analysis, and it is also used in VLBI data analysis. Our work focus on whether there are significant difference when use the two softwares to analyze the same VLBI data set and investigate the reasons caused the difference.

ACES: Space shuttle flight software analysis expert system

NASA Technical Reports Server (NTRS)

Satterwhite, R. Scott

1990-01-01

The Analysis Criteria Evaluation System (ACES) is a knowledge based expert system that automates the final certification of the Space Shuttle onboard flight software. Guidance, navigation and control of the Space Shuttle through all its flight phases are accomplished by a complex onboard flight software system. This software is reconfigured for each flight to allow thousands of mission-specific parameters to be introduced and must therefore be thoroughly certified prior to each flight. This certification is performed in ground simulations by executing the software in the flight computers. Flight trajectories from liftoff to landing, including abort scenarios, are simulated and the results are stored for analysis. The current methodology of performing this analysis is repetitive and requires many man-hours. The ultimate goals of ACES are to capture the knowledge of the current experts and improve the quality and reduce the manpower required to certify the Space Shuttle onboard flight software.

The Effects of Development Team Skill on Software Product Quality

NASA Technical Reports Server (NTRS)

Beaver, Justin M.; Schiavone, Guy A.

2006-01-01

This paper provides an analysis of the effect of the skill/experience of the software development team on the quality of the final software product. A method for the assessment of software development team skill and experience is proposed, and was derived from a workforce management tool currently in use by the National Aeronautics and Space Administration. Using data from 26 smallscale software development projects, the team skill measures are correlated to 5 software product quality metrics from the ISO/IEC 9126 Software Engineering Product Quality standard. in the analysis of the results, development team skill is found to be a significant factor in the adequacy of the design and implementation. In addition, the results imply that inexperienced software developers are tasked with responsibilities ill-suited to their skill level, and thus have a significant adverse effect on the quality of the software product. Keywords: software quality, development skill, software metrics

SAO mission support software and data standards, version 1.0

NASA Technical Reports Server (NTRS)

Hsieh, P.

1993-01-01

This document defines the software developed by the SAO AXAF Mission Support (MS) Program and defines standards for the software development process and control of data products generated by the software. The SAO MS is tasked to develop and use software to perform a variety of functions in support of the AXAF mission. Software is developed by software engineers and scientists, and commercial off-the-shelf (COTS) software is used either directly or customized through the use of scripts to implement analysis procedures. Software controls real-time laboratory instruments, performs data archiving, displays data, and generates model predictions. Much software is used in the analysis of data to generate data products that are required by the AXAF project, for example, on-orbit mirror performance predictions or detailed characterization of the mirror reflection performance with energy.

Long-term Preservation of Data Analysis Capabilities

NASA Astrophysics Data System (ADS)

Gabriel, C.; Arviset, C.; Ibarra, A.; Pollock, A.

2015-09-01

While the long-term preservation of scientific data obtained by large astrophysics missions is ensured through science archives, the issue of data analysis software preservation has hardly been addressed. Efforts by large data centres have contributed so far to maintain some instrument or mission-specific data reduction packages on top of high-level general purpose data analysis software. However, it is always difficult to keep software alive without support and maintenance once the active phase of a mission is over. This is especially difficult in the budgetary model followed by space agencies. We discuss the importance of extending the lifetime of dedicated data analysis packages and review diverse strategies under development at ESA using new paradigms such as Virtual Machines, Cloud Computing, and Software as a Service for making possible full availability of data analysis and calibration software for decades at minimal cost.

Teaching meta-analysis using MetaLight.

PubMed

Thomas, James; Graziosi, Sergio; Higgins, Steve; Coe, Robert; Torgerson, Carole; Newman, Mark

2012-10-18

Meta-analysis is a statistical method for combining the results of primary studies. It is often used in systematic reviews and is increasingly a method and topic that appears in student dissertations. MetaLight is a freely available software application that runs simple meta-analyses and contains specific functionality to facilitate the teaching and learning of meta-analysis. While there are many courses and resources for meta-analysis available and numerous software applications to run meta-analyses, there are few pieces of software which are aimed specifically at helping those teaching and learning meta-analysis. Valuable teaching time can be spent learning the mechanics of a new software application, rather than on the principles and practices of meta-analysis. We discuss ways in which the MetaLight tool can be used to present some of the main issues involved in undertaking and interpreting a meta-analysis. While there are many software tools available for conducting meta-analysis, in the context of a teaching programme such software can require expenditure both in terms of money and in terms of the time it takes to learn how to use it. MetaLight was developed specifically as a tool to facilitate the teaching and learning of meta-analysis and we have presented here some of the ways it might be used in a training situation.

Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.

CellStress - open source image analysis program for single-cell analysis

NASA Astrophysics Data System (ADS)

Smedh, Maria; Beck, Caroline; Sott, Kristin; Goksör, Mattias

2010-08-01

This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimer's or Huntington's disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.

Spacecraft Trajectory Analysis and Mission Planning Simulation (STAMPS) Software

NASA Technical Reports Server (NTRS)

Puckett, Nancy; Pettinger, Kris; Hallstrom,John; Brownfield, Dana; Blinn, Eric; Williams, Frank; Wiuff, Kelli; McCarty, Steve; Ramirez, Daniel; Lamotte, Nicole;

On-Orbit Software Analysis

NASA Technical Reports Server (NTRS)

Moran, Susanne I.

2004-01-01

The On-Orbit Software Analysis Research Infusion Project was done by Intrinsyx Technologies Corporation (Intrinsyx) at the National Aeronautics and Space Administration (NASA) Ames Research Center (ARC). The Project was a joint collaborative effort between NASA Codes IC and SL, Kestrel Technology (Kestrel), and Intrinsyx. The primary objectives of the Project were: Discovery and verification of software program properties and dependencies, Detection and isolation of software defects across different versions of software, and Compilation of historical data and technical expertise for future applications

An overview of the mathematical and statistical analysis component of RICIS

NASA Technical Reports Server (NTRS)

Hallum, Cecil R.

1987-01-01

Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.

Identification of Differentially Expressed miRNAs between White and Black Hair Follicles by RNA-Sequencing in the Goat (Capra hircus)

PubMed Central

Wu, Zhenyang; Fu, Yuhua; Cao, Jianhua; Yu, Mei; Tang, Xiaohui; Zhao, Shuhong

2014-01-01

MicroRNAs (miRNAs) play a key role in many biological processes by regulating gene expression at the post-transcriptional level. A number of miRNAs have been identified from livestock species. However, compared with other animals, such as pigs and cows, the number of miRNAs identified in goats is quite low, particularly in hair follicles. In this study, to investigate the functional roles of miRNAs in goat hair follicles of goats with different coat colors, we sequenced miRNAs from two hair follicles samples (white and black) using Solexa sequencing. A total of 35,604,016 reads were obtained, which included 30,878,637 clean reads (86.73%). MiRDeep2 software identified 214 miRNAs. Among them, 205 were conserved among species and nine were novel miRNAs. Furthermore, DESeq software identified six differentially expressed miRNAs. Quantitative PCR confirmed differential expression of two miRNAs, miR-10b and miR-211. KEGG pathways were analyzed using the DAVID website for the predicted target genes of the differentially expressed miRNAs. Several signaling pathways including Notch and MAPK pathways may affect the process of coat color formation. Our study showed that the identified miRNAs might play an essential role in black and white follicle formation in goats. PMID:24879525

How Safe Is Control Software

NASA Technical Reports Server (NTRS)

Dunn, William R.; Corliss, Lloyd D.

1991-01-01

Paper examines issue of software safety. Presents four case histories of software-safety analysis. Concludes that, to be safe, software, for all practical purposes, must be free of errors. Backup systems still needed to prevent catastrophic software failures.

Design and implementation of software for automated quality control and data analysis for a complex LC/MS/MS assay for urine opiates and metabolites.

PubMed

Dickerson, Jane A; Schmeling, Michael; Hoofnagle, Andrew N; Hoffman, Noah G

2013-01-16

Mass spectrometry provides a powerful platform for performing quantitative, multiplexed assays in the clinical laboratory, but at the cost of increased complexity of analysis and quality assurance calculations compared to other methodologies. Here we describe the design and implementation of a software application that performs quality control calculations for a complex, multiplexed, mass spectrometric analysis of opioids and opioid metabolites. The development and implementation of this application improved our data analysis and quality assurance processes in several ways. First, use of the software significantly improved the procedural consistency for performing quality control calculations. Second, it reduced the amount of time technologists spent preparing and reviewing the data, saving on average over four hours per run, and in some cases improving turnaround time by a day. Third, it provides a mechanism for coupling procedural and software changes with the results of each analysis. We describe several key details of the implementation including the use of version control software and automated unit tests. These generally useful software engineering principles should be considered for any software development project in the clinical lab. Copyright © 2012 Elsevier B.V. All rights reserved.

Software system safety

NASA Technical Reports Server (NTRS)

Uber, James G.

1988-01-01

Software itself is not hazardous, but since software and hardware share common interfaces there is an opportunity for software to create hazards. Further, these software systems are complex, and proven methods for the design, analysis, and measurement of software safety are not yet available. Some past software failures, future NASA software trends, software engineering methods, and tools and techniques for various software safety analyses are reviewed. Recommendations to NASA are made based on this review.

Space station software reliability analysis based on failures observed during testing at the multisystem integration facility

NASA Technical Reports Server (NTRS)

Tamayo, Tak Chai

1987-01-01

Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented.

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.

Analysis of a hardware and software fault tolerant processor for critical applications

NASA Technical Reports Server (NTRS)

Dugan, Joanne B.

1993-01-01

Computer systems for critical applications must be designed to tolerate software faults as well as hardware faults. A unified approach to tolerating hardware and software faults is characterized by classifying faults in terms of duration (transient or permanent) rather than source (hardware or software). Errors arising from transient faults can be handled through masking or voting, but errors arising from permanent faults require system reconfiguration to bypass the failed component. Most errors which are caused by software faults can be considered transient, in that they are input-dependent. Software faults are triggered by a particular set of inputs. Quantitative dependability analysis of systems which exhibit a unified approach to fault tolerance can be performed by a hierarchical combination of fault tree and Markov models. A methodology for analyzing hardware and software fault tolerant systems is applied to the analysis of a hypothetical system, loosely based on the Fault Tolerant Parallel Processor. The models consider both transient and permanent faults, hardware and software faults, independent and related software faults, automatic recovery, and reconfiguration.

Biocharts: a visual formalism for complex biological systems

PubMed Central

Kugler, Hillel; Larjo, Antti; Harel, David

2010-01-01

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis. PMID:20022895

Managing nuclear power plant induced disasters.

PubMed

Kyne, Dean

2015-01-01

To understand the management process of nuclear power plant (NPP) induced disasters. The study shields light on phases and issues associated with the NPP induced disaster management. This study uses Palo Verde Nuclear Generation Station as study subject and Arizona State as study area. This study uses the Radiological Assessment System for Consequence Analysis (RASCAL) Source Term to Dose (STDose) of the Nuclear Regulatory Commission, a computer software to project and assess the source term dose and release pathway. This study also uses ArcGIS, a geographic information system to analyze geospatial data. A detailed case study of Palo Verde Nuclear Power Generation (PVNPG) Plant was conducted. The findings reveal that the NPP induced disaster management process is conducted by various stakeholders. To save lives and to minimize the impacts, it is vital to relate planning and process of the disaster management. Number of people who expose to the radioactive plume pathway and level of radioactivity could vary depending on the speed and direction of wind on the day the event takes place. This study findings show that there is a need to address the burning issue of different racial and ethnic groups' unequal exposure and unequal protection to potential risks associated with the NPPs.

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

State-of-the-Art Resources (SOAR) for Software Vulnerability Detection, Test, and Evaluation

DTIC Science & Technology

2014-07-01

preclude in-depth analysis, and widespread use of a Software -as-a- Service ( SaaS ) model that limits data availability and application to DoD systems...provide mobile application analysis using a Software - as-a- Service ( SaaS ) model. In this case, any software to be analyzed must be sent to the...tools are only available through a SaaS model. The widespread use of a Software -as-a- Service ( SaaS ) model as a sole evaluation model limits data

A Method for Populating the Knowledge Base of AFIT’s Domain-Oriented Application Composition System

DTIC Science & Technology

1993-12-01

Analysis ( FODA ). The approach identifies prominent features (similarities) and distinctive features (differences) of software systems within an... analysis approaches we have summarized, the re- searchers described FODA in sufficient detail to use on large domain analysis projects (ones with...Software Technology Center, July 1991. 18. Kang, Kyo C. and others. Feature-Oriented Domain Analysis ( FODA ) Feasibility Study. Technical Report, Software

Selection of software for mechanical engineering undergraduates

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

Cheah, C. T.; Yin, C. S.; Halim, T.

A major problem with the undergraduate mechanical course is the limited exposure of students to software packages coupled with the long learning curve on the existing software packages. This work proposes the use of appropriate software packages for the entire mechanical engineering curriculum to ensure students get sufficient exposure real life design problems. A variety of software packages are highlighted as being suitable for undergraduate work in mechanical engineering, e.g. simultaneous non-linear equations; uncertainty analysis; 3-D modeling software with the FEA; analysis tools for the solution of problems in thermodynamics, fluid mechanics, mechanical system design, and solid mechanics.

A Case Study of Measuring Process Risk for Early Insights into Software Safety

NASA Technical Reports Server (NTRS)

Layman, Lucas; Basili, Victor; Zelkowitz, Marvin V.; Fisher, Karen L.

2011-01-01

In this case study, we examine software safety risk in three flight hardware systems in NASA's Constellation spaceflight program. We applied our Technical and Process Risk Measurement (TPRM) methodology to the Constellation hazard analysis process to quantify the technical and process risks involving software safety in the early design phase of these projects. We analyzed 154 hazard reports and collected metrics to measure the prevalence of software in hazards and the specificity of descriptions of software causes of hazardous conditions. We found that 49-70% of 154 hazardous conditions could be caused by software or software was involved in the prevention of the hazardous condition. We also found that 12-17% of the 2013 hazard causes involved software, and that 23-29% of all causes had a software control. The application of the TPRM methodology identified process risks in the application of the hazard analysis process itself that may lead to software safety risk.

Knowledge and utilization of computer-software for statistics among Nigerian dentists.

PubMed

Chukwuneke, F N; Anyanechi, C E; Obiakor, A O; Amobi, O; Onyejiaka, N; Alamba, I

2013-01-01

The use of computer soft ware for generation of statistic analysis has transformed health information and data to simplest form in the areas of access, storage, retrieval and analysis in the field of research. This survey therefore was carried out to assess the level of knowledge and utilization of computer software for statistical analysis among dental researchers in eastern Nigeria. Questionnaires on the use of computer software for statistical analysis were randomly distributed to 65 practicing dental surgeons of above 5 years experience in the tertiary academic hospitals in eastern Nigeria. The focus was on: years of clinical experience; research work experience; knowledge and application of computer generated software for data processing and stastistical analysis. Sixty-two (62/65; 95.4%) of these questionnaires were returned anonymously, which were used in our data analysis. Twenty-nine (29/62; 46.8%) respondents fall within those with 5-10 years of clinical experience out of which none has completed the specialist training programme. Practitioners with above 10 years clinical experiences were 33 (33/62; 53.2%) out of which 15 (15/33; 45.5%) are specialists representing 24.2% (15/62) of the total number of respondents. All the 15 specialists are actively involved in research activities and only five (5/15; 33.3%) can utilize software statistical analysis unaided. This study has i dentified poor utilization of computer software for statistic analysis among dental researchers in eastern Nigeria. This is strongly associated with lack of exposure on the use of these software early enough especially during the undergraduate training. This call for introduction of computer training programme in dental curriculum to enable practitioners develops the attitude of using computer software for their research.

Melanie II--a third-generation software package for analysis of two-dimensional electrophoresis images: I. Features and user interface.

PubMed

Appel, R D; Palagi, P M; Walther, D; Vargas, J R; Sanchez, J C; Ravier, F; Pasquali, C; Hochstrasser, D F

1997-12-01

Although two-dimensional electrophoresis (2-DE) computer analysis software packages have existed ever since 2-DE technology was developed, it is only now that the hardware and software technology allows large-scale studies to be performed on low-cost personal computers or workstations, and that setting up a 2-DE computer analysis system in a small laboratory is no longer considered a luxury. After a first attempt in the seventies and early eighties to develop 2-DE analysis software systems on hardware that had poor or even no graphical capabilities, followed in the late eighties by a wave of innovative software developments that were possible thanks to new graphical interface standards such as XWindows, a third generation of 2-DE analysis software packages has now come to maturity. It can be run on a variety of low-cost, general-purpose personal computers, thus making the purchase of a 2-DE analysis system easily attainable for even the smallest laboratory that is involved in proteome research. Melanie II 2-D PAGE, developed at the University Hospital of Geneva, is such a third-generation software system for 2-DE analysis. Based on unique image processing algorithms, this user-friendly object-oriented software package runs on multiple platforms, including Unix, MS-Windows 95 and NT, and Power Macintosh. It provides efficient spot detection and quantitation, state-of-the-art image comparison, statistical data analysis facilities, and is Internet-ready. Linked to proteome databases such as those available on the World Wide Web, it represents a valuable tool for the "Virtual Lab" of the post-genome area.

FunRich proteomics software analysis, let the fun begin!

PubMed

Benito-Martin, Alberto; Peinado, Héctor

2015-08-01

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small-scale and high-throughput studies. However, user-friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597-2601) report the development of FunRich software, an open-access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions

PubMed Central

Hucka, Michael; Bergmann, Frank T.; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M.; Le Novére, Nicolas; Myers, Chris J.; Olivier, Brett G.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Waltemath, Dagmar; Wilkinson, Darren J.

2017-01-01

Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/. PMID:26528569

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core

PubMed Central

Hucka, Michael; Bergmann, Frank T.; Hoops, Stefan; Keating, Sarah M.; Sahle, Sven; Schaff, James C.; Smith, Lucian P.; Wilkinson, Darren J.

2017-01-01

Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/. PMID:26528564

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions.

PubMed

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2015-09-04

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.

PubMed

Hucka, Michael; Bergmann, Frank T; Hoops, Stefan; Keating, Sarah M; Sahle, Sven; Schaff, James C; Smith, Lucian P; Wilkinson, Darren J

2015-09-04

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.

PubMed

Hucka, Michael; Bergmann, Frank T; Hoops, Stefan; Keating, Sarah M; Sahle, Sven; Schaff, James C; Smith, Lucian P; Wilkinson, Darren J

2015-06-01

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions.

PubMed

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2015-06-01

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions

PubMed Central

2010-01-01

Background Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. Description We describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. Conclusions BiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu. PMID:20426874

multiplierz v2.0: A Python-based ecosystem for shared access and analysis of native mass spectrometry data.

PubMed

Alexander, William M; Ficarro, Scott B; Adelmant, Guillaume; Marto, Jarrod A

2017-08-01

The continued evolution of modern mass spectrometry instrumentation and associated methods represents a critical component in efforts to decipher the molecular mechanisms which underlie normal physiology and understand how dysregulation of biological pathways contributes to human disease. The increasing scale of these experiments combined with the technological diversity of mass spectrometers presents several challenges for community-wide data access, analysis, and distribution. Here we detail a redesigned version of multiplierz, our Python software library which leverages our common application programming interface (mzAPI) for analysis and distribution of proteomic data. New features include support for a wider range of native mass spectrometry file types, interfaces to additional database search engines, compatibility with new reporting formats, and high-level tools to perform post-search proteomic analyses. A GUI desktop environment, mzDesktop, provides access to multiplierz functionality through a user friendly interface. multiplierz is available for download from: https://github.com/BlaisProteomics/multiplierz; and mzDesktop is available for download from: https://sourceforge.net/projects/multiplierz/. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Imaging C. elegans embryos using an epifluorescent microscope and open source software.

PubMed

Verbrugghe, Koen J C; Chan, Raymond C

2011-03-24

Cellular processes, such as chromosome assembly, segregation and cytokinesis,are inherently dynamic. Time-lapse imaging of living cells, using fluorescent-labeled reporter proteins or differential interference contrast (DIC) microscopy, allows for the examination of the temporal progression of these dynamic events which is otherwise inferred from analysis of fixed samples(1,2). Moreover, the study of the developmental regulations of cellular processes necessitates conducting time-lapse experiments on an intact organism during development. The Caenorhabiditis elegans embryo is light-transparent and has a rapid, invariant developmental program with a known cell lineage(3), thus providing an ideal experiment model for studying questions in cell biology(4,5)and development(6-9). C. elegans is amendable to genetic manipulation by forward genetics (based on random mutagenesis(10,11)) and reverse genetics to target specific genes (based on RNAi-mediated interference and targeted mutagenesis(12-15)). In addition, transgenic animals can be readily created to express fluorescently tagged proteins or reporters(16,17). These traits combine to make it easy to identify the genetic pathways regulating fundamental cellular and developmental processes in vivo(18-21). In this protocol we present methods for live imaging of C. elegans embryos using DIC optics or GFP fluorescence on a compound epifluorescent microscope. We demonstrate the ease with which readily available microscopes, typically used for fixed sample imaging, can also be applied for time-lapse analysis using open-source software to automate the imaging process.

MPFit: Computational Tool for Predicting Moonlighting Proteins.

PubMed

Khan, Ishita; McGraw, Joshua; Kihara, Daisuke

2017-01-01

An increasing number of proteins have been found which are capable of performing two or more distinct functions. These proteins, known as moonlighting proteins, have drawn much attention recently as they may play critical roles in disease pathways and development. However, because moonlighting proteins are often found serendipitously, our understanding of moonlighting proteins is still quite limited. In order to lay the foundation for systematic moonlighting proteins studies, we developed MPFit, a software package for predicting moonlighting proteins from their omics features including protein-protein and gene interaction networks. Here, we describe and demonstrate the algorithm of MPFit, the idea behind it, and provide instruction for using the software.

Lipidomics study of plasma phospholipid metabolism in early type 2 diabetes rats with ancient prescription Huang-Qi-San intervention by UPLC/Q-TOF-MS and correlation coefficient.

PubMed

Wu, Xia; Zhu, Jian-Cheng; Zhang, Yu; Li, Wei-Min; Rong, Xiang-Lu; Feng, Yi-Fan

2016-08-25

Potential impact of lipid research has been increasingly realized both in disease treatment and prevention. An effective metabolomics approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS) along with multivariate statistic analysis has been applied for investigating the dynamic change of plasma phospholipids compositions in early type 2 diabetic rats after the treatment of an ancient prescription of Chinese Medicine Huang-Qi-San. The exported UPLC/Q-TOF-MS data of plasma samples were subjected to SIMCA-P and processed by bioMark, mixOmics, Rcomdr packages with R software. A clear score plots of plasma sample groups, including normal control group (NC), model group (MC), positive medicine control group (Flu) and Huang-Qi-San group (HQS), were achieved by principal-components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Biomarkers were screened out using student T test, principal component regression (PCR), partial least-squares regression (PLS) and important variable method (variable influence on projection, VIP). Structures of metabolites were identified and metabolic pathways were deduced by correlation coefficient. The relationship between compounds was explained by the correlation coefficient diagram, and the metabolic differences between similar compounds were illustrated. Based on KEGG database, the biological significances of identified biomarkers were described. The correlation coefficient was firstly applied to identify the structure and deduce the metabolic pathways of phospholipids metabolites, and the study provided a new methodological cue for further understanding the molecular mechanisms of metabolites in the process of regulating Huang-Qi-San for treating early type 2 diabetes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Reference Model for Software and System Inspections. White Paper

NASA Technical Reports Server (NTRS)

He, Lulu; Shull, Forrest

2009-01-01

Software Quality Assurance (SQA) is an important component of the software development process. SQA processes provide assurance that the software products and processes in the project life cycle conform to their specified requirements by planning, enacting, and performing a set of activities to provide adequate confidence that quality is being built into the software. Typical techniques include: (1) Testing (2) Simulation (3) Model checking (4) Symbolic execution (5) Management reviews (6) Technical reviews (7) Inspections (8) Walk-throughs (9) Audits (10) Analysis (complexity analysis, control flow analysis, algorithmic analysis) (11) Formal method Our work over the last few years has resulted in substantial knowledge about SQA techniques, especially the areas of technical reviews and inspections. But can we apply the same QA techniques to the system development process? If yes, what kind of tailoring do we need before applying them in the system engineering context? If not, what types of QA techniques are actually used at system level? And, is there any room for improvement.) After a brief examination of the system engineering literature (especially focused on NASA and DoD guidance) we found that: (1) System and software development process interact with each other at different phases through development life cycle (2) Reviews are emphasized in both system and software development. (Figl.3). For some reviews (e.g. SRR, PDR, CDR), there are both system versions and software versions. (3) Analysis techniques are emphasized (e.g. Fault Tree Analysis, Preliminary Hazard Analysis) and some details are given about how to apply them. (4) Reviews are expected to use the outputs of the analysis techniques. In other words, these particular analyses are usually conducted in preparation for (before) reviews. The goal of our work is to explore the interaction between the Quality Assurance (QA) techniques at the system level and the software level.

Web-based applications for building, managing and analysing kinetic models of biological systems.

PubMed

Lee, Dong-Yup; Saha, Rajib; Yusufi, Faraaz Noor Khan; Park, Wonjun; Karimi, Iftekhar A

2009-01-01

Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.

Disulfide proteomics of rice cultured cells in response to OsRacl and probenazole-related immune signaling pathway in rice.

PubMed

Morino, Kazuko; Kimizu, Mayumi; Fujiwara, Masayuki

2016-01-01

Reactive oxygen species (ROS) production is an early event in the immune response of plants. ROS production affects the redox-based modification of cysteine residues in redox proteins, which contribute to protein functions such as enzymatic activity, protein-protein interactions, oligomerization, and intracellular localization. Thus, the sensitivity of cysteine residues to changes in the cellular redox status is critical to the immune response of plants. We used disulfide proteomics to identify immune response-related redox proteins. Total protein was extracted from rice cultured cells expressing constitutively active or dominant-negative OsRacl, which is a key regulator of the immune response in rice, and from rice cultured cells that were treated with probenazole, which is an activator of the plant immune response, in the presence of the thiol group-specific fluorescent probe monobromobimane (mBBr), which was a tag for reduced proteins in a differential display two-dimensional gel electrophoresis. The mBBr fluorescence was detected by using a charge-coupled device system, and total protein spots were detected using Coomassie brilliant blue staining. Both of the protein spots were analyzed by gel image software and identified using MS spectrometry. The possible disulfide bonds were identified using the disulfide bond prediction software. Subcellular localization and bimolecular fluorescence complementation analysis were performed in one of the identified proteins: Oryza sativa cold shock protein 2 (OsCSP2). We identified seven proteins carrying potential redox-sensitive cysteine residues. Two proteins of them were oxidized in cultured cells expressing DN-OsRac1, which indicates that these two proteins would be inactivated through the inhibition of OsRac1 signaling pathway. One of the two oxidized proteins, OsCSP2, contains 197 amino acid residues and six cysteine residues. Site-directed mutagenesis of these cysteine residues revealed that a Cys 140 mutation causes mislocalization of a green fluorescent protein fusion protein in the root cells of rice. Bimolecular fluorescence complementation analysis revealed that OsCSP2 is localized in the nucleus as a homo dimer in rice root cells. The findings of the study indicate that redox-sensitive cysteine modification would contribute to the immune response in rice.

Molecular mechanisms of pathogenesis in hepatocellular carcinoma revealed by RNA‑sequencing.

PubMed

Liu, Yao; Yang, Zhe; Du, Feng; Yang, Qiao; Hou, Jie; Yan, Xiaohong; Geng, Yi; Zhao, Yaning; Wang, Hua

2017-11-01

The present study aimed to explore the underlying molecular mechanisms of hepatocellular carcinoma (HCC). RNA‑sequencing profiles GSM629264 and GSM629265, from the GSE25599 data set, were downloaded from the Gene Expression Omnibus database and processed by quality evaluation. GSM629264 and GSM629265 were from HCC and adjacent non‑cancerous tissues, respectively. TopHat software was used for alignment analysis, followed by the detection of novel splicing sites. In addition, the Cufflinks software package was used to analyze gene expressions, and the Cuffdiff program was used to screen for differently expressed genes (DEGs) and differentially expressed splicing variants. Gene ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs were also performed. Transcription factors (TFs) and microRNAs (miRNAs) that regulate DEGs were identified, and a protein‑protein interaction (PPI) network was constructed. The hub node in the PPI network was obtained, and the TFs and miRNAs that regulated the hub node were further predicted. The quality of the sequencing data met the standards for analysis, and the clean reads were ~65%. Most sequencing reads mapped into coding sequence exons (CDS_exons), whereas other reads mapped into exon 3' untranslated regions (UTR_Exons), 5'UTR_Exons and Introns. Upregulated and downregulated DEGs between HCC and adjacent non‑cancerous tissues were screened. Genes of differentially expressed splicing variants were identified, including vesicle‑associated membrane protein 4, phosphatidylinositol glycan anchor biosynthesis class C, protein disulfide isomerase family A member 4 and growth arrest specific 5. Screened DEGs were enriched in the complement pathway. In the PPI network, ubiquitin C (UBC) was the hub node. UBC was predicted to be regulated by several TFs, including specificity protein 1 (SP1), FBJ murine osteosarcoma viral oncogene homolog (FOS), proto‑oncogene c‑JUN (JUN), FOS‑like antigen 2 (FOSL2) and SWI/SNF‑related, matrix‑associated, actin‑dependent regulator of chromatin, subfamily A, member 4 (SMARCA4), and several miRNAs, including miR‑30 and miR‑181. Results from the present study demonstrated that UBC, SP1, FOS, JUN, FOSL2, SMARCA4, miR‑30 and miR‑181 may participate in the development of HCC.

Standardizing Activation Analysis: New Software for Photon Activation Analysis

NASA Astrophysics Data System (ADS)

Sun, Z. J.; Wells, D.; Segebade, C.; Green, J.

2011-06-01

Photon Activation Analysis (PAA) of environmental, archaeological and industrial samples requires extensive data analysis that is susceptible to error. For the purpose of saving time, manpower and minimizing error, a computer program was designed, built and implemented using SQL, Access 2007 and asp.net technology to automate this process. Based on the peak information of the spectrum and assisted by its PAA library, the program automatically identifies elements in the samples and calculates their concentrations and respective uncertainties. The software also could be operated in browser/server mode, which gives the possibility to use it anywhere the internet is accessible. By switching the nuclide library and the related formula behind, the new software can be easily expanded to neutron activation analysis (NAA), charged particle activation analysis (CPAA) or proton-induced X-ray emission (PIXE). Implementation of this would standardize the analysis of nuclear activation data. Results from this software were compared to standard PAA analysis with excellent agreement. With minimum input from the user, the software has proven to be fast, user-friendly and reliable.

Second Generation Product Line Engineering Takes Hold in the DoD

DTIC Science & Technology

2014-01-01

Feature- Oriented Domain Analysis ( FODA ) Feasibility Study” (CMU/SEI-90- TR-021, ADA235785). Pittsburgh, PA: Software Engineering Institute...software product line engineering and software architecture documentation and analysis . Clements is co-author of three practitioner-oriented books about

An active learning approach for rapid characterization of endothelial cells in human tumors.

PubMed

Padmanabhan, Raghav K; Somasundar, Vinay H; Griffith, Sandra D; Zhu, Jianliang; Samoyedny, Drew; Tan, Kay See; Hu, Jiahao; Liao, Xuejun; Carin, Lawrence; Yoon, Sam S; Flaherty, Keith T; Dipaola, Robert S; Heitjan, Daniel F; Lal, Priti; Feldman, Michael D; Roysam, Badrinath; Lee, William M F

2014-01-01

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

Proteomic Analysis of Matched Formalin-Fixed, Paraffin-Embedded Specimens in Patients with Advanced Serous Ovarian Carcinoma

PubMed Central

Smith, Ashlee L.; Sun, Mai; Bhargava, Rohit; Stewart, Nicolas A.; Flint, Melanie S.; Bigbee, William L.; Krivak, Thomas C.; Strange, Mary A.; Cooper, Kristine L.; Zorn, Kristin K.

2013-01-01

Objective: The biology of high grade serous ovarian carcinoma (HGSOC) is poorly understood. Little has been reported on intratumoral homogeneity or heterogeneity of primary HGSOC tumors and their metastases. We evaluated the global protein expression profiles of paired primary and metastatic HGSOC from formalin-fixed, paraffin-embedded (FFPE) tissue samples. Methods: After IRB approval, six patients with advanced HGSOC were identified with tumor in both ovaries at initial surgery. Laser capture microdissection (LCM) was used to extract tumor for protein digestion. Peptides were extracted and analyzed by reversed-phase liquid chromatography coupled to a linear ion trap mass spectrometer. Tandem mass spectra were searched against the UniProt human protein database. Differences in protein abundance between samples were assessed and analyzed by Ingenuity Pathway Analysis software. Immunohistochemistry (IHC) for select proteins from the original and an additional validation set of five patients was performed. Results: Unsupervised clustering of the abundance profiles placed the paired specimens adjacent to each other. IHC H-score analysis of the validation set revealed a strong correlation between paired samples for all proteins. For the similarly expressed proteins, the estimated correlation coefficients in two of three experimental samples and all validation samples were statistically significant (p < 0.05). The estimated correlation coefficients in the experimental sample proteins classified as differentially expressed were not statistically significant. Conclusion: A global proteomic screen of primary HGSOC tumors and their metastatic lesions identifies tumoral homogeneity and heterogeneity and provides preliminary insight into these protein profiles and the cellular pathways they constitute. PMID:28250404

[Molecular cloning, expression and characterization of lysine decarboxylase gene of endophytic fungus Shiraia sp. Slf14 from Huperzia serrata].

PubMed

Peng, Silu; Yang, Huilin; Zhu, Du; Zhang, Zhibin; Yan, Riming; Wang, Ya

2016-04-14

Huperzine A (HupA) was approved as a drug for the treatment of Alzheimer's disease. The HupA biosynthetic pathway was started from lysine decarboxylase (LDC), which catalyzes lysine to cadaverine. In this study, we cloned and expressed an LDC gene from a HupA-producing endophytic fungus, and tested LDC activities. An endophytic fungus Shiraia sp. Slf14 from Huperzia serrata was used. LDC gene was obtained by RT-PCR, and cloned into pET-22b(+) and pET-32a(+) vectors to construct recombinant plasmids pET- 22b-LDC and pET-32a-LDC. These two recombinant plasmids were transformed into E. coli BL21, cultured for 8 h at 24 °C, 200 r/min with 1×10–3 mol/L IPTG into medium to express the LDC proteins, respectively. LDC proteins were purified by Ni2+ affinity chromatography. Catalytic activities were measured by Thin Layer Chromatography. At last, the physicochemical properties and structures of these two LDCs were obtained by bioinformatics software. LDC and Trx-LDC were expressed in E. coli BL21 successfully. SDS-PAGE analysis shows that the molecular weight of LDC and Trx-LDC were 24.4 kDa and 42.7 kDa respectively, which are consistent with bioinformatics analysis. In addition, TLC analysis reveals that both LDC and Trx-LDC had catalytic abilities. This work can provide fundamental data for enriching LDC molecular information and reveal the HupA biosynthetic pathway in endophytic fungi.

Comparison of gene expression profiles between dental pulp and periodontal ligament tissues in humans

PubMed Central

Gong, Ai-Xiu; Zhang, Jing-Han; Li, Jing; Wu, Jun; Wang, Lin; Miao, Deng-Shun

2017-01-01

There are anatomical and functional differences between human dental pulp (DP) and periodontal ligament (PDL). However, the molecular biological differences and function of these tissues are poorly understood. In the present study, we employed a cDNA microarray array to screen for differentially expressed genes (DEGs) between human DP and PDL tissues, and used the online software WebGestalt to perform the functional analysis of the DEGs. In addition, the STRING database and KEGG pathway analysis were applied for interaction network and pathway analysis of the DEGs. DP and PDL samples were obtained from permanent premolars (n=16) extracted for orthodontic purposes. The results of the microarray assay were confirmed by RT-qPCR. The DEGs were found to be significantly associated with the extracellular matrix and focal adhesion. A total of 10 genes were selected to confirm the results. The mRNA levels of integrin alpha 4 (ITGA4), integrin alpha 8 (ITGA8), neurexin 1 (NRXN1) and contactin 1 (CNTN1) were significantly higher in the DP than in the PDL tissues. However, the levels of collagen type XI alpha 1 (COL11A1), aggrecan (ACAN), collagen type VI alpha 1 (COL6A1), chondroadherin (CHAD), laminin gamma 2 (LAMC2) and laminin alpha 3 (LAMA3) were higher in the PDL than in the DP samples. The gene expression profiles provide novel insight into the characterization of DP and PDL tissues, and contribute to our understanding of the potential molecular mechanisms of dental tissue mineralization and regeneration. PMID:28713908

The Holistic Targeting (HOT) Methodology as the Means to Improve Information Operations (IO) Target Development and Prioritization

DTIC Science & Technology

2008-09-01

software facilitate targeting problem understanding and the network analysis tool, Palantir , as an efficient and tailored semi-automated means to...the use of compendium software facilitate targeting problem understanding and the network analysis tool, Palantir , as an efficient and tailored semi...OBJECTIVES USING COMPENDIUM SOFTWARE .....63 E. HOT TARGET PRIORITIZATION AND DEVELOPMENT USING PALANTIR SOFTWARE .................................69 1

Software Defined Network Monitoring Scheme Using Spectral Graph Theory and Phantom Nodes

DTIC Science & Technology

2014-09-01

networks is the emergence of software - defined networking ( SDN ) [1]. SDN has existed for the...Chapter III for network monitoring. A. SOFTWARE DEFINED NETWORKS SDNs provide a new and innovative method to simplify network hardware by logically...and R. Giladi, “Performance analysis of software - defined networking ( SDN ),” in Proc. of IEEE 21st International Symposium on Modeling, Analysis

Proteomics and bioinformatics analysis of altered protein expression in the placental villous tissue from early recurrent miscarriage patients.

PubMed

Pan, Hai-Tao; Ding, Hai-Gang; Fang, Min; Yu, Bin; Cheng, Yi; Tan, Ya-Jing; Fu, Qi-Qin; Lu, Bo; Cai, Hong-Guang; Jin, Xin; Xia, Xian-Qing; Zhang, Tao

2018-01-01

Recurrent miscarriage (RM) affects 5% of women, it has an adverse emotional impact on women. Because of the complexities of early development, the mechanism of recurrent miscarriage is still unclear. We hypothesized that abnormal placenta leads to early recurrent miscarriage (ERM). The aim of this study was to identify ERM associated factors in human placenta villous tissue using proteomics. Investigation of these differences in protein expression in parallel profiling is essential to understand the comprehensive pathophysiological mechanism underlying recurrent miscarriage (RM). To gain more insight into mechanisms of recurrent miscarriage (RM), a comparative proteome profile of the human placenta villous tissue in normal and RM pregnancies was analyzed using iTRAQ technology and bioinformatics analysis used by Ingenuity Pathway Analysis (IPA) software. In this study, we employed an iTRAQ based proteomics analysis of four placental villous tissues from patients with early recurrent miscarriage (ERM) and four from normal pregnant women. Finally, we identified 2805 proteins and 79,998 peptides between patients with RM and normal matched group. Further analysis identified 314 differentially expressed proteins in placental villous tissue (≥1.3-fold, Student's t-test, p < 0.05); 209 proteins showed the increased expression while 105 proteins showed decreased expression. These 314 proteins were analyzed by Ingenuity Pathway Analysis (IPA) and were found to play important roles in the growth of embryo. Furthermore, network analysis show that Angiotensinogen (AGT), MAPK14 and Prothrombin (F2) are core factors in early embryonic development. We used another 8 independent samples (4 cases and 4 controls) to cross validation of the proteomic data. This study has identified several proteins that are associated with early development, these results may supply new insight into mechanisms behind recurrent miscarriage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of new vibration energy flow analysis software and its applications to vehicle systems

NASA Astrophysics Data System (ADS)

Kim, D.-J.; Hong, S.-Y.; Park, Y.-H.

2005-09-01

The Energy flow analysis (EFA) offers very promising results in predicting the noise and vibration responses of system structures in medium-to-high frequency ranges. We have developed the Energy flow finite element method (EFFEM) based software, EFADSC++ R4, for the vibration analysis. The software can analyze the system structures composed of beam, plate, spring-damper, rigid body elements and many other components developed, and has many useful functions in analysis. For convenient use of the software, the main functions of the whole software are modularized into translator, model-converter, and solver. The translator module makes it possible to use finite element (FE) model for the vibration analysis. The model-converter module changes FE model into energy flow finite element (EFFE) model, and generates joint elements to cover the vibrational attenuation in the complex structures composed of various elements and can solve the joint element equations by using the wave tra! nsmission approach very quickly. The solver module supports the various direct and iterative solvers for multi-DOF structures. The predictions of vibration for real vehicles by using the developed software were performed successfully.

The Implication of Using NVivo Software in Qualitative Data Analysis: Evidence-Based Reflections.

PubMed

Zamawe, F C

2015-03-01

For a long time, electronic data analysis has been associated with quantitative methods. However, Computer Assisted Qualitative Data Analysis Software (CAQDAS) are increasingly being developed. Although the CAQDAS has been there for decades, very few qualitative health researchers report using it. This may be due to the difficulties that one has to go through to master the software and the misconceptions that are associated with using CAQDAS. While the issue of mastering CAQDAS has received ample attention, little has been done to address the misconceptions associated with CAQDAS. In this paper, the author reflects on his experience of interacting with one of the popular CAQDAS (NVivo) in order to provide evidence-based implications of using the software. The key message is that unlike statistical software, the main function of CAQDAS is not to analyse data but rather to aid the analysis process, which the researcher must always remain in control of. In other words, researchers must equally know that no software can analyse qualitative data. CAQDAS are basically data management packages, which support the researcher during analysis.

Description of the GMAO OSSE for Weather Analysis Software Package: Version 3

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Errico, Ronald M.; Prive, Nikki C.; Carvalho, David; Sienkiewicz, Meta; El Akkraoui, Amal; Guo, Jing; Todling, Ricardo; McCarty, Will; Putman, William M.;

Creation of a Genome-Wide Metabolic Pathway Database for Populus trichocarpa Using a New Approach for Reconstruction and Curation of Metabolic Pathways for Plants1[W][OA

PubMed Central

Zhang, Peifen; Dreher, Kate; Karthikeyan, A.; Chi, Anjo; Pujar, Anuradha; Caspi, Ron; Karp, Peter; Kirkup, Vanessa; Latendresse, Mario; Lee, Cynthia; Mueller, Lukas A.; Muller, Robert; Rhee, Seung Yon

2010-01-01

Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http://plantcyc.org). PMID:20522724

Analytical and Methodological Issues in the Use of Qualitative Data Analysis Software: A Description of Three Studies.

ERIC Educational Resources Information Center

Margerum-Leys, Jon; Kupperman, Jeff; Boyle-Heimann, Kristen

This paper presents perspectives on the use of data analysis software in the process of qualitative research. These perspectives were gained in the conduct of three qualitative research studies that differed in theoretical frames, areas of interests, and scope. Their common use of a particular data analysis software package allows the exploration…

ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes

PubMed Central

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section. PMID:21577273

ElectroMagnetoEncephalography software: overview and integration with other EEG/MEG toolboxes.

PubMed

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section.

Report: Scientific Software.

ERIC Educational Resources Information Center

Borman, Stuart A.

1985-01-01

Discusses various aspects of scientific software, including evaluation and selection of commercial software products; program exchanges, catalogs, and other information sources; major data analysis packages; statistics and chemometrics software; and artificial intelligence. (JN)

Multiscale systems pharmacological analysis of everolimus action in hepatocellular carcinoma.

PubMed

Ande, Anusha; Chaar, Maher; Ait-Oudhia, Sihem

2018-05-03

Dysregulation of mTOR pathway is common in hepatocellular carcinoma (HCC). A translational quantitative systems pharmacology (QSP), pharmacokinetic (PK), and pharmacodynamic (PD) model dissecting the circuitry of this pathway was developed to predict HCC patients' response to everolimus, an mTOR inhibitor. The time course of key signaling proteins in the mTOR pathway, HCC cells viability, tumor volume (TV) and everolimus plasma and tumor concentrations in xenograft mice, clinical PK of everolimus and progression free survival (PFS) in placebo and everolimus-treated patients were extracted from literature. A comprehensive and multiscale QSP/PK/PD model was developed, qualified, and translated to clinical settings. Model fittings and simulations were performed using Monolix software. The S6-kinase protein was identified as critical in the mTOR signaling pathway for describing everolimus lack of efficacy in HCC patients. The net growth rate constant (kg) of HCC cells was estimated at 0.02 h -1 (2.88%RSE). The partition coefficient of everolimus into the tumor (kp) was determined at 0.06 (12.98%RSE). The kg in patients was calculated from the doubling time of TV in naturally progressing HCC patients, and was determined at 0.004 day -1 . Model-predicted and observed PFS were in good agreement for placebo and everolimus-treated patients. In conclusion, a multiscale QSP/PK/PD model elucidating everolimus lack of efficacy in HCC patients was successfully developed and predicted PFS reasonably well compared to observed clinical findings. This model may provide insights into clinical response to everolimus-based therapy and serve as a valuable tool for the clinical translation of efficacy for novel mTOR inhibitors.

Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions

DOE PAGES

Martí-Arbona, Ricardo; Mu, Fangping; Nowak-Lovato, Kristy L.; ...

2014-12-18

In this study, the clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity. software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed,more » we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans, a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018. These studies provide the proof of concept and validation of a systematic approach to the discovery of the biological activity for proteins of unknown function, in this case a TR. Bxe_B3018 is a methylglyoxal responsive TR that controls the expression of an operon composed of a putative efflux system.« less

The chemokine receptor CCR1 is identified in mast cell-derived exosomes

PubMed Central

Liang, Yuting; Qiao, Longwei; Peng, Xia; Cui, Zelin; Yin, Yue; Liao, Huanjin; Jiang, Min; Li, Li

2018-01-01

Mast cells are important effector cells of the immune system, and mast cell-derived exosomes carrying RNAs play a role in immune regulation. However, the molecular function of mast cell-derived exosomes is currently unknown, and here, we identify differentially expressed genes (DEGs) in mast cells and exosomes. We isolated mast cells derived exosomes through differential centrifugation and screened the DEGs from mast cell-derived exosomes, using the GSE25330 array dataset downloaded from the Gene Expression Omnibus database. Biochemical pathways were analyzed by Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the online tool DAVID. DEGs-associated protein-protein interaction networks (PPIs) were constructed using the STRING database and Cytoscape software. The genes identified from these bioinformatics analyses were verified by qRT-PCR and Western blot in mast cells and exosomes. We identified 2121 DEGs (843 up and 1278 down-regulated genes) in HMC-1 cell-derived exosomes and HMC-1 cells. The up-regulated DEGs were classified into two significant modules. The chemokine receptor CCR1 was screened as a hub gene and enriched in cytokine-mediated signaling pathway in module one. Seven genes, including CCR1, CD9, KIT, TGFBR1, TLR9, TPSAB1 and TPSB2 were screened and validated through qRT-PCR analysis. We have achieved a comprehensive view of the pivotal genes and pathways in mast cells and exosomes and identified CCR1 as a hub gene in mast cell-derived exosomes. Our results provide novel clues with respect to the biological processes through which mast cell-derived exosomes modulate immune responses. PMID:29511430

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

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

Yang, Chin-Rang

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complementmore » Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.« less

Transcriptomic analyses and leukocyte telomere length measurement in subjects exposed to severe recent stressful life events.

PubMed

Lopizzo, N; Tosato, S; Begni, V; Tomassi, S; Cattane, N; Barcella, M; Turco, G; Ruggeri, M; Riva, M A; Pariante, C M; Cattaneo, A

2017-02-21

Stressful life events occurring in adulthood have been found able to affect mood and behavior, thus increasing the vulnerability for several stress-related psychiatric disorders. However, although there is plenty of clinical data supporting an association between stressful life events in adulthood and an enhanced vulnerability for psychopathology, the underlying molecular mechanisms are still poorly investigated. Thus, in this study we performed peripheral/whole-genome transcriptomic analyses in blood samples obtained from 53 adult subjects characterized for recent stressful life events occurred within the previous 6 months. Transcriptomic data were analyzed using Partek Genomics Suite; pathway and network analyses were performed using Ingenuity Pathway Analysis and GeneMANIA Software. We found 207 genes significantly differentially expressed in adult subjects who reported recent stressful life experiences (n=21) compared with those without such experiences (n=32). Moreover, the same subjects exposed to such stressful experiences showed a reduction in leukocyte telomere length. A correlation analyses between telomere length and transcriptomic data indicated an association between the exposures to recent stressful life events and the modulation of several pathways, mainly involved in immune-inflammatory-related processes and oxidative stress, such as natural killer cell signaling, interleukin-1 (IL-1) signaling, MIF regulation of innate immunity and IL-6 signaling. Our data suggest an association between exposures to recent stressful life events in adulthood and alterations in the immune, inflammatory and oxidative stress pathways, which could be also involved in the negative effect of stressful life events on leukocyte telomere length. The modulation of these mechanisms may underlie the clinical association between the exposure to recent Stressful life events in adulthood and an enhanced vulnerability to develop psychiatric diseases in adulthood.

Pathway enrichment analysis approach based on topological structure and updated annotation of pathway.

PubMed

Yang, Qian; Wang, Shuyuan; Dai, Enyu; Zhou, Shunheng; Liu, Dianming; Liu, Haizhou; Meng, Qianqian; Jiang, Bin; Jiang, Wei

2017-08-16

Pathway enrichment analysis has been widely used to identify cancer risk pathways, and contributes to elucidating the mechanism of tumorigenesis. However, most of the existing approaches use the outdated pathway information and neglect the complex gene interactions in pathway. Here, we first reviewed the existing widely used pathway enrichment analysis approaches briefly, and then, we proposed a novel topology-based pathway enrichment analysis (TPEA) method, which integrated topological properties and global upstream/downstream positions of genes in pathways. We compared TPEA with four widely used pathway enrichment analysis tools, including database for annotation, visualization and integrated discovery (DAVID), gene set enrichment analysis (GSEA), centrality-based pathway enrichment (CePa) and signaling pathway impact analysis (SPIA), through analyzing six gene expression profiles of three tumor types (colorectal cancer, thyroid cancer and endometrial cancer). As a result, we identified several well-known cancer risk pathways that could not be obtained by the existing tools, and the results of TPEA were more stable than that of the other tools in analyzing different data sets of the same cancer. Ultimately, we developed an R package to implement TPEA, which could online update KEGG pathway information and is available at the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/TPEA/. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

Different effection of p.1125Val>Ala and rs11954856 in APC on Wnt signaling pathway.

PubMed

Li, Fei-Feng; Zhao, Zhi-Xun; Yan, Peng; Wang, Song; Liu, Zheng; Zhang, Qiong; Zhang, Xiao-Ning; Sun, Chang-Hao; Wang, Xi-Shan; Wang, Gui-Yu; Liu, Shu-Lin

2017-09-19

Colorectal cancer (CRC) is among the most common and fatal forms of solid tumors worldwide and more than two thirds of CRC and adenomas patients have APC gene mutations. APC is a key regulator in the Wnt/β-catenin signaling pathway but its roles in CRC remains to be elucidated. In this study, we compared APC genes between CRC patients and controls to determine possible associations of nucleotide changes in the APC gene with the pathways involved in CRC pathogenesis. All participants received physical and enteroscopic examinations. The APC gene was sequenced for 300 Chinese Han CRC patients and 411 normal controls, and the expression levels of genes in the signaling pathway were analyzed using Western Blotting. Statistical analyses were conducted using SPSS (version 19.0) software. We found that rs11954856 in the APC gene was associated with colorectal cancer and could increase the expression levels of APC , β-catenin , TCF7L1 , TCF7L2 and LEF1 genes in the pathway in the CRC patients, demonstrating the involvement of APC in the pathological processes leading to CRC.

Proteomic interactions in the mouse vitreous-retina complex.

PubMed

Skeie, Jessica M; Mahajan, Vinit B

2013-01-01

Human vitreoretinal diseases are due to presumed abnormal mechanical interactions between the vitreous and retina, and translational models are limited. This study determined whether nonstructural proteins and potential retinal biomarkers were expressed by the normal mouse vitreous and retina. Vitreous and retina samples from mice were collected by evisceration and analyzed by liquid chromatography-tandem mass spectrometry. Identified proteins were further analyzed for differential expression and functional interactions using bioinformatic software. We identified 1,680 unique proteins in the retina and 675 unique proteins in the vitreous. Unbiased clustering identified protein pathways that distinguish retina from vitreous including oxidative phosphorylation and neurofilament cytoskeletal remodeling, whereas the vitreous expressed oxidative stress and innate immunology pathways. Some intracellular protein pathways were found in both retina and vitreous, such as glycolysis and gluconeogenesis and neuronal signaling, suggesting proteins might be shuttled between the retina and vitreous. We also identified human disease biomarkers represented in the mouse vitreous and retina, including carbonic anhydrase-2 and 3, crystallins, macrophage inhibitory factor, glutathione peroxidase, peroxiredoxins, S100 precursors, and von Willebrand factor. Our analysis suggests the vitreous expresses nonstructural proteins that functionally interact with the retina to manage oxidative stress, immune reactions, and intracellular proteins may be exchanged between the retina and vitreous. This novel proteomic dataset can be used for investigating human vitreoretinopathies in mouse models. Validation of vitreoretinal biomarkers for human ocular diseases will provide a critical tool for diagnostics and an avenue for therapeutics.

Software selection based on analysis and forecasting methods, practised in 1C

NASA Astrophysics Data System (ADS)

Vazhdaev, A. N.; Chernysheva, T. Y.; Lisacheva, E. I.

2015-09-01

The research focuses on the problem of a “1C: Enterprise 8” platform inboard mechanisms for data analysis and forecasting. It is important to evaluate and select proper software to develop effective strategies for customer relationship management in terms of sales, as well as implementation and further maintenance of software. Research data allows creating new forecast models to schedule further software distribution.

Software for Real-Time Analysis of Subsonic Test Shot Accuracy

DTIC Science & Technology

2014-03-01

used the C++ programming language, the Open Source Computer Vision ( OpenCV ®) software library, and Microsoft Windows® Application Programming...video for comparison through OpenCV image analysis tools. Based on the comparison, the software then computed the coordinates of each shot relative to...DWB researchers wanted to use the Open Source Computer Vision ( OpenCV ) software library for capturing and analyzing frames of video. OpenCV contains

Software ion scan functions in analysis of glycomic and lipidomic MS/MS datasets.

PubMed

Haramija, Marko

2018-03-01

Hardware ion scan functions unique to tandem mass spectrometry (MS/MS) mode of data acquisition, such as precursor ion scan (PIS) and neutral loss scan (NLS), are important for selective extraction of key structural data from complex MS/MS spectra. However, their software counterparts, software ion scan (SIS) functions, are still not regularly available. Software ion scan functions can be easily coded for additional functionalities, such as software multiple precursor ion scan, software no ion scan, and software variable ion scan functions. These are often necessary, since they allow more efficient analysis of complex MS/MS datasets, often encountered in glycomics and lipidomics. Software ion scan functions can be easily coded by using modern script languages and can be independent of instrument manufacturer. Here we demonstrate the utility of SIS functions on a medium-size glycomic MS/MS dataset. Knowledge of sample properties, as well as of diagnostic and conditional diagnostic ions crucial for data analysis, was needed. Based on the tables constructed with the output data from the SIS functions performed, a detailed analysis of a complex MS/MS glycomic dataset could be carried out in a quick, accurate, and efficient manner. Glycomic research is progressing slowly, and with respect to the MS experiments, one of the key obstacles for moving forward is the lack of appropriate bioinformatic tools necessary for fast analysis of glycomic MS/MS datasets. Adding novel SIS functionalities to the glycomic MS/MS toolbox has a potential to significantly speed up the glycomic data analysis process. Similar tools are useful for analysis of lipidomic MS/MS datasets as well, as will be discussed briefly. Copyright © 2017 John Wiley & Sons, Ltd.

New software for statistical analysis of Cambridge Structural Database data

PubMed Central

Sykes, Richard A.; McCabe, Patrick; Allen, Frank H.; Battle, Gary M.; Bruno, Ian J.; Wood, Peter A.

2011-01-01

A collection of new software tools is presented for the analysis of geometrical, chemical and crystallographic data from the Cambridge Structural Database (CSD). This software supersedes the program Vista. The new functionality is integrated into the program Mercury in order to provide statistical, charting and plotting options alongside three-dimensional structural visualization and analysis. The integration also permits immediate access to other information about specific CSD entries through the Mercury framework, a common requirement in CSD data analyses. In addition, the new software includes a range of more advanced features focused towards structural analysis such as principal components analysis, cone-angle correction in hydrogen-bond analyses and the ability to deal with topological symmetry that may be exhibited in molecular search fragments. PMID:22477784

Development of Cell Analysis Software for Cultivated Corneal Endothelial Cells.

PubMed

Okumura, Naoki; Ishida, Naoya; Kakutani, Kazuya; Hongo, Akane; Hiwa, Satoru; Hiroyasu, Tomoyuki; Koizumi, Noriko

2017-11-01

To develop analysis software for cultured human corneal endothelial cells (HCECs). Software was designed to recognize cell borders and to provide parameters such as cell density, coefficient of variation, and polygonality of cultured HCECs based on phase contrast images. Cultured HCECs with high or low cell density were incubated with Ca-free and Mg-free phosphate-buffered saline for 10 minutes to reveal the cell borders and were then analyzed with software (n = 50). Phase contrast images showed that cell borders were not distinctly outlined, but these borders became more distinctly outlined after phosphate-buffered saline treatment and were recognized by cell analysis software. The cell density value provided by software was similar to that obtained using manual cell counting by an experienced researcher. Morphometric parameters, such as the coefficient of variation and polygonality, were also produced by software, and these values were significantly correlated with cell density (Pearson correlation coefficients -0.62 and 0.63, respectively). The software described here provides morphometric information from phase contrast images, and it enables subjective and noninvasive quality assessment for tissue engineering therapy of the corneal endothelium.

A guide for building biological pathways along with two case studies: hair and breast development.

PubMed

Trindade, Daniel; Orsine, Lissur A; Barbosa-Silva, Adriano; Donnard, Elisa R; Ortega, J Miguel

2015-03-01

Genomic information is being underlined in the format of biological pathways. Building these biological pathways is an ongoing demand and benefits from methods for extracting information from biomedical literature with the aid of text-mining tools. Here we hopefully guide you in the attempt of building a customized pathway or chart representation of a system. Our manual is based on a group of software designed to look at biointeractions in a set of abstracts retrieved from PubMed. However, they aim to support the work of someone with biological background, who does not need to be an expert on the subject and will play the role of manual curator while designing the representation of the system, the pathway. We therefore illustrate with two challenging case studies: hair and breast development. They were chosen for focusing on recent acquisitions of human evolution. We produced sub-pathways for each study, representing different phases of development. Differently from most charts present in current databases, we present detailed descriptions, which will additionally guide PESCADOR users along the process. The implementation as a web interface makes PESCADOR a unique tool for guiding the user along the biointeractions, which will constitute a novel pathway. Copyright © 2014 Elsevier Inc. All rights reserved.

Team Software Development for Aerothermodynamic and Aerodynamic Analysis and Design

NASA Technical Reports Server (NTRS)

Alexandrov, N.; Atkins, H. L.; Bibb, K. L.; Biedron, R. T.; Carpenter, M. H.; Gnoffo, P. A.; Hammond, D. P.; Jones, W. T.; Kleb, W. L.; Lee-Rausch, E. M.

2003-01-01

A collaborative approach to software development is described. The approach employs the agile development techniques: project retrospectives, Scrum status meetings, and elements of Extreme Programming to efficiently develop a cohesive and extensible software suite. The software product under development is a fluid dynamics simulator for performing aerodynamic and aerothermodynamic analysis and design. The functionality of the software product is achieved both through the merging, with substantial rewrite, of separate legacy codes and the authorship of new routines. Examples of rapid implementation of new functionality demonstrate the benefits obtained with this agile software development process. The appendix contains a discussion of coding issues encountered while porting legacy Fortran 77 code to Fortran 95, software design principles, and a Fortran 95 coding standard.

Using Combined SFTA and SFMECA Techniques for Space Critical Software

NASA Astrophysics Data System (ADS)

Nicodemos, F. G.; Lahoz, C. H. N.; Abdala, M. A. D.; Saotome, O.

2012-01-01

This work addresses the combined Software Fault Tree Analysis (SFTA) and Software Failure Modes, Effects and Criticality Analysis (SFMECA) techniques applied to space critical software of satellite launch vehicles. The combined approach is under research as part of the Verification and Validation (V&V) efforts to increase software dependability and as future application in other projects under development at Instituto de Aeronáutica e Espaço (IAE). The applicability of such approach was conducted on system software specification and applied to a case study based on the Brazilian Satellite Launcher (VLS). The main goal is to identify possible failure causes and obtain compensating provisions that lead to inclusion of new functional and non-functional system software requirements.

Software development predictors, error analysis, reliability models and software metric analysis

NASA Technical Reports Server (NTRS)

Basili, Victor

1983-01-01

The use of dynamic characteristics as predictors for software development was studied. It was found that there are some significant factors that could be useful as predictors. From a study on software errors and complexity, it was shown that meaningful results can be obtained which allow insight into software traits and the environment in which it is developed. Reliability models were studied. The research included the field of program testing because the validity of some reliability models depends on the answers to some unanswered questions about testing. In studying software metrics, data collected from seven software engineering laboratory (FORTRAN) projects were examined and three effort reporting accuracy checks were applied to demonstrate the need to validate a data base. Results are discussed.

Integrated learning in practical machine element design course: a case study of V-pulley design

NASA Astrophysics Data System (ADS)

Tantrabandit, Manop

2014-06-01

To achieve an effective integrated learning in Machine Element Design course, it is of importance to bridge the basic knowledge and skills of element designs. The multiple core learning leads the pathway which consists of two main parts. The first part involves teaching documents of which the contents are number of V-groove formulae, standard of V-grooved pulleys, and parallel key dimension's formulae. The second part relates to the subjects that the students have studied prior to participating in this integrated learning course, namely Material Selection, Manufacturing Process, Applied Engineering Drawing, CAD (Computer Aided Design) animation software. Moreover, an intensive cooperation between a lecturer and students is another key factor to fulfill the success of integrated learning. Last but not least, the students need to share their knowledge within the group and among the other groups aiming to gain knowledge of and skills in 1) the application of CAD-software to build up manufacture part drawings, 2) assembly drawing, 3) simulation to verify the strength of loaded pulley by method of Finite Element Analysis (FEA), 4) the software to create animation of mounting and dismounting of a pulley to a shaft, and 5) an instruction manual. The end product of this integrated learning, as a result of the above 1 to 5 knowledge and skills obtained, the participating students can create an assembly derived from manufacture part drawings and a video presentation with bilingual (English-Thai) audio description of Vpulley with datum diameter of 250 mm, 4 grooves, and type of groove: SPA.

Automated daily quality control analysis for mammography in a multi-unit imaging center.

PubMed

Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

2018-01-01

Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

Analysis of Software Systems for Specialized Computers,

DTIC Science & Technology

computer) with given computer hardware and software . The object of study is the software system of a computer, designed for solving a fixed complex of...purpose of the analysis is to find parameters that characterize the system and its elements during operation, i.e., when servicing the given requirement flow. (Author)

MRI-based dynamic tracking of an untethered ferromagnetic microcapsule navigating in liquid

NASA Astrophysics Data System (ADS)

Dahmen, Christian; Belharet, Karim; Folio, David; Ferreira, Antoine; Fatikow, Sergej

2016-04-01

The propulsion of ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the ferromagnetic objects, and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment, integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this article aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in the human body. The proposed approaches are validated with different experiments.

PCBA depaneling stress minimization study

NASA Astrophysics Data System (ADS)

Darus, M. H. B. M.; Aziz, M. H. B. A.; Ong, N. R.; Alcain, J. B.; Retnasamy, V.

2017-09-01

Printed circuit board (PCB) is board that used to connect the electricity using the conductive pathways. The PCB that consists with electronic components was called as printed circuit board assembly (PCBA). Bending process has been used as one of the depaneling techniques may contribute to mechanical stress and the failure of capacitors and other components to function. As a result, the idea to create holes in particular location was implemented in order to absorb the stress. In this study, finite element analysis is demonstrated by using ANSYS software. Two PCBA design models are considered in order to investigate the effect of the hole and the stress response. The simulation results show that the hole on the PCBA has reduced the stress. For Design model 2, the stress response of the holes located vertically to the PCBA is lower than the holes located horizontally to the PCBA.

A Bioinformatics Facility for NASA

NASA Technical Reports Server (NTRS)

Schweighofer, Karl; Pohorille, Andrew

2006-01-01

Building on an existing prototype, we have fielded a facility with bioinformatics technologies that will help NASA meet its unique requirements for biological research. This facility consists of a cluster of computers capable of performing computationally intensive tasks, software tools, databases and knowledge management systems. Novel computational technologies for analyzing and integrating new biological data and already existing knowledge have been developed. With continued development and support, the facility will fulfill strategic NASA s bioinformatics needs in astrobiology and space exploration. . As a demonstration of these capabilities, we will present a detailed analysis of how spaceflight factors impact gene expression in the liver and kidney for mice flown aboard shuttle flight STS-108. We have found that many genes involved in signal transduction, cell cycle, and development respond to changes in microgravity, but that most metabolic pathways appear unchanged.

ASPASIA: A toolkit for evaluating the effects of biological interventions on SBML model behaviour.

PubMed

Evans, Stephanie; Alden, Kieran; Cucurull-Sanchez, Lourdes; Larminie, Christopher; Coles, Mark C; Kullberg, Marika C; Timmis, Jon

2017-02-01

A calibrated computational model reflects behaviours that are expected or observed in a complex system, providing a baseline upon which sensitivity analysis techniques can be used to analyse pathways that may impact model responses. However, calibration of a model where a behaviour depends on an intervention introduced after a defined time point is difficult, as model responses may be dependent on the conditions at the time the intervention is applied. We present ASPASIA (Automated Simulation Parameter Alteration and SensItivity Analysis), a cross-platform, open-source Java toolkit that addresses a key deficiency in software tools for understanding the impact an intervention has on system behaviour for models specified in Systems Biology Markup Language (SBML). ASPASIA can generate and modify models using SBML solver output as an initial parameter set, allowing interventions to be applied once a steady state has been reached. Additionally, multiple SBML models can be generated where a subset of parameter values are perturbed using local and global sensitivity analysis techniques, revealing the model's sensitivity to the intervention. To illustrate the capabilities of ASPASIA, we demonstrate how this tool has generated novel hypotheses regarding the mechanisms by which Th17-cell plasticity may be controlled in vivo. By using ASPASIA in conjunction with an SBML model of Th17-cell polarisation, we predict that promotion of the Th1-associated transcription factor T-bet, rather than inhibition of the Th17-associated transcription factor RORγt, is sufficient to drive switching of Th17 cells towards an IFN-γ-producing phenotype. Our approach can be applied to all SBML-encoded models to predict the effect that intervention strategies have on system behaviour. ASPASIA, released under the Artistic License (2.0), can be downloaded from http://www.york.ac.uk/ycil/software.

Flexible Software Architecture for Visualization and Seismic Data Analysis

NASA Astrophysics Data System (ADS)

Petunin, S.; Pavlov, I.; Mogilenskikh, D.; Podzyuban, D.; Arkhipov, A.; Baturuin, N.; Lisin, A.; Smith, A.; Rivers, W.; Harben, P.

2007-12-01

Research in the field of seismology requires software and signal processing utilities for seismogram manipulation and analysis. Seismologists and data analysts often encounter a major problem in the use of any particular software application specific to seismic data analysis: the tuning of commands and windows to the specific waveforms and hot key combinations so as to fit their familiar informational environment. The ability to modify the user's interface independently from the developer requires an adaptive code structure. An adaptive code structure also allows for expansion of software capabilities such as new signal processing modules and implementation of more efficient algorithms. Our approach is to use a flexible "open" architecture for development of geophysical software. This report presents an integrated solution for organizing a logical software architecture based on the Unix version of the Geotool software implemented on the Microsoft NET 2.0 platform. Selection of this platform greatly expands the variety and number of computers that can implement the software, including laptops that can be utilized in field conditions. It also facilitates implementation of communication functions for seismic data requests from remote databases through the Internet. The main principle of the new architecture for Geotool is that scientists should be able to add new routines for digital waveform analysis via software plug-ins that utilize the basic Geotool display for GUI interaction. The use of plug-ins allows the efficient integration of diverse signal-processing software, including software still in preliminary development, into an organized platform without changing the fundamental structure of that platform itself. An analyst's use of Geotool is tracked via a metadata file so that future studies can reconstruct, and alter, the original signal processing operations. The work has been completed in the framework of a joint Russian- American project.

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.

Influence analysis of Github repositories.

PubMed

Hu, Yan; Zhang, Jun; Bai, Xiaomei; Yu, Shuo; Yang, Zhuo

2016-01-01

With the support of cloud computing techniques, social coding platforms have changed the style of software development. Github is now the most popular social coding platform and project hosting service. Software developers of various levels keep entering Github, and use Github to save their public and private software projects. The large amounts of software developers and software repositories on Github are posing new challenges to the world of software engineering. This paper tries to tackle one of the important problems: analyzing the importance and influence of Github repositories. We proposed a HITS based influence analysis on graphs that represent the star relationship between Github users and repositories. A weighted version of HITS is applied to the overall star graph, and generates a different set of top influential repositories other than the results from standard version of HITS algorithm. We also conduct the influential analysis on per-month star graph, and study the monthly influence ranking of top repositories.

A Visual Basic simulation software tool for performance analysis of a membrane-based advanced water treatment plant.

PubMed

Pal, P; Kumar, R; Srivastava, N; Chaudhuri, J

2014-02-01

A Visual Basic simulation software (WATTPPA) has been developed to analyse the performance of an advanced wastewater treatment plant. This user-friendly and menu-driven software is based on the dynamic mathematical model for an industrial wastewater treatment scheme that integrates chemical, biological and membrane-based unit operations. The software-predicted results corroborate very well with the experimental findings as indicated in the overall correlation coefficient of the order of 0.99. The software permits pre-analysis and manipulation of input data, helps in optimization and exhibits performance of an integrated plant visually on a graphical platform. It allows quick performance analysis of the whole system as well as the individual units. The software first of its kind in its domain and in the well-known Microsoft Excel environment is likely to be very useful in successful design, optimization and operation of an advanced hybrid treatment plant for hazardous wastewater.

Experience report: Using formal methods for requirements analysis of critical spacecraft software

NASA Technical Reports Server (NTRS)

Lutz, Robyn R.; Ampo, Yoko

1994-01-01

Formal specification and analysis of requirements continues to gain support as a method for producing more reliable software. However, the introduction of formal methods to a large software project is difficult, due in part to the unfamiliarity of the specification languages and the lack of graphics. This paper reports results of an investigation into the effectiveness of formal methods as an aid to the requirements analysis of critical, system-level fault-protection software on a spacecraft currently under development. Our experience indicates that formal specification and analysis can enhance the accuracy of the requirements and add assurance prior to design development in this domain. The work described here is part of a larger, NASA-funded research project whose purpose is to use formal-methods techniques to improve the quality of software in space applications. The demonstration project described here is part of the effort to evaluate experimentally the effectiveness of supplementing traditional engineering approaches to requirements specification with the more rigorous specification and analysis available with formal methods.

Software design for analysis of multichannel intracardial and body surface electrocardiograms.

PubMed

Potse, Mark; Linnenbank, André C; Grimbergen, Cornelis A

2002-11-01

Analysis of multichannel ECG recordings (body surface maps (BSMs) and intracardial maps) requires special software. We created a software package and a user interface on top of a commercial data analysis package (MATLAB) by a combination of high-level and low-level programming. Our software was created to satisfy the needs of a diverse group of researchers. It can handle a large variety of recording configurations. It allows for interactive usage through a fast and robust user interface, and batch processing for the analysis of large amounts of data. The package is user-extensible, includes routines for both common and experimental data processing tasks, and works on several computer platforms. The source code is made intelligible using software for structured documentation and is available to the users. The package is currently used by more than ten research groups analysing ECG data worldwide.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

NASA Technical Reports Server (NTRS)

Selby, Richard W.; Porter, Adam A.

1988-01-01

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

78 FR 1162 - Cardiovascular Devices; Reclassification of External Cardiac Compressor

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-08

... safety and electromagnetic compatibility; For devices containing software, software verification... electromagnetic compatibility; For devices containing software, software verification, validation, and hazard... electrical components, appropriate analysis and testing must validate electrical safety and electromagnetic...

Segment fusion of ToF-SIMS images.

PubMed

Milillo, Tammy M; Miller, Mary E; Fischione, Remo; Montes, Angelina; Gardella, Joseph A

2016-06-08

The imaging capabilities of time-of-flight secondary ion mass spectrometry (ToF-SIMS) have not been used to their full potential in the analysis of polymer and biological samples. Imaging has been limited by the size of the dataset and the chemical complexity of the sample being imaged. Pixel and segment based image fusion algorithms commonly used in remote sensing, ecology, geography, and geology provide a way to improve spatial resolution and classification of biological images. In this study, a sample of Arabidopsis thaliana was treated with silver nanoparticles and imaged with ToF-SIMS. These images provide insight into the uptake mechanism for the silver nanoparticles into the plant tissue, giving new understanding to the mechanism of uptake of heavy metals in the environment. The Munechika algorithm was programmed in-house and applied to achieve pixel based fusion, which improved the spatial resolution of the image obtained. Multispectral and quadtree segment or region based fusion algorithms were performed using ecognition software, a commercially available remote sensing software suite, and used to classify the images. The Munechika fusion improved the spatial resolution for the images containing silver nanoparticles, while the segment fusion allowed classification and fusion based on the tissue types in the sample, suggesting potential pathways for the uptake of the silver nanoparticles.

FASEA: A FPGA Acquisition System and Software Event Analysis for liquid scintillation counting

NASA Astrophysics Data System (ADS)

Steele, T.; Mo, L.; Bignell, L.; Smith, M.; Alexiev, D.

2009-10-01

The FASEA (FPGA based Acquisition and Software Event Analysis) system has been developed to replace the MAC3 for coincidence pulse processing. The system uses a National Instruments Virtex 5 FPGA card (PXI-7842R) for data acquisition and a purpose developed data analysis software for data analysis. Initial comparisons to the MAC3 unit are included based on measurements of 89Sr and 3H, confirming that the system is able to accurately emulate the behaviour of the MAC3 unit.

Evaluation of gene expression profiles and pathways underlying postnatal development in mouse sclera.

PubMed

Lim, Wan'E; Kwan, Jia Lin; Goh, Liang Kee; Beuerman, Roger W; Barathi, Veluchamy A

2012-01-01

The aim of this study was to identify the genes and pathways underlying the growth of the mouse sclera during postnatal development. Total RNA was isolated from each of 30 single mouse sclera (n=30, 6 sclera each from 1-, 2-, 3-, 6-, and 8-week-old mice) and reverse-transcribed into cDNA using a T7-N(6) primer. The resulting cDNA was fragmented, labeled with biotin, and hybridized to a Mouse Gene 1.0 ST Array. ANOVA analysis was then performed using Partek Genomic Suite 6.5 beta and differentially expressed transcript clusters were filtered based on a selection criterion of ≥ 2 relative fold change at a false discovery rate of ≤ 5%. Genes identified as involved in the main biologic processes during postnatal scleral development were further confirmed using qPCR. A possible pathway that contributes to the postnatal development of the sclera was investigated using Ingenuity Pathway Analysis software. The hierarchical clustering of all time points showed that they did not cluster according to age. The highest number of differentially expressed transcript clusters was found when week 1 and week 2 old scleral tissues were compared. The peroxisome proliferator- activated receptor gamma coactivator 1-alpha (Ppargc1a) gene was found to be involved in the networks generated using Ingenuity Pathway Studio (IPA) from the differentially expressed transcript cluster lists of week 2 versus 1, week 3 versus 2, week 6 versus 3, and week 8 versus 6. The gene expression of Ppargc1a varied during scleral growth from week 1 to 2, week 2 to 3, week 3 to 6, and week 6 to 8 and was found to interact with a different set of genes at different scleral growth stages. Therefore, this indicated that Ppargc1a might play a role in scleral growth during postnatal weeks 1 to 8. Gene expression of eye diseases should be studied as early as postnatal weeks 1-2 to ensure that any changes in gene expression pattern during disease development are detected. In addition, we propose that Ppargc1a might play a role in regulating postnatal scleral development by interacting with a different set of genes at different scleral growth stages.

Evaluation of gene expression profiles and pathways underlying postnatal development in mouse sclera

PubMed Central

Lim, Wan’E.; Kwan, Jia Lin; Goh, Liang Kee; Beuerman, Roger W.

2012-01-01

Purpose The aim of this study was to identify the genes and pathways underlying the growth of the mouse sclera during postnatal development. Methods Total RNA was isolated from each of 30 single mouse sclera (n=30, 6 sclera each from 1-, 2-, 3-, 6-, and 8-week-old mice) and reverse-transcribed into cDNA using a T7-N6 primer. The resulting cDNA was fragmented, labeled with biotin, and hybridized to a Mouse Gene 1.0 ST Array. ANOVA analysis was then performed using Partek Genomic Suite 6.5 beta and differentially expressed transcript clusters were filtered based on a selection criterion of ≥2 relative fold change at a false discovery rate of ≤5%. Genes identified as involved in the main biologic processes during postnatal scleral development were further confirmed using qPCR. A possible pathway that contributes to the postnatal development of the sclera was investigated using Ingenuity Pathway Analysis software. Results The hierarchical clustering of all time points showed that they did not cluster according to age. The highest number of differentially expressed transcript clusters was found when week 1 and week 2 old scleral tissues were compared. The peroxisome proliferator- activated receptor gamma coactivator 1-alpha (Ppargc1a) gene was found to be involved in the networks generated using Ingenuity Pathway Studio (IPA) from the differentially expressed transcript cluster lists of week 2 versus 1, week 3 versus 2, week 6 versus 3, and week 8 versus 6. The gene expression of Ppargc1a varied during scleral growth from week 1 to 2, week 2 to 3, week 3 to 6, and week 6 to 8 and was found to interact with a different set of genes at different scleral growth stages. Therefore, this indicated that Ppargc1a might play a role in scleral growth during postnatal weeks 1 to 8. Conclusions Gene expression of eye diseases should be studied as early as postnatal weeks 1–2 to ensure that any changes in gene expression pattern during disease development are detected. In addition, we propose that Ppargc1a might play a role in regulating postnatal scleral development by interacting with a different set of genes at different scleral growth stages. PMID:22736935

A User's Guide to the Meta-Analysis of Research Studies. Meta-Stat: Software To Aid in the Meta-Analysis of Research Findings.

ERIC Educational Resources Information Center

Rudner, Lawrence M.; Glass Gene V.; Evartt, David L.; Emery, Patrick J.

This manual and the accompanying software are intended to provide a step-by-step guide to conducting a meta-analytic study along with references for further reading and free high-quality software, "Meta-Stat.""Meta-Stat" is a comprehensive package designed to help in the meta-analysis of research studies in the social and behavioral sciences.…

Development of an automated asbestos counting software based on fluorescence microscopy.

PubMed

Alexandrov, Maxym; Ichida, Etsuko; Nishimura, Tomoki; Aoki, Kousuke; Ishida, Takenori; Hirota, Ryuichi; Ikeda, Takeshi; Kawasaki, Tetsuo; Kuroda, Akio

2015-01-01

An emerging alternative to the commonly used analytical methods for asbestos analysis is fluorescence microscopy (FM), which relies on highly specific asbestos-binding probes to distinguish asbestos from interfering non-asbestos fibers. However, all types of microscopic asbestos analysis require laborious examination of large number of fields of view and are prone to subjective errors and large variability between asbestos counts by different analysts and laboratories. A possible solution to these problems is automated counting of asbestos fibers by image analysis software, which would lower the cost and increase the reliability of asbestos testing. This study seeks to develop a fiber recognition and counting software for FM-based asbestos analysis. We discuss the main features of the developed software and the results of its testing. Software testing showed good correlation between automated and manual counts for the samples with medium and high fiber concentrations. At low fiber concentrations, the automated counts were less accurate, leading us to implement correction mode for automated counts. While the full automation of asbestos analysis would require further improvements in accuracy of fiber identification, the developed software could already assist professional asbestos analysts and record detailed fiber dimensions for the use in epidemiological research.

IFDOTMETER: A New Software Application for Automated Immunofluorescence Analysis.

PubMed

Rodríguez-Arribas, Mario; Pizarro-Estrella, Elisa; Gómez-Sánchez, Rubén; Yakhine-Diop, S M S; Gragera-Hidalgo, Antonio; Cristo, Alejandro; Bravo-San Pedro, Jose M; González-Polo, Rosa A; Fuentes, José M

2016-04-01

Most laboratories interested in autophagy use different imaging software for managing and analyzing heterogeneous parameters in immunofluorescence experiments (e.g., LC3-puncta quantification and determination of the number and size of lysosomes). One solution would be software that works on a user's laptop or workstation that can access all image settings and provide quick and easy-to-use analysis of data. Thus, we have designed and implemented an application called IFDOTMETER, which can run on all major operating systems because it has been programmed using JAVA (Sun Microsystems). Briefly, IFDOTMETER software has been created to quantify a variety of biological hallmarks, including mitochondrial morphology and nuclear condensation. The program interface is intuitive and user-friendly, making it useful for users not familiar with computer handling. By setting previously defined parameters, the software can automatically analyze a large number of images without the supervision of the researcher. Once analysis is complete, the results are stored in a spreadsheet. Using software for high-throughput cell image analysis offers researchers the possibility of performing comprehensive and precise analysis of a high number of images in an automated manner, making this routine task easier. © 2015 Society for Laboratory Automation and Screening.

FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses.

PubMed

Desai, Trunil S; Srivastava, Shireesh

2018-01-01

13 C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13 C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13 C-MFA software that works in various operating systems will enable more researchers to perform 13 C-MFA and to further modify and develop the package.

FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses

PubMed Central

Desai, Trunil S.

2018-01-01

13C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13C-MFA software that works in various operating systems will enable more researchers to perform 13C-MFA and to further modify and develop the package. PMID:29736347

Reliability of skeletal maturity analysis using the cervical vertebrae maturation method on dedicated software.

PubMed

Padalino, Saverio; Sfondrini, Maria Francesca; Chenuil, Laura; Scudeller, Luigia; Gandini, Paola

2014-12-01

The aim of this study was to assess the feasibility of skeletal maturation analysis using the Cervical Vertebrae Maturation (CVM) method by means of dedicated software, developed in collaboration with Outside Format (Paullo-Milan), as compared with manual analysis. From a sample of patients aged 7-21 years, we gathered 100 lateral cephalograms, 20 for each of the five CVM stages. For each cephalogram, we traced cervical vertebrae C2, C3 and C4 by hand using a lead pencil and an acetate sheet and dedicated software. All the tracings were made by an experienced operator (a dentofacial orthopedics resident) and by an inexperienced operator (a student in dental surgery). Each operator recorded the time needed to make each tracing in order to demonstrate differences in the times taken. Concordance between the manual analysis and the analysis performed using the dedicated software was 94% for the resident and 93% for the student. Interobserver concordance was 99%. The hand-tracing was quicker than that performed by means of the software (28 seconds more on average). The cervical vertebrae analysis software offers excellent clinical performance, even if the method takes longer than the manual technique. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

MicroRNA Expression Patterns of CD8+ T Cells in Acute and Chronic Brucellosis

PubMed Central

Budak, Ferah; Bal, S. Haldun; Tezcan, Gulcin; Guvenc, Furkan; Akalin, E. Halis; Goral, Guher; Deniz, Gunnur

2016-01-01

Although our knowledge about Brucella virulence factors and the host response increase rapidly, the mechanisms of immune evasion by the pathogen and causes of chronic disease are still unknown. Here, we aimed to investigate the immunological factors which belong to CD8+ T cells and their roles in the transition of brucellosis from acute to chronic infection. Using miRNA microarray, more than 2000 miRNAs were screened in CD8+ T cells of patients with acute or chronic brucellosis and healthy controls that were sorted from peripheral blood with flow cytometry and validated through qRT-PCR. Findings were evaluated using GeneSpring GX (Agilent) 13.0 software and KEGG pathway analysis. Expression of two miRNAs were determined to display a significant fold change in chronic group when compared with acute or control groups. Both miRNAs (miR-126-5p and miR-4753-3p) were decreased (p <0.05 or fold change > 2). These miRNAs have the potential to be the regulators of CD8+ T cell-related marker genes for chronic brucellosis infections. The differentially expressed miRNAs and their predicted target genes are involved in MAPK signaling pathway, cytokine-cytokine receptor interactions, endocytosis, regulation of actin cytoskeleton, and focal adhesion indicating their potential roles in chronic brucellosis and its progression. It is the first study of miRNA expression analysis of human CD8+ T cells to clarify the mechanism of inveteracy in brucellosis. PMID:27824867

Copy number variation in ALOX5 and PTGER1 is associated with NSAIDs-induced urticaria and/or angioedema.

PubMed

Plaza-Serón, María Del Carmen; Ayuso, Pedro; Pérez-Sánchez, Natalia; Doña, Inmaculada; Blanca-Lopez, Natalia; Flores, Carlos; Galindo, Luisa; Molina, Ana; Perkins, James R; Cornejo-García, Jose A; Agúndez, Jose A; García-Martín, Elena; Campo, Paloma; Canto, Gabriela; Blanca, Miguel

2016-06-01

Cross-intolerance to NSAIDs is a class of drug hypersensitivity reaction, of which NSAIDs-induced urticaria and/or angioedema (NIUA) are the most frequent clinical entities. They are considered to involve dysregulation of the arachidonic acid pathway; however, this mechanism has not been confirmed for NIUA. In this work, we assessed copy number variations (CNVs) in eight of the main genes involved in the arachidonic acid pathway and their possible genetic association with NIUA. CNVs in ALOX5, LTC4S, PTGS1, PTGS2, PTGER1, PTGER2, PTGER3, and PTGER4 were analyzed using TaqMan copy number assays. Genotyping was carried out by real-time quantitative PCR. Individual genotypes were assigned using the CopyCaller Software. Statistical analysis was carried out using GraphPad prism 5, PLINK, EPIDAT, and R version 3.1.2. A total of 151 cases and 139 controls were analyzed during the discovery phase and 148 cases and 140 controls were used for replication. CNVs in open reading frames were found for ALOX5, PTGER1, PTGER3, and PTGER4. Statistically significant differences in the CNV frequency between NIUA and controls were found for ALOX5 (Pc=0.017) and PTGER1 (Pc=1.22E-04). This study represents the first analysis showing an association between CNVs in exonic regions of ALOX5 and PTGER1 and NIUA. This suggests a role of CNVs in this pathology that should be explored further.

Path Analysis Associations Between Perceived Social Support, Stressful Life Events and Other Psychosocial Risk Factors During Pregnancy and Preterm Delivery

PubMed Central

Mirabzadeh, Arash; Dolatian, Mahrokh; Forouzan, Ameneh Setare; Sajjadi, Homeira; Majd, Hamid Alavi; Mahmoodi, Zohreh

2013-01-01

Background Although several socio-medical risk factors have been identified for preterm labor, there is a gap in understanding the underlying etiology of preterm labor. Objectives The current study aimed to analyze the relationship pathway of perceived social support, stressful life events, and other psychosocial risk factors during pregnancy with incidence of preterm labor. Materials and Methods In a prospective cohort study in four hospitals in Tehran, 500 pregnant women in their 24th to 28th gestational weeks were studied. They filled out a self-report questionnaire on perceived social support, depression, anxiety, stress and stressful life events. Sociodemographic characteristics were also assessed. The participants were followed up until labor, and the data about mother and the newborn were collected after labor. The data were analyzed by SPSS 16 and Lisrel 8.8 software programs using pathway analysis. Results The final path model fit well (CFI = 0.96; RMSEA = .064). The results showed that depression, anxiety, and stress (β = -0.18) directly, and stressful life events indirectly (β= -0.0396) had the most predict on gestational age at labor. Perceived social support, directly through socioeconomic status (β=0.25), and indirectly through stress, depression and anxiety (β= -0.26) affected the gestational age at birth (β= 0.0468). Conclusions The current study showed that supporting pregnant mother moderates psychological problems such as stress, anxiety, and depression, and hence reduces preterm labor. PMID:24349750

New software for 3D fracture network analysis and visualization

NASA Astrophysics Data System (ADS)

Song, J.; Noh, Y.; Choi, Y.; Um, J.; Hwang, S.

2013-12-01

This study presents new software to perform analysis and visualization of the fracture network system in 3D. The developed software modules for the analysis and visualization, such as BOUNDARY, DISK3D, FNTWK3D, CSECT and BDM, have been developed using Microsoft Visual Basic.NET and Visualization TookKit (VTK) open-source library. Two case studies revealed that each module plays a role in construction of analysis domain, visualization of fracture geometry in 3D, calculation of equivalent pipes, production of cross-section map and management of borehole data, respectively. The developed software for analysis and visualization of the 3D fractured rock mass can be used to tackle the geomechanical problems related to strength, deformability and hydraulic behaviors of the fractured rock masses.

Novel features and enhancements in BioBin, a tool for the biologically inspired binning and association analysis of rare variants

PubMed Central

Byrska-Bishop, Marta; Wallace, John; Frase, Alexander T; Ritchie, Marylyn D

2018-01-01

Abstract Motivation BioBin is an automated bioinformatics tool for the multi-level biological binning of sequence variants. Herein, we present a significant update to BioBin which expands the software to facilitate a comprehensive rare variant analysis and incorporates novel features and analysis enhancements. Results In BioBin 2.3, we extend our software tool by implementing statistical association testing, updating the binning algorithm, as well as incorporating novel analysis features providing for a robust, highly customizable, and unified rare variant analysis tool. Availability and implementation The BioBin software package is open source and freely available to users at http://www.ritchielab.com/software/biobin-download Contact mdritchie@geisinger.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28968757

Development problem analysis of correlation leak detector’s software

NASA Astrophysics Data System (ADS)

Faerman, V. A.; Avramchuk, V. S.; Marukyan, V. M.

2018-05-01

In the article, the practical application and the structure of the correlation leak detectors’ software is studied and the task of its designing is analyzed. In the first part of the research paper, the expediency of the facilities development of correlation leak detectors for the following operating efficiency of public utilities exploitation is shown. The analysis of the functional structure of correlation leak detectors is conducted and its program software tasks are defined. In the second part of the research paper some development steps of the software package – requirement forming, program structure definition and software concept creation – are examined in the context of the usage experience of the hardware-software prototype of correlation leak detector.

relaxGUI: a new software for fast and simple NMR relaxation data analysis and calculation of ps-ns and μs motion of proteins.

PubMed

Bieri, Michael; d'Auvergne, Edward J; Gooley, Paul R

2011-06-01

Investigation of protein dynamics on the ps-ns and μs-ms timeframes provides detailed insight into the mechanisms of enzymes and the binding properties of proteins. Nuclear magnetic resonance (NMR) is an excellent tool for studying protein dynamics at atomic resolution. Analysis of relaxation data using model-free analysis can be a tedious and time consuming process, which requires good knowledge of scripting procedures. The software relaxGUI was developed for fast and simple model-free analysis and is fully integrated into the software package relax. It is written in Python and uses wxPython to build the graphical user interface (GUI) for maximum performance and multi-platform use. This software allows the analysis of NMR relaxation data with ease and the generation of publication quality graphs as well as color coded images of molecular structures. The interface is designed for simple data analysis and management. The software was tested and validated against the command line version of relax.

Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing.

PubMed

Grasso, Chiara; Trevisan, Morena; Fiano, Valentina; Tarallo, Valentina; De Marco, Laura; Sacerdote, Carlotta; Richiardi, Lorenzo; Merletti, Franco; Gillio-Tos, Anna

2016-01-01

Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis. Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results. We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively. We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites. The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing.

Toward Baseline Software Anomalies in NASA Missions

NASA Technical Reports Server (NTRS)

Layman, Lucas; Zelkowitz, Marvin; Basili, Victor; Nikora, Allen P.

2012-01-01

In this fast abstract, we provide preliminary findings an analysis of 14,500 spacecraft anomalies from unmanned NASA missions. We provide some baselines for the distributions of software vs. non-software anomalies in spaceflight systems, the risk ratings of software anomalies, and the corrective actions associated with software anomalies.

Computing and software

USGS Publications Warehouse

White, Gary C.; Hines, J.E.

2004-01-01

The reality is that the statistical methods used for analysis of data depend upon the availability of software. Analysis of marked animal data is no different than the rest of the statistical field. The methods used for analysis are those that are available in reliable software packages. Thus, the critical importance of having reliable, up–to–date software available to biologists is obvious. Statisticians have continued to develop more robust models, ever expanding the suite of potential analysis methodsavailable. But without software to implement these newer methods, they will languish in the abstract, and not be applied to the problems deserving them.In the Computers and Software Session, two new software packages are described, a comparison of implementation of methods for the estimation of nest survival is provided, and a more speculative paper about how the next generation of software might be structured is presented.Rotella et al. (2004) compare nest survival estimation with different software packages: SAS logistic regression, SAS non–linear mixed models, and Program MARK. Nests are assumed to be visited at various, possibly infrequent, intervals. All of the approaches described compute nest survival with the same likelihood, and require that the age of the nest is known to account for nests that eventually hatch. However, each approach offers advantages and disadvantages, explored by Rotella et al. (2004).Efford et al. (2004) present a new software package called DENSITY. The package computes population abundance and density from trapping arrays and other detection methods with a new and unique approach. DENSITY represents the first major addition to the analysis of trapping arrays in 20 years.Barker & White (2004) discuss how existing software such as Program MARK require that each new model’s likelihood must be programmed specifically for that model. They wishfully think that future software might allow the user to combine pieces of likelihood functions together to generate estimates. The idea is interesting, and maybe some bright young statistician can work out the specifics to implement the procedure.Choquet et al. (2004) describe MSURGE, a software package that implements the multistate capture–recapture models. The unique feature of MSURGE is that the design matrix is constructed with an interpreted language called GEMACO. Because MSURGE is limited to just multistate models, the special requirements of these likelihoods can be provided.The software and methods presented in these papers gives biologists and wildlife managers an expanding range of possibilities for data analysis. Although ease–of–use is generally getting better, it does not replace the need for understanding of the requirements and structure of the models being computed. The internet provides access to many free software packages as well as user–discussion groups to share knowledge and ideas. (A starting point for wildlife–related applications is (http://www.phidot.org).

Cellular processes involved in human epidermal cells exposed to extremely low frequency electric fields.

PubMed

Collard, J-F; Hinsenkamp, M

2015-05-01

We observed on different tissues and organisms a biological response after exposure to pulsed low frequency and low amplitude electric or electromagnetic fields but the precise mechanism of cell response remains unknown. The aim of this publication is to understand, using bioinformatics, the biological relevance of processes involved in the modification of gene expression. The list of genes analyzed was obtained after microarray protocol realized on cultures of human epidermal explants growing on deepidermized human skin exposed to a pulsed low frequency electric field. The directed acyclic graph on a WebGestalt Gene Ontology module shows six categories under the biological process root: "biological regulation", "cellular process", "cell proliferation", "death", "metabolic process" and "response to stimulus". Enriched derived categories are coherent with the type of in vitro culture, the stimulation protocol or with the previous results showing a decrease of cell proliferation and an increase of differentiation. The Kegg module on WebGestalt has highlighted "cell cycle" and "p53 signaling pathway" as significantly involved. The Kegg website brings out interactions between FoxO, MAPK, JNK, p53, p38, PI3K/Akt, Wnt, mTor or NF-KappaB. Some genes expressed by the stimulation are known to have an exclusive function on these pathways. Analyses performed with Pathway Studio linked cell proliferation, cell differentiation, apoptosis, cell cycle, mitosis, cell death etc. with our microarrays results. Medline citation generated by the software and the fold change variation confirms a diminution of the proliferation, activation of the differentiation and a less well-defined role of apoptosis or wound healing. Wnt and DKK functional classes, DKK1, MACF1, ATF3, MME, TXNRD1, and BMP-2 genes proposed in previous publications after a manual analysis are also highlighted with other genes after Pathway Studio automatic procedure. Finally, an analysis conducted on a list of genes characterized by an accelerated regulation after extremely low frequency pulsed stimulation also confirms their role in the processes of cell proliferation and differentiation. Bioinformatics approach allows in-depth research, without the bias of pre-selection, on cellular processes involved in a huge gene list. Copyright © 2015 Elsevier Inc. All rights reserved.

USER'S GUIDE: Strategic Waste Minimization Initiative (SWAMI) Version 2.0 - A Software Tool to Aid in Process Analysis for Pollution Prevention

EPA Science Inventory

The Strategic WAste Minimization Initiative (SWAMI) Software, Version 2.0 is a tool for using process analysis for identifying waste minimization opportunities within an industrial setting. The software requires user-supplied information for process definition, as well as materia...

Integrating Model-Based Verification into Software Design Education

ERIC Educational Resources Information Center

Yilmaz, Levent; Wang, Shuo

2005-01-01

Proper design analysis is indispensable to assure quality and reduce emergent costs due to faulty software. Teaching proper design verification skills early during pedagogical development is crucial, as such analysis is the only tractable way of resolving software problems early when they are easy to fix. The premise of the presented strategy is…

Software Reliability, Measurement, and Testing. Volume 2. Guidebook for Software Reliability Measurement and Testing

DTIC Science & Technology

1992-04-01

contractor’s existing data collection, analysis and corrective action system shall be utilized, with modification only as necessary to meet the...either from test or from analysis of field data . The procedures of MIL-STD-756B assume that the reliability of a 18 DEFINE IDENTIFY SOFTWARE LIFE CYCLE...to generate sufficient data to report a statistically valid reliability figure for a class of software. Casual data gathering accumulates data more

Orbit Software Suite

NASA Technical Reports Server (NTRS)

Osgood, Cathy; Williams, Kevin; Gentry, Philip; Brownfield, Dana; Hallstrom, John; Stuit, Tim

2012-01-01

Orbit Software Suite is used to support a variety of NASA/DM (Dependable Multiprocessor) mission planning and analysis activities on the IPS (Intrusion Prevention System) platform. The suite of Orbit software tools (Orbit Design and Orbit Dynamics) resides on IPS/Linux workstations, and is used to perform mission design and analysis tasks corresponding to trajectory/ launch window, rendezvous, and proximity operations flight segments. A list of tools in Orbit Software Suite represents tool versions established during/after the Equipment Rehost-3 Project.

Installing a Local Copy of the Reactome Web Site and Knowledgebase

PubMed Central

McKay, Sheldon J; Weiser, Joel

2015-01-01

The Reactome project builds, maintains, and publishes a knowledgebase of biological pathways. The information in the knowledgebase is gathered from the experts in the field, peer reviewed, and edited by Reactome editorial staff and then published to the Reactome Web site, http://www.reactome.org (see UNIT 8.7; Croft et al., 2013). The Reactome software is open source and builds on top of other open-source or freely available software. Reactome data and code can be freely downloaded in its entirety and the Web site installed locally. This allows for more flexible interrogation of the data and also makes it possible to add one’s own information to the knowledgebase. PMID:26087747

Wu-Tou Decoction in Rheumatoid Arthritis: Integrating Network Pharmacology and In Vivo Pharmacological Evaluation

PubMed Central

Guo, Qingqing; Zheng, Kang; Fan, Danping; Zhao, Yukun; Li, Li; Bian, Yanqin; Qiu, Xuemei; Liu, Xue; Zhang, Ge; Ma, Chaoying; He, Xiaojuan; Lu, Aiping

2017-01-01

Purpose: This study aimed to explore underlying action mechanism of Wu-Tou decoction (WTD) in rheumatoid arthritis (RA) through network pharmacology prediction and experimental verification. Methods: Chemical compounds and human target proteins of WTD as well as RA-related human genes were obtained from TCM Database @ Taiwan, PubChem and GenBank, respectively. Subsequently, molecular networks and canonical pathways presumably involved in the treatment of WTD on RA were generated by ingenuity pathway analysis (IPA) software. Furthermore, experimental validation was carried out with MIP-1β-induced U937 cell model and collagen induced arthritis (CIA) rat model. Results: CCR5 signaling pathway in macrophages was shown to be the top one shared signaling pathway associated with both cell immune response and cytokine signaling. In addition, protein kinase C (PKC) δ and p38 in this pathway were treated as target proteins of WTD in RA. In vitro experiments indicated that WTD inhibited MIP-1β-induced production of TNF-α, MIP-1α, and RANTES as well as phosphorylation of CCR5, PKC δ, and p38 in U937 cells. WTD treatment maintained the inhibitory effects on production of TNF-α and RANTES in MIP-1β-induced U937 cells after CCR5 knockdown. In vivo experiments demonstrated that WTD ameliorated symptoms in CIA rats, decreased the levels of IL-1β, IL-2, IL-6, TNF-α, MIP-1α, MIP-2, RANTES, and IP-10 in serum of CIA rats, as well as mRNA levels of MIP-1α, MIP-2, RANTES, and IP-10 in ankle joints of CIA rats. Furthermore, WTD also lowered the phosphorylation levels of CCR5, PKC δ and p38 in both ankle joints and macrophages in ankle joints from CIA rats. Conclusion: It was demonstrated in this research that WTD played a role in inhibiting inflammatory response in RA which was closely connected with the modulation effect of WTD on CCR5 signaling pathway in macrophages. PMID:28515692

FMT (Flight Software Memory Tracker) For Cassini Spacecraft-Software Engineering Using JAVA

NASA Technical Reports Server (NTRS)

Kan, Edwin P.; Uffelman, Hal; Wax, Allan H.

1997-01-01

The software engineering design of the Flight Software Memory Tracker (FMT) Tool is discussed in this paper. FMT is a ground analysis software set, consisting of utilities and procedures, designed to track the flight software, i.e., images of memory load and updatable parameters of the computers on-board Cassini spacecraft. FMT is implemented in Java.

Engineering Complex Embedded Systems with State Analysis and the Mission Data System

NASA Technical Reports Server (NTRS)

Ingham, Michel D.; Rasmussen, Robert D.; Bennett, Matthew B.; Moncada, Alex C.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.

Pilot Study of an Open-source Image Analysis Software for Automated Screening of Conventional Cervical Smears.

PubMed

Sanyal, Parikshit; Ganguli, Prosenjit; Barui, Sanghita; Deb, Prabal

2018-01-01

The Pap stained cervical smear is a screening tool for cervical cancer. Commercial systems are used for automated screening of liquid based cervical smears. However, there is no image analysis software used for conventional cervical smears. The aim of this study was to develop and test the diagnostic accuracy of a software for analysis of conventional smears. The software was developed using Python programming language and open source libraries. It was standardized with images from Bethesda Interobserver Reproducibility Project. One hundred and thirty images from smears which were reported Negative for Intraepithelial Lesion or Malignancy (NILM), and 45 images where some abnormality has been reported, were collected from the archives of the hospital. The software was then tested on the images. The software was able to segregate images based on overall nuclear: cytoplasmic ratio, coefficient of variation (CV) in nuclear size, nuclear membrane irregularity, and clustering. 68.88% of abnormal images were flagged by the software, as well as 19.23% of NILM images. The major difficulties faced were segmentation of overlapping cell clusters and separation of neutrophils. The software shows potential as a screening tool for conventional cervical smears; however, further refinement in technique is required.

Lessons Learned from Application of System and Software Level RAMS Analysis to a Space Control System

NASA Astrophysics Data System (ADS)

Silva, N.; Esper, A.

2012-01-01

The work presented in this article represents the results of applying RAMS analysis to a critical space control system, both at system and software levels. The system level RAMS analysis allowed the assignment of criticalities to the high level components, which was further refined by a tailored software level RAMS analysis. The importance of the software level RAMS analysis in the identification of new failure modes and its impact on the system level RAMS analysis is discussed. Recommendations of changes in the software architecture have also been proposed in order to reduce the criticality of the SW components to an acceptable minimum. The dependability analysis was performed in accordance to ECSS-Q-ST-80, which had to be tailored and complemented in some aspects. This tailoring will also be detailed in the article and lessons learned from the application of this tailoring will be shared, stating the importance to space systems safety evaluations. The paper presents the applied techniques, the relevant results obtained, the effort required for performing the tasks and the planned strategy for ROI estimation, as well as the soft skills required and acquired during these activities.

Off-the-shelf Control of Data Analysis Software

NASA Astrophysics Data System (ADS)

Wampler, S.

The Gemini Project must provide convenient access to data analysis facilities to a wide user community. The international nature of this community makes the selection of data analysis software particularly interesting, with staunch advocates of systems such as ADAM and IRAF among the users. Additionally, the continuing trends towards increased use of networked systems and distributed processing impose additional complexity. To meet these needs, the Gemini Project is proposing the novel approach of using low-cost, off-the-shelf software to abstract out both the control and distribution of data analysis from the functionality of the data analysis software. For example, the orthogonal nature of control versus function means that users might select analysis routines from both ADAM and IRAF as appropriate, distributing these routines across a network of machines. It is the belief of the Gemini Project that this approach results in a system that is highly flexible, maintainable, and inexpensive to develop. The Khoros visualization system is presented as an example of control software that is currently available for providing the control and distribution within a data analysis system. The visual programming environment provided with Khoros is also discussed as a means to providing convenient access to this control.

TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies.

PubMed

Klein, Johannes; Leupold, Stefan; Biegler, Ilona; Biedendieck, Rebekka; Münch, Richard; Jahn, Dieter

2012-09-01

Time-lapse imaging in combination with fluorescence microscopy techniques enable the investigation of gene regulatory circuits and uncovered phenomena like culture heterogeneity. In this context, computational image processing for the analysis of single cell behaviour plays an increasing role in systems biology and mathematical modelling approaches. Consequently, we developed a software package with graphical user interface for the analysis of single bacterial cell behaviour. A new software called TLM-Tracker allows for the flexible and user-friendly interpretation for the segmentation, tracking and lineage analysis of microbial cells in time-lapse movies. The software package, including manual, tutorial video and examples, is available as Matlab code or executable binaries at http://www.tlmtracker.tu-bs.de.

Failure-Modes-And-Effects Analysis Of Software Logic

NASA Technical Reports Server (NTRS)

Garcia, Danny; Hartline, Thomas; Minor, Terry; Statum, David; Vice, David

1996-01-01

Rigorous analysis applied early in design effort. Method of identifying potential inadequacies and modes and effects of failures caused by inadequacies (failure-modes-and-effects analysis or "FMEA" for short) devised for application to software logic.

ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

PubMed Central

Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

CAMBerVis: visualization software to support comparative analysis of multiple bacterial strains.

PubMed

Woźniak, Michał; Wong, Limsoon; Tiuryn, Jerzy

2011-12-01

A number of inconsistencies in genome annotations are documented among bacterial strains. Visualization of the differences may help biologists to make correct decisions in spurious cases. We have developed a visualization tool, CAMBerVis, to support comparative analysis of multiple bacterial strains. The software manages simultaneous visualization of multiple bacterial genomes, enabling visual analysis focused on genome structure annotations. The CAMBerVis software is freely available at the project website: http://bioputer.mimuw.edu.pl/camber. Input datasets for Mycobacterium tuberculosis and Staphylocacus aureus are integrated with the software as examples. m.wozniak@mimuw.edu.pl Supplementary data are available at Bioinformatics online.

Object-oriented productivity metrics

NASA Technical Reports Server (NTRS)

Connell, John L.; Eller, Nancy

1992-01-01

Software productivity metrics are useful for sizing and costing proposed software and for measuring development productivity. Estimating and measuring source lines of code (SLOC) has proven to be a bad idea because it encourages writing more lines of code and using lower level languages. Function Point Analysis is an improved software metric system, but it is not compatible with newer rapid prototyping and object-oriented approaches to software development. A process is presented here for counting object-oriented effort points, based on a preliminary object-oriented analysis. It is proposed that this approach is compatible with object-oriented analysis, design, programming, and rapid prototyping. Statistics gathered on actual projects are presented to validate the approach.

State analysis requirements database for engineering complex embedded systems

NASA Technical Reports Server (NTRS)

Bennett, Matthew B.; Rasmussen, Robert D.; Ingham, Michel D.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer's intent, potentially leading to software errors. This problem is addressed by a systems engineering tool called the State Analysis Database, which provides a tool for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using the State Analysis Database.

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

Acoustic Emission Analysis Applet (AEAA) Software

NASA Technical Reports Server (NTRS)

Nichols, Charles T.; Roth, Don J.

2013-01-01

NASA Glenn Research and NASA White Sands Test Facility have developed software supporting an automated pressure vessel structural health monitoring (SHM) system based on acoustic emissions (AE). The software, referred to as the Acoustic Emission Analysis Applet (AEAA), provides analysts with a tool that can interrogate data collected on Digital Wave Corp. and Physical Acoustics Corp. software using a wide spectrum of powerful filters and charts. This software can be made to work with any data once the data format is known. The applet will compute basic AE statistics, and statistics as a function of time and pressure (see figure). AEAA provides value added beyond the analysis provided by the respective vendors' analysis software. The software can handle data sets of unlimited size. A wide variety of government and commercial applications could benefit from this technology, notably requalification and usage tests for compressed gas and hydrogen-fueled vehicles. Future enhancements will add features similar to a "check engine" light on a vehicle. Once installed, the system will ultimately be used to alert International Space Station crewmembers to critical structural instabilities, but will have little impact to missions otherwise. Diagnostic information could then be transmitted to experienced technicians on the ground in a timely manner to determine whether pressure vessels have been impacted, are structurally unsound, or can be safely used to complete the mission.

A review of some problems in global-local stress analysis

NASA Technical Reports Server (NTRS)

Nelson, Richard B.

1989-01-01

The various types of local-global finite-element problems point out the need to develop a new generation of software. First, this new software needs to have a complete analysis capability, encompassing linear and nonlinear analysis of 1-, 2-, and 3-dimensional finite-element models, as well as mixed dimensional models. The software must be capable of treating static and dynamic (vibration and transient response) problems, including the stability effects of initial stress, and the software should be able to treat both elastic and elasto-plastic materials. The software should carry a set of optional diagnostics to assist the program user during model generation in order to help avoid obvious structural modeling errors. In addition, the program software should be well documented so the user has a complete technical reference for each type of element contained in the program library, including information on such topics as the type of numerical integration, use of underintegration, and inclusion of incompatible modes, etc. Some packaged information should also be available to assist the user in building mixed-dimensional models. An important advancement in finite-element software should be in the development of program modularity, so that the user can select from a menu various basic operations in matrix structural analysis.

Maintaining the Health of Software Monitors

NASA Technical Reports Server (NTRS)

Person, Suzette; Rungta, Neha

2013-01-01

Software health management (SWHM) techniques complement the rigorous verification and validation processes that are applied to safety-critical systems prior to their deployment. These techniques are used to monitor deployed software in its execution environment, serving as the last line of defense against the effects of a critical fault. SWHM monitors use information from the specification and implementation of the monitored software to detect violations, predict possible failures, and help the system recover from faults. Changes to the monitored software, such as adding new functionality or fixing defects, therefore, have the potential to impact the correctness of both the monitored software and the SWHM monitor. In this work, we describe how the results of a software change impact analysis technique, Directed Incremental Symbolic Execution (DiSE), can be applied to monitored software to identify the potential impact of the changes on the SWHM monitor software. The results of DiSE can then be used by other analysis techniques, e.g., testing, debugging, to help preserve and improve the integrity of the SWHM monitor as the monitored software evolves.

Taking the Observatory to the Astronomer

NASA Astrophysics Data System (ADS)

Bisque, T. M.

1997-05-01

Since 1992, Software Bisque's Remote Astronomy Software has been used by the Mt. Wilson Institute to allow interactive control of a 24" telescope and digital camera via modem. Software Bisque now introduces a comparable, relatively low-cost observatory system that allows powerful, yet "user-friendly" telescope and CCD camera control via the Internet. Utilizing software developed for the Windows 95/NT operating systems, the system offers point-and-click access to comprehensive celestial databases, extremely accurate telescope pointing, rapid download of digital CCD images by one or many users and flexible image processing software for data reduction and analysis. Our presentation will describe how the power of the personal computer has been leveraged to provide professional-level tools to the amateur astronomer, and include a description of this system's software and hardware components. The system software includes TheSky Astronomy Software?, CCDSoft CCD Astronomy Software?, TPoint Telescope Pointing Analysis System? software, Orchestrate? and, optionally, the RealSky CDs. The system hardware includes the Paramount GT-1100? Robotic Telescope Mount, as well as third party CCD cameras, focusers and optical tube assemblies.

Development of automation software for neutron activation analysis process in Malaysian nuclear agency

NASA Astrophysics Data System (ADS)

Yussup, N.; Rahman, N. A. A.; Ibrahim, M. M.; Mokhtar, M.; Salim, N. A. A.; Soh@Shaari, S. C.; Azman, A.

2017-01-01

Neutron Activation Analysis (NAA) process has been established in Malaysian Nuclear Agency (Nuclear Malaysia) since 1980s. Most of the procedures established especially from sample registration to sample analysis are performed manually. These manual procedures carried out by the NAA laboratory personnel are time consuming and inefficient. Hence, a software to support the system automation is developed to provide an effective method to replace redundant manual data entries and produce faster sample analysis and calculation process. This paper describes the design and development of automation software for NAA process which consists of three sub-programs. The sub-programs are sample registration, hardware control and data acquisition; and sample analysis. The data flow and connection between the sub-programs will be explained. The software is developed by using National Instrument LabView development package.

FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

PubMed

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

Software and package applicating for network meta-analysis: A usage-based comparative study.

PubMed

Xu, Chang; Niu, Yuming; Wu, Junyi; Gu, Huiyun; Zhang, Chao

2017-12-21

To compare and analyze the characteristics and functions of software applications for network meta-analysis (NMA). PubMed, EMbase, The Cochrane Library, the official websites of Bayesian inference Using Gibbs Sampling (BUGS), Stata and R, and Google were searched to collect the software and packages for performing NMA; software and packages published up to March 2016 were included. After collecting the software, packages, and their user guides, we used the software and packages to calculate a typical example. All characteristics, functions, and computed results were compared and analyzed. Ten types of software were included, including programming and non-programming software. They were developed mainly based on Bayesian or frequentist theory. Most types of software have the characteristics of easy operation, easy mastery, exact calculation, or excellent graphing. However, there was no single software that performed accurate calculations with superior graphing; this could only be achieved through the combination of two or more types of software. This study suggests that the user should choose the appropriate software according to personal programming basis, operational habits, and financial ability. Then, the choice of the combination of BUGS and R (or Stata) software to perform the NMA is considered. © 2017 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.

Toward Intelligent Software Defect Detection

NASA Technical Reports Server (NTRS)

Benson, Markland J.

2011-01-01

Source code level software defect detection has gone from state of the art to a software engineering best practice. Automated code analysis tools streamline many of the aspects of formal code inspections but have the drawback of being difficult to construct and either prone to false positives or severely limited in the set of defects that can be detected. Machine learning technology provides the promise of learning software defects by example, easing construction of detectors and broadening the range of defects that can be found. Pinpointing software defects with the same level of granularity as prominent source code analysis tools distinguishes this research from past efforts, which focused on analyzing software engineering metrics data with granularity limited to that of a particular function rather than a line of code.

Structural Analysis Using NX Nastran 9.0

NASA Technical Reports Server (NTRS)

Rolewicz, Benjamin M.

2014-01-01

NX Nastran is a powerful Finite Element Analysis (FEA) software package used to solve linear and non-linear models for structural and thermal systems. The software, which consists of both a solver and user interface, breaks down analysis into four files, each of which are important to the end results of the analysis. The software offers capabilities for a variety of types of analysis, and also contains a respectable modeling program. Over the course of ten weeks, I was trained to effectively implement NX Nastran into structural analysis and refinement for parts of two missions at NASA's Kennedy Space Center, the Restore mission and the Orion mission.

A Virtual World of Visualization

NASA Technical Reports Server (NTRS)

1998-01-01

In 1990, Sterling Software, Inc., developed the Flow Analysis Software Toolkit (FAST) for NASA Ames on contract. FAST is a workstation based modular analysis and visualization tool. It is used to visualize and animate grids and grid oriented data, typically generated by finite difference, finite element and other analytical methods. FAST is now available through COSMIC, NASA's software storehouse.

A parallel and sensitive software tool for methylation analysis on multicore platforms.

PubMed

Tárraga, Joaquín; Pérez, Mariano; Orduña, Juan M; Duato, José; Medina, Ignacio; Dopazo, Joaquín

2015-10-01

DNA methylation analysis suffers from very long processing time, as the advent of Next-Generation Sequencers has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. As it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed. We present a new software tool, called HPG-Methyl, which efficiently maps bisulphite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows-Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPG-Methyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulphite reads. Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to anonymous@clariano.uv.es (password 'anonymous'). juan.orduna@uv.es or jdopazo@cipf.es. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.

PubMed

George, Kevin W; Chen, Amy; Jain, Aakriti; Batth, Tanveer S; Baidoo, Edward E K; Wang, George; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek Soon

2014-08-01

The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways. © 2014 Wiley Periodicals, Inc.

Spatial-Temporal Mapping of the T Cell Receptor NF-kappaB Signaling Pathway

DTIC Science & Technology

2006-05-30

Lasos), a 700/488-nm excitation filter and a 500– 550-nm emission filter. Multiphoton PA-GFP activation was performed using the Aim software bleach ...Bcl10 was fused to a PA-GFP [65], and MALT1 was fused to the reef coral fluorescent protein, monomeric Kusabira-Orange (mKO) [70]. D10 T-cells

What Videogame Making Can Teach Us about Literacy and Learning: Alternative Pathways into Participatory Culture

ERIC Educational Resources Information Center

Peppler, Kylie A.; Kafai, Yasmin B.

2007-01-01

In this paper we articulate an alternative approach to look at video games and learning to become a creator and contributor in the digital culture. Previous discussions have focused mostly on playing games and learning. Here, we discuss game making approaches and their benefits for illuminating game preferences and learning both software design…

Automated Diatom Analysis Applied to Traditional Light Microscopy: A Proof-of-Concept Study

NASA Astrophysics Data System (ADS)

Little, Z. H. L.; Bishop, I.; Spaulding, S. A.; Nelson, H.; Mahoney, C.

2017-12-01

Diatom identification and enumeration by high resolution light microscopy is required for many areas of research and water quality assessment. Such analyses, however, are both expertise and labor-intensive. These challenges motivate the need for an automated process to efficiently and accurately identify and enumerate diatoms. Improvements in particle analysis software have increased the likelihood that diatom enumeration can be automated. VisualSpreadsheet software provides a possible solution for automated particle analysis of high-resolution light microscope diatom images. We applied the software, independent of its complementary FlowCam hardware, to automated analysis of light microscope images containing diatoms. Through numerous trials, we arrived at threshold settings to correctly segment 67% of the total possible diatom valves and fragments from broad fields of view. (183 light microscope images were examined containing 255 diatom particles. Of the 255 diatom particles present, 216 diatoms valves and fragments of valves were processed, with 170 properly analyzed and focused upon by the software). Manual analysis of the images yielded 255 particles in 400 seconds, whereas the software yielded a total of 216 particles in 68 seconds, thus highlighting that the software has an approximate five-fold efficiency advantage in particle analysis time. As in past efforts, incomplete or incorrect recognition was found for images with multiple valves in contact or valves with little contrast. The software has potential to be an effective tool in assisting taxonomists with diatom enumeration by completing a large portion of analyses. Benefits and limitations of the approach are presented to allow for development of future work in image analysis and automated enumeration of traditional light microscope images containing diatoms.

The integration of the risk management process with the lifecycle of medical device software.

PubMed

Pecoraro, F; Luzi, D

2014-01-01

The application of software in the Medical Device (MD) domain has become central to the improvement of diagnoses and treatments. The new European regulations that specifically address software as an important component of MD, require complex procedures to make software compliant with safety requirements, introducing thereby new challenges in the qualification and classification of MD software as well as in the performance of risk management activities. Under this perspective, the aim of this paper is to propose an integrated framework that combines the activities to be carried out by the manufacturer to develop safe software within the development lifecycle based on the regulatory requirements reported in US and European regulations as well as in the relevant standards and guidelines. A comparative analysis was carried out to identify the main issues related to the application of the current new regulations. In addition, standards and guidelines recently released to harmonise procedures for the validation of MD software have been used to define the risk management activities to be carried out by the manufacturer during the software development process. This paper highlights the main issues related to the qualification and classification of MD software, providing an analysis of the different regulations applied in Europe and the US. A model that integrates the risk management process within the software development lifecycle has been proposed too. It is based on regulatory requirements and considers software risk analysis as a central input to be managed by the manufacturer already at the initial stages of the software design, in order to prevent MD failures. Relevant changes in the process of MD development have been introduced with the recognition of software being an important component of MDs as stated in regulations and standards. This implies the performance of highly iterative processes that have to integrate the risk management in the framework of software development. It also makes it necessary to involve both medical and software engineering competences to safeguard patient and user safety.

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.

The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core.

PubMed

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2018-03-09

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. The design of Version 2 differs from Version 1 principally in allowing new MathML constructs, making more child elements optional, and adding identifiers to all SBML elements instead of only selected elements. Other materials and software are available from the SBML project website at http://sbml.org/.

Gene expression profile after activation of RIG-I in 5'ppp-dsRNA challenged DF1.

PubMed

Chen, Yang; Xu, Qi; Li, Yang; Liu, Ran; Huang, Zhengyang; Wang, Bin; Chen, Guohong

2016-12-01

Retinoic acid inducible gene I (RIG-I) can recognize influenza viruses and evoke the innate immune response. RIG-I is absent in the chicken genome, but is conserved in the genome of ducks. Lack of RIG-I renders chickens more susceptible to avian influenza infection, and the clinical symptoms are more prominent than in other poultry. It is unknown whether introduction of duck RIG-I into chicken cells can establish the immunity as is seen in ducks and the role of RIG-I in established immunity is unknown. In this study, a chicken cell strain with stable expression of duRIG-I was established by lentiviral infection, giving DF1/LV5-RIG-I, and a control strain DF1/LV5 was established in parallel. To verify stable, high level expression of duRIG-I in DF1 cells, the levels of duRIG-I mRNA and protein were determined by real-time RT-PCR and Western blot, respectively. Further, 5'triphosphate double stranded RNA (5'ppp-dsRNA) was used to mimic an RNA virus infection and the infected DF1/LV5-RIG-I and DF1/LV5 cells were subjected to high-throughput RNA-sequencing, which yielded 193.46 M reads and 39.07 G bases. A total of 278 differentially expressed genes (DEGs), i.e., duRIG-I-mediated responsive genes, were identified by RNA-seq. Among the 278 genes, 120 DEGs are annotated in the KEGG database, and the most reliable KEGG pathways are likely to be the signaling pathways of RIG-I like receptors. Functional analysis by Gene ontology (GO) indicates that the functions of these DEGs are primarily related to Type I interferon (IFN) signaling, IFN-β-mediated cellular responses and up-regulation of the RIG-I signaling pathway. Based on the shared genes among different pathways, a network representing crosstalk between RIG-I and other signaling pathways was constructed using Cytoscape software. The network suggests that RIG-mediated pathway may crosstalk with the Jak-STAT signaling pathway, Toll-like receptor signaling pathway, Wnt signaling pathway, ubiquitin-mediated proteolysis and MAPK signaling pathway during the transduction of antiviral signals. After screening, a group of key responsive genes in RIG-I-mediated signaling pathways, such as ISG12-2, Mx1, IFIT5, TRIM25, USP18, STAT1, STAT2, IRF1, IRF7 and IRF8, were tested for differential expression by real-time RT-PCR. In summary, by combining our results and the current literature, we propose a RIG-I-mediated signaling network in chickens. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolomic Profiling of the Synergistic Effects of Melittin in Combination with Cisplatin on Ovarian Cancer Cells

PubMed Central

Alonezi, Sanad; Tusiimire, Jonans; Wallace, Jennifer; Dufton, Mark J.; Parkinson, John A.; Young, Louise C.; Clements, Carol J.; Park, Jin-Kyu; Jeon, Jong-Woon; Ferro, Valerie A.; Watson, David G.

2017-01-01

Melittin, the main peptide present in bee venom, has been proposed as having potential for anticancer therapy; the addition of melittin to cisplatin, a first line treatment for ovarian cancer, may increase the therapeutic response in cancer treatment via synergy, resulting in improved tolerability, reduced relapse, and decreased drug resistance. Thus, this study was designed to compare the metabolomic effects of melittin in combination with cisplatin in cisplatin-sensitive (A2780) and resistant (A2780CR) ovarian cancer cells. Liquid chromatography (LC) coupled with mass spectrometry (MS) was applied to identify metabolic changes in A2780 (combination treatment 5 μg/mL melittin + 2 μg/mL cisplatin) and A2780CR (combination treatment 2 μg/mL melittin + 10 μg/mL cisplatin) cells. Principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) multivariate data analysis models were produced using SIMCA-P software. All models displayed good separation between experimental groups and high-quality goodness of fit (R2) and goodness of prediction (Q2), respectively. The combination treatment induced significant changes in both cell lines involving reduction in the levels of metabolites in the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, purine and pyrimidine metabolism, and the arginine/proline pathway. The combination of melittin with cisplatin that targets these pathways had a synergistic effect. The melittin-cisplatin combination had a stronger effect on the A2780 cell line in comparison with the A2780CR cell line. The metabolic effects of melittin and cisplatin in combination were very different from those of each agent alone. PMID:28420117

ImagePy: an open-source, Python-based and platform-independent software package for boimage analysis.

PubMed

Wang, Anliang; Yan, Xiaolong; Wei, Zhijun

2018-04-27

This note presents the design of a scalable software package named ImagePy for analysing biological images. Our contribution is concentrated on facilitating extensibility and interoperability of the software through decoupling the data model from the user interface. Especially with assistance from the Python ecosystem, this software framework makes modern computer algorithms easier to be applied in bioimage analysis. ImagePy is free and open source software, with documentation and code available at https://github.com/Image-Py/imagepy under the BSD license. It has been tested on the Windows, Mac and Linux operating systems. wzjdlut@dlut.edu.cn or yxdragon@imagepy.org.

Advanced Automation for Ion Trap Mass Spectrometry-New Opportunities for Real-Time Autonomous Analysis

NASA Technical Reports Server (NTRS)

Palmer, Peter T.; Wong, C. M.; Salmonson, J. D.; Yost, R. A.; Griffin, T. P.; Yates, N. A.; Lawless, James G. (Technical Monitor)

1994-01-01

The utility of MS/MS for both target compound analysis and the structure elucidation of unknowns has been described in a number of references. A broader acceptance of this technique has not yet been realized as it requires large, complex, and costly instrumentation which has not been competitive with more conventional techniques. Recent advancements in ion trap mass spectrometry promise to change this situation. Although the ion trap's small size, sensitivity, and ability to perform multiple stages of mass spectrometry have made it eminently suitable for on-line, real-time monitoring applications, advance automation techniques are required to make these capabilities more accessible to non-experts. Towards this end we have developed custom software for the design and implementation of MS/MS experiments. This software allows the user to take full advantage of the ion trap's versatility with respect to ionization techniques, scan proxies, and ion accumulation/ejection methods. Additionally, expert system software has been developed for autonomous target compound analysis. This software has been linked to ion trap control software and a commercial data system to bring all of the steps in the analysis cycle under control of the expert system. These software development efforts and their utilization for a number of trace analysis applications will be described.

Introducing a New Software for Geodetic Analysis

NASA Astrophysics Data System (ADS)

Hjelle, G. A.; Dähnn, M.; Fausk, I.; Kirkvik, A. S.; Mysen, E.

2016-12-01

At the Norwegian Mapping Authority, we are currently developing Where, a newsoftware for geodetic analysis. Where is built on our experiences with theGeosat software, and will be able to analyse and combine data from VLBI, SLR,GNSS and DORIS. The software is mainly written in Python which has proved veryfruitful. The code is quick to write and the architecture is easily extendableand maintainable. The Python community provides a rich eco-system of tools fordoing data-analysis, including effective data storage and powerfulvisualization. Python interfaces well with other languages so that we can easilyreuse existing, well-tested code like the SOFA and IERS libraries. This presentation will show some of the current capabilities of Where,including benchmarks against other software packages. In addition we will reporton some simple investigations we have done using the software, and outline ourplans for further progress.

Capi text V.1--data analysis software for nailfold skin capillaroscopy.

PubMed

Dobrev, Hristo P

2007-01-01

Nailfold skin capillaroscopy is a simple non-invasive method used to assess conditions of disturbed microcirculation such as Raynaud's phenomenon, acrocyanosis, perniones, connective tissue diseases, psoriasis, diabetes mellitus, neuropathy and vibration disease. To develop data analysis software aimed at assisting the documentation and analysis of a capillaroscopic investigation. SOFTWARE DESCRIPTION: The programme is based on a modular principle. The module "Nomenclatures" includes menus for the patients' data. The module "Examinations" includes menus for all general and specific aspects of the medical examination and capillaroscopic investigations. The modules "Settings" and "Information" include customization menus for the programme. The results of nailfold capillaroscopy can be printed in a short or expanded form. This software allows physicians to perform quick search by using various specified criteria and prepare analyses and reports. This software programme will facilitate any practitioner who performs nailfold skin capillaroscopy.