XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

BIOZON: a system for unification, management and analysis of heterogeneous biological data.

PubMed

Birkland, Aaron; Yona, Golan

2006-02-15

Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability. Here we present a system (Biozon) that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways). It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated. The Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

PubMed

Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Computational approaches to metabolic engineering utilizing systems biology and synthetic biology.

PubMed

Fong, Stephen S

2014-08-01

Metabolic engineering modifies cellular function to address various biochemical applications. Underlying metabolic engineering efforts are a host of tools and knowledge that are integrated to enable successful outcomes. Concurrent development of computational and experimental tools has enabled different approaches to metabolic engineering. One approach is to leverage knowledge and computational tools to prospectively predict designs to achieve the desired outcome. An alternative approach is to utilize combinatorial experimental tools to empirically explore the range of cellular function and to screen for desired traits. This mini-review focuses on computational systems biology and synthetic biology tools that can be used in combination for prospective in silico strain design.

Influence of using challenging tasks in biology classrooms on students' cognitive knowledge structure: an empirical video study

NASA Astrophysics Data System (ADS)

Nawani, Jigna; Rixius, Julia; Neuhaus, Birgit J.

2016-08-01

Empirical analysis of secondary biology classrooms revealed that, on average, 68% of teaching time in Germany revolved around processing tasks. Quality of instruction can thus be assessed by analyzing the quality of tasks used in classroom discourse. This quasi-experimental study analyzed how teachers used tasks in 38 videotaped biology lessons pertaining to the topic 'blood and circulatory system'. Two fundamental characteristics used to analyze tasks include: (1) required cognitive level of processing (e.g. low level information processing: repetiition, summary, define, classify and high level information processing: interpret-analyze data, formulate hypothesis, etc.) and (2) complexity of task content (e.g. if tasks require use of factual, linking or concept level content). Additionally, students' cognitive knowledge structure about the topic 'blood and circulatory system' was measured using student-drawn concept maps (N = 970 students). Finally, linear multilevel models were created with high-level cognitive processing tasks and higher content complexity tasks as class-level predictors and students' prior knowledge, students' interest in biology, and students' interest in biology activities as control covariates. Results showed a positive influence of high-level cognitive processing tasks (β = 0.07; p < .01) on students' cognitive knowledge structure. However, there was no observed effect of higher content complexity tasks on students' cognitive knowledge structure. Presented findings encourage the use of high-level cognitive processing tasks in biology instruction.

From Noise to Order: The Psychological Development of Knowledge and Phenocopy in Biology

ERIC Educational Resources Information Center

Piaget, Jean

1975-01-01

Shows that one of the most general processes in the development of cognitive structures consists in replacing exogenous knowledge by endogenous reconstructions that reconstitute the same forms but incorporate them into systems whose internal composition is a pre-requisite. Biologically equivalent process is discussed. (Author/AM)

Learning Biology by Designing

ERIC Educational Resources Information Center

Janssen, Fred; Waarlo, Arend Jan

2010-01-01

According to a century-old tradition in biological thinking, organisms can be considered as being optimally designed. In modern biology this idea still has great heuristic value. In evolutionary biology a so-called design heuristic has been formulated which provides guidance to researchers in the generation of knowledge about biological systems.…

Promoting Student Teachers' Content Related Knowledge in Teaching Systems Thinking: Measuring Effects of an Intervention through Evaluating a Videotaped Lesson

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Kramer, Tim; Hörsch, Christian; Schuler, Stephan; Rieß, Werner

2016-01-01

The understanding of complex, dynamic and animate systems has a special standing in education for sustainable development and biology. Thus one important role of science teacher education is to promote student teachers' Content Related Knowledge (CRK) for teaching systems thinking, consisting of extensive Content Knowledge (CK) and well formed…

Reputation-based collaborative network biology.

PubMed

Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Fields, R Brett; Hayes, William; Hoeng, Julia; Park, Jennifer S; Peitsch, Manuel C

2015-01-01

A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities.

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

PubMed Central

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2013-10-11

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

From systems biology to systems biomedicine.

PubMed

Antony, Paul M A; Balling, Rudi; Vlassis, Nikos

2012-08-01

Systems Biology is about combining theory, technology, and targeted experiments in a way that drives not only data accumulation but knowledge as well. The challenge in Systems Biomedicine is to furthermore translate mechanistic insights in biological systems to clinical application, with the central aim of improving patients' quality of life. The challenge is to find theoretically well-chosen models for the contextually correct and intelligible representation of multi-scale biological systems. In this review, we discuss the current state of Systems Biology, highlight the emergence of Systems Biomedicine, and highlight some of the topics and views that we think are important for the efficient application of Systems Theory in Biomedicine. Copyright © 2011 Elsevier Ltd. All rights reserved.

When one model is not enough: combining epistemic tools in systems biology.

PubMed

Green, Sara

2013-06-01

In recent years, the philosophical focus of the modeling literature has shifted from descriptions of general properties of models to an interest in different model functions. It has been argued that the diversity of models and their correspondingly different epistemic goals are important for developing intelligible scientific theories (Leonelli, 2007; Levins, 2006). However, more knowledge is needed on how a combination of different epistemic means can generate and stabilize new entities in science. This paper will draw on Rheinberger's practice-oriented account of knowledge production. The conceptual repertoire of Rheinberger's historical epistemology offers important insights for an analysis of the modelling practice. I illustrate this with a case study on network modeling in systems biology where engineering approaches are applied to the study of biological systems. I shall argue that the use of multiple representational means is an essential part of the dynamic of knowledge generation. It is because of-rather than in spite of-the diversity of constraints of different models that the interlocking use of different epistemic means creates a potential for knowledge production. Copyright © 2013 Elsevier Ltd. All rights reserved.

Applications of systems biology towards microbial fuel production.

PubMed

Gowen, Christopher M; Fong, Stephen S

2011-10-01

Harnessing the immense natural diversity of biological functions for economical production of fuel has enormous potential benefits. Inevitably, however, the native capabilities for any given organism must be modified to increase the productivity or efficiency of a biofuel bioprocess. From a broad perspective, the challenge is to sufficiently understand the details of cellular functionality to be able to prospectively predict and modify the cellular function of a microorganism. Recent advances in experimental and computational systems biology approaches can be used to better understand cellular level function and guide future experiments. With pressure to quickly develop viable, renewable biofuel processes a balance must be maintained between obtaining depth of biological knowledge and applying that knowledge. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

The mammary gland in domestic ruminants: a systems biology perspective.

PubMed

Ferreira, Ana M; Bislev, Stine L; Bendixen, Emøke; Almeida, André M

2013-12-06

Milk and dairy products are central elements in the human diet. It is estimated that 108kg of milk per year are consumed per person worldwide. Therefore, dairy production represents a relevant fraction of the economies of many countries, being cattle, sheep, goat, water buffalo, and other ruminants the main species used worldwide. An adequate management of dairy farming cannot be achieved without the knowledge on the biological mechanisms behind lactation in ruminants. Thus, understanding the morphology, development and regulation of the mammary gland in health, disease and production is crucial. Presently, innovative and high-throughput technologies such as genomics, transcriptomics, proteomics and metabolomics allow a much broader and detailed knowledge on such issues. Additionally, the application of a systems biology approach to animal science is vastly growing, as new advances in one field of specialization or animal species lead to new lines of research in other areas or/and are expanded to other species. This article addresses how modern research approaches may help us understand long-known issues in mammary development, lactation biology and dairy production. Dairy production depends upon the knowledge of the morphology and regulation of the mammary gland and lactation. High-throughput technologies allow a much broader and detailed knowledge on the biology of the mammary gland. This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production. In the context of mammary gland "omics"-based research, the integration of results using a Systems Biology Approach is of key importance. © 2013.

Adverse outcome pathway (AOP) development I: Strategies and principles

EPA Science Inventory

An adverse outcome pathway (AOP) is a conceptual framework that organizes existing knowledge concerning biologically plausible, and empirically-supported, links between molecular-level perturbation of a biological system and an adverse outcome at a level of biological organizatio...

Reverse engineering systems models of regulation: discovery, prediction and mechanisms.

PubMed

Ashworth, Justin; Wurtmann, Elisabeth J; Baliga, Nitin S

2012-08-01

Biological systems can now be understood in comprehensive and quantitative detail using systems biology approaches. Putative genome-scale models can be built rapidly based upon biological inventories and strategic system-wide molecular measurements. Current models combine statistical associations, causative abstractions, and known molecular mechanisms to explain and predict quantitative and complex phenotypes. This top-down 'reverse engineering' approach generates useful organism-scale models despite noise and incompleteness in data and knowledge. Here we review and discuss the reverse engineering of biological systems using top-down data-driven approaches, in order to improve discovery, hypothesis generation, and the inference of biological properties. Copyright © 2011 Elsevier Ltd. All rights reserved.

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

PubMed

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

PubMed Central

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189

Knowledge of Adverse Drug Reaction Reporting and the Pharmacovigilance of Biological Medicines: A Survey of Healthcare Professionals in Ireland.

PubMed

O'Callaghan, J; Griffin, B T; Morris, J M; Bermingham, Margaret

2018-06-01

In Europe, changes to pharmacovigilance legislation, which include additional monitoring of medicines, aim to optimise adverse drug reaction (ADR) reporting systems. The legislation also makes provisions related to the traceability of biological medicines. The objective of this study was to assess (i) knowledge and general experience of ADR reporting, (ii) knowledge, behaviours, and attitudes related to the pharmacovigilance of biologicals, and (iii) awareness of additional monitoring among healthcare professionals (HCPs) in Ireland. Hospital doctors (n = 88), general practitioners (GPs) (n = 197), nurses (n = 104) and pharmacists (n = 309) completed an online questionnaire. There were differences in mean knowledge scores relating to ADR reporting and the pharmacovigilance of biologicals among the HCP groups. The majority of HCPs who use biological medicines in their practice generally record biologicals by brand name but practice behaviours relating to batch number recording differed between some professions. HCPs consider batch number recording to be valuable but also regard it as being more difficult than brand name recording. Most respondents were aware of the concept of additional monitoring but awareness rates differed between some groups. Among those who knew about additional monitoring, there was higher awareness of the inverted black triangle symbol among pharmacists (> 86.4%) compared with hospital doctors (35.1%), GPs (35.6%), and nurses (14.9%). Hospital pharmacists had more experience and knowledge of ADR reporting than other practising HCPs. This study highlights the important role hospital pharmacists play in post-marketing surveillance. There is a need to increase pharmacovigilance awareness of biological medicines and improve systems to support their batch traceability.

Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics

PubMed Central

Huang, Jingshan; Dou, Dejing; Dang, Jiangbo; Pardue, J Harold; Qin, Xiao; Huan, Jun; Gerthoffer, William T; Tan, Ming

2012-01-01

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research. PMID:22371823

Bioinformatics workflows and web services in systems biology made easy for experimentalists.

PubMed

Jimenez, Rafael C; Corpas, Manuel

2013-01-01

Workflows are useful to perform data analysis and integration in systems biology. Workflow management systems can help users create workflows without any previous knowledge in programming and web services. However the computational skills required to build such workflows are usually above the level most biological experimentalists are comfortable with. In this chapter we introduce workflow management systems that reuse existing workflows instead of creating them, making it easier for experimentalists to perform computational tasks.

Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2.

PubMed

Mi, Huaiyu; Schreiber, Falk; Moodie, Stuart; Czauderna, Tobias; Demir, Emek; Haw, Robin; Luna, Augustin; Le Novère, Nicolas; Sorokin, Anatoly; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

A new organismal systems biology: how animals walk the tight rope between stability and change.

PubMed

Padilla, Dianna K; Tsukimura, Brian

2014-07-01

The amount of knowledge in the biological sciences is growing at an exponential rate. Simultaneously, the incorporation of new technologies in gathering scientific information has greatly accelerated our capacity to ask, and answer, new questions. How do we, as organismal biologists, meet these challenges, and develop research strategies that will allow us to address the grand challenge question: how do organisms walk the tightrope between stability and change? Organisms and organismal systems are complex, and multi-scale in both space and time. It is clear that addressing major questions about organismal biology will not come from "business as usual" approaches. Rather, we require the collaboration of a wide range of experts and integration of biological information with more quantitative approaches traditionally found in engineering and applied mathematics. Research programs designed to address grand challenge questions will require deep knowledge and expertise within subfields of organismal biology, collaboration and integration among otherwise disparate areas of research, and consideration of organisms as integrated systems. Our ability to predict which features of complex integrated systems provide the capacity to be robust in changing environments is poorly developed. A predictive organismal biology is needed, but will require more quantitative approaches than are typical in biology, including complex systems-modeling approaches common to engineering. This new organismal systems biology will have reciprocal benefits for biologists, engineers, and mathematicians who address similar questions, including those working on control theory and dynamical systems biology, and will develop the tools we need to address the grand challenge questions of the 21st century. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Causality, randomness, intelligibility, and the epistemology of the cell.

PubMed

Dougherty, Edward R; Bittner, Michael L

2010-06-01

Because the basic unit of biology is the cell, biological knowledge is rooted in the epistemology of the cell, and because life is the salient characteristic of the cell, its epistemology must be centered on its livingness, not its constituent components. The organization and regulation of these components in the pursuit of life constitute the fundamental nature of the cell. Thus, regulation sits at the heart of biological knowledge of the cell and the extraordinary complexity of this regulation conditions the kind of knowledge that can be obtained, in particular, the representation and intelligibility of that knowledge. This paper is essentially split into two parts. The first part discusses the inadequacy of everyday intelligibility and intuition in science and the consequent need for scientific theories to be expressed mathematically without appeal to commonsense categories of understanding, such as causality. Having set the backdrop, the second part addresses biological knowledge. It briefly reviews modern scientific epistemology from a general perspective and then turns to the epistemology of the cell. In analogy with a multi-faceted factory, the cell utilizes a highly parallel distributed control system to maintain its organization and regulate its dynamical operation in the face of both internal and external changes. Hence, scientific knowledge is constituted by the mathematics of stochastic dynamical systems, which model the overall relational structure of the cell and how these structures evolve over time, stochasticity being a consequence of the need to ignore a large number of factors while modeling relatively few in an extremely complex environment.

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

PubMed Central

Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

2011-01-01

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Fostering synergy between cell biology and systems biology.

PubMed

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Knowledge Discovery from Biomedical Ontologies in Cross Domains.

PubMed

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.

Knowledge Discovery from Biomedical Ontologies in Cross Domains

PubMed Central

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262

A Biochemistry and Molecular Biology Experiment and Evaluation System for Biotechnology Specialty Students: An Effective Evaluation System to Improve the Biochemistry and Molecular Biology Experiment Teaching

ERIC Educational Resources Information Center

Li, Suxia; Wu, Haizhen; Zhao, Jian; Ou, Ling; Zhang, Yuanxing

2010-01-01

In an effort to achieve high success in knowledge and technique acquisition as a whole, a biochemistry and molecular biology experiment was established for high-grade biotechnology specialty students after they had studied essential theory and received proper technique training. The experiment was based on cloning and expression of alkaline…

Biological standards for the Knowledge-Based BioEconomy: What is at stake.

PubMed

de Lorenzo, Víctor; Schmidt, Markus

2018-01-25

The contribution of life sciences to the Knowledge-Based Bioeconomy (KBBE) asks for the transition of contemporary, gene-based biotechnology from being a trial-and-error endeavour to becoming an authentic branch of engineering. One requisite to this end is the need for standards to measure and represent accurately biological functions, along with languages for data description and exchange. However, the inherent complexity of biological systems and the lack of quantitative tradition in the field have largely curbed this enterprise. Fortunately, the onset of systems and synthetic biology has emphasized the need for standards not only to manage omics data, but also to increase reproducibility and provide the means of engineering living systems in earnest. Some domains of biotechnology can be easily standardized (e.g. physical composition of DNA sequences, tools for genome editing, languages to encode workflows), while others might be standardized with some dedicated research (e.g. biological metrology, operative systems for bio-programming cells) and finally others will require a considerable effort, e.g. defining the rules that allow functional composition of biological activities. Despite difficulties, these are worthy attempts, as the history of technology shows that those who set/adopt standards gain a competitive advantage over those who do not. Copyright © 2017 Elsevier B.V. All rights reserved.

The human biology--saturated with experience.

PubMed

Getz, Linn; Kirkengen, Anna Luise; Ulvestad, Elling

2011-04-08

The human being is a self-reflecting, relationship-oriented, goal-directed organism in search of meaning. The process of coordinating and developing knowledge about how experience associated with self-conscience, relationships and values can contribute to development of health and disease is a great challenge for the medical profession. We present a theory-guided synthesis of new scientific knowledge from fields such as epigenetics, psycho-neuro-endocrino-immunology, stress research and systems biology. The sources are articles in acknowledged journals and books, chosen to provide insight into associations between life history (biography) and the human body (biology) in a wide sense. Research shows that information about biography, i.e. experienced meaning and relationships, is literally incorporated into the human organism. Epigenetics illustrates the fundamental biological potential for context-dependent adaptation. Further, studies have shown that different types of existential strain may disturb systems for human physiological adaptation, affect structures in the brain and subsequently render the organism vulnerable for disease. However, a sense of belonging and a perception of being supported and acknowledged can contribute to strengthening or restoring health. The traditional approach to increasing biomedical knowledge has prevented insight into the medical significance of experience. The new knowledge necessitates a reorientation of theory and practice within the medical profession both with respect to individuals and society.

HVDC power transmission environmental issues review

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

Bailey, W.H.; Weil, D.E.; Stewart, J.R.

1997-04-01

This report strives to define the various environmental effects associated with HVDC lines, discusses the current knowledge of their potential effects on biological and non-biological systems, and compares these effects associated with ac lines where appropriate.

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering.

PubMed

Teixeira, Ana P; Carinhas, Nuno; Dias, João M L; Cruz, Pedro; Alves, Paula M; Carrondo, Manuel J T; Oliveira, Rui

2007-12-01

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.

Causality, Randomness, Intelligibility, and the Epistemology of the Cell

PubMed Central

Dougherty, Edward R; Bittner, Michael L

2010-01-01

Because the basic unit of biology is the cell, biological knowledge is rooted in the epistemology of the cell, and because life is the salient characteristic of the cell, its epistemology must be centered on its livingness, not its constituent components. The organization and regulation of these components in the pursuit of life constitute the fundamental nature of the cell. Thus, regulation sits at the heart of biological knowledge of the cell and the extraordinary complexity of this regulation conditions the kind of knowledge that can be obtained, in particular, the representation and intelligibility of that knowledge. This paper is essentially split into two parts. The first part discusses the inadequacy of everyday intelligibility and intuition in science and the consequent need for scientific theories to be expressed mathematically without appeal to commonsense categories of understanding, such as causality. Having set the backdrop, the second part addresses biological knowledge. It briefly reviews modern scientific epistemology from a general perspective and then turns to the epistemology of the cell. In analogy with a multi-faceted factory, the cell utilizes a highly parallel distributed control system to maintain its organization and regulate its dynamical operation in the face of both internal and external changes. Hence, scientific knowledge is constituted by the mathematics of stochastic dynamical systems, which model the overall relational structure of the cell and how these structures evolve over time, stochasticity being a consequence of the need to ignore a large number of factors while modeling relatively few in an extremely complex environment. PMID:21119887

From the Director: The Joy of Science, the Courage of Research

MedlinePlus

... Dr. Zerhouni , one that combines an appreciation of biological complexity with the fearless search for scientific knowledge. ... techniques for greater understanding of the complexity of biological systems. The one thing that has driven my ...

A history of biological and chemical warfare and terrorism.

PubMed

Malloy, C D

2000-07-01

This article provides a brief history of biological warfare and terrorism. It contends that examining disease in history provides public health specialists with the knowledge necessary to improve our surveillance system for potential acts of bioterrorism.

Knowledge base and functionality of concepts of some Filipino biology teachers in five biology topics

NASA Astrophysics Data System (ADS)

Barquilla, Manuel B.

2018-01-01

This mixed research, is a snapshot of some Filipino Biology teachers' knowledge structure and how their concepts of the five topics in Biology (Photosynthesis, Cellular Respiration, human reproductive system, Mendelian genetics and NonMendelian genetics) functions and develops inside a biology classroom. The study focuses on the six biology teachers and a total of 222 students in their respective classes. Of the Six (6) teachers, three (3) are under the Science curriculum and the other three (3) are under regular curriculum in both public and private schools in Iligan city and Lanao del Norte, Philippines. The study utilized classroom discourses, concept maps, interpretative case-study method, bracketing method, and concept analysis for qualitative part; the quantitative part uses a nonparametric statistical tool, Kendall's tau Coefficient for determining relationship and congruency while measures of central tendencies and dispersion (mean, and standard deviation) for concept maps scores interpretation. Knowledge Base of Biology teachers were evaluated by experts in field of specialization having a doctorate program (e.g. PhD in Genetics) and PhD Biology candidates. The data collection entailed seven (7) months immersion: one (1) month for preliminary phase for the researcher to gain teachers' and students' confidence and the succeeding six (6) months for main observation and data collection. The evaluation of teachers' knowledge base by experts indicated that teachers' knowledge of (65%) is lower than the minimum (75%) recommended by ABD-el-Khalick and Boujaoude (1997). Thus, the experts believe that content knowledge of the teachers is hardly adequate for their teaching assignment. Moreover, the teachers in this study do not systematically use reallife situation to apply the concepts they teach. They can identify concepts too abstract for their student; however, they seldom use innovative ways to bring the discussion to their students' level of readiness and capacity to learn. Kendall's Tau Coefficient of agreement indicated that there is an agreement of the rating by experts and PhD (Biology) candidates. As for recommended level for teaching based on the respondent content knowledge structure, the experts and the PhD (Biology) candidates agree that the content knowledge of the teachers is at the borderline (rating of 6) between elementary and high school. These results imply that biology teachers need in-service training to upgrade their content knowledge in the subject. At the same time, the pre-service curriculum for biology teachers needs upgrading.

A Computational Workflow for the Automated Generation of Models of Genetic Designs.

PubMed

Misirli, Göksel; Nguyen, Tramy; McLaughlin, James Alastair; Vaidyanathan, Prashant; Jones, Timothy S; Densmore, Douglas; Myers, Chris; Wipat, Anil

2018-06-05

Computational models are essential to engineer predictable biological systems and to scale up this process for complex systems. Computational modeling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models have still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoded using the Systems Biology Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biological systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation.

You can exercise your way out of HIV and other stories: The role of biological knowledge in adolescents' evaluation of myths

NASA Astrophysics Data System (ADS)

Keselman, Alla; Kaufman, David R.; Patel, Vimla L.

2004-07-01

A primary objective for science education is to impart robust knowledge that has applicability to real-world problems. This article presents research investigating the relationship between adolescents' conceptual understanding of the biological basis of HIV and critical reasoning. Middle and high school students were interviewed about their understanding of HIV and were subsequently asked to evaluate scenarios that contained myths about HIV. On the basis of their responses to the interview questions, students' understanding of HIV was categorized into three models, naïve, intermediate, and advanced. The results indicate that knowledge mediated students' responses in specific ways. Students at different levels of HIV knowledge reasoned in qualitatively different ways about the myths. A significant relationship was found between students' understanding of HIV biology and the level of biological reasoning. We found that students who employed cellular-level biological reasoning were more likely to reject the myths than students who employed just system-level reasoning or nonspecific biological reasoning. The findings emphasize the importance of conceptual understanding in the critical evaluation of information that may serve as a basis for making decisions about HIV. We conclude with discussing the implications of the findings for science and health education.

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Semantic Web meets Integrative Biology: a survey.

PubMed

Chen, Huajun; Yu, Tong; Chen, Jake Y

2013-01-01

Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

2016 Summer Series - Michael Flynn - Synthetic Biological Membrane

NASA Image and Video Library

2016-08-02

Full understanding leads to creation capability, which results in customization capacity. Synthetic biology uses our knowledge of biology to engineer novel biological devices or organisms that can perform tasks not found in nature. For Human space exploration, synthetic biology approaches will reduce risk, mass carried and increase Human reach. Michael Flynn will discuss the International Space Station (ISS) water recycling and his current work on developing a water filtration system capable of self-repair.

Silvicultural systems for the major forest types of the United States

Treesearch

Russell M. Burns

1983-01-01

The current trend toward the establishment and care of forests for a wide combination of uses requires flexibility in forest culture and a knowledge of the silvicultural choices available to the resource manager. This publication summarizes the silvicultural systems that appear biologically feasible, on the basis of present knowledge, for each of 48 major forest types...

Plant defense compounds: systems approaches to metabolic analysis.

PubMed

Kliebenstein, Daniel J

2012-01-01

Systems biology attempts to answer biological questions by integrating across diverse genomic data sets. With the increasing ability to conduct genomics experiments, this integrative approach is being rapidly applied across numerous biological research communities. One of these research communities investigates how plants utilize secondary metabolites or defense metabolites to defend against attack by pathogens and other biotic organisms. This use of systems biology to integrate across transcriptomics, metabolomics, and genomics is significantly enhancing the rate of discovery of genes, metabolites, and bioactivities for plant defense compounds as well as extending our knowledge of how these compounds are regulated. Plant defense compounds are also providing a unique proving platform to develop new approaches that enhance the ability to conduct systems biology with existing and previously unforseen genomics data sets. This review attempts to illustrate both how systems biology is helping the study of plant defense compounds and vice versa.

Learning To Use Scientific Knowledge in Education and Practice Settings: An Evaluation of the Contribution of the Biological Behavioural and Social Sciences to Pre-Registration Nursing and Midwifery Programmes. Researching Professional Education. Research Reports Series Number 3.

ERIC Educational Resources Information Center

Eraut, Michael; And Others

A research project evaluated the contribution of biological, behavioral, and social sciences to nursing and midwifery education programs in Britain. The study of scientific knowledge relevant to recently qualified nurses and midwives was confined to six topics: fluids, electrolytes, and renal systems; nutrition; acute pain; shock; stress; and…

Computational Embryology and Predictive Toxicology of Cleft Palate

EPA Science Inventory

Capacity to model and simulate key events in developmental toxicity using computational systems biology and biological knowledge steps closer to hazard identification across the vast landscape of untested environmental chemicals. In this context, we chose cleft palate as a model ...

Application of Mechanistic Toxicology Data to Ecological Risk Assessments

EPA Science Inventory

The ongoing evolution of knowledge and tools in the areas of molecular biology, bioinformatics, and systems biology holds significant promise for reducing uncertainties associated with ecological risk assessment. As our understanding of the mechanistic basis of responses of organ...

Bacteria as computers making computers

PubMed Central

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments. PMID:19016882

Bacteria as computers making computers.

PubMed

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments.

Using doubly latent multilevel analysis to elucidate relationships between science teachers' professional knowledge and students' performance

NASA Astrophysics Data System (ADS)

Mahler, Daniela; Großschedl, Jörg; Harms, Ute

2017-01-01

Teachers make a difference for the outcome of their students in science classrooms. One focus in this context lies on teachers' professional knowledge. We describe this knowledge according to three domains, namely (1) content knowledge (CK), (2) pedagogical content knowledge (PCK), and (3) curricular knowledge (CuK). We hypothesise a positive relationship between these three domains and students' performance in science. Students' science performance was conceptualised by system thinking performance in the context of biology teaching. In order to test our hypothesis, we examined the relationship between the knowledge triplet CK, PCK, and CuK and students' performance. 48 biology teachers and their students (N = 1036) participated in this study. Teachers' content-related professional knowledge and students' performance were measured by paper-and-pencil tests. Moreover, we used concept maps to further assess students' performance. By specifying doubly latent models, we found a significant positive relationship between biology teachers' PCK and students' performance. On the contrary, the results reveal no relationship between CK and CuK and students' performance. These findings are discussed in respect to modelling the interrelationship of teachers' content-related professional knowledge and students' learning in science, as well as concerning their relevance for further research and teacher education programmes.

Interaction of Inorganic Nanoparticles With Cell Membranes

DTIC Science & Technology

2008-10-20

the field of colloidal and biological behaviour of nanoparticles. Questions regarding the colloidal behavior of particles in biological liquids...better the behaviour of nanoparticles in living systems. 2. Research work During the preparation phase of this project we have defined following...unique knowledge of the participating researgroups in the field of colloidal and biological behaviour of nanoparticles. Questions regarding the

New applications in EPA’s ECOTOX Knowledge System: Assimilating relative potencies of metals across chemical and biological species from literature-based toxicity effects data.

EPA Science Inventory

Toxicity of metals in field settings can vary widely among ionic chemical species and across biological receptors. Thus, a challenge often found in developing TRVs for the risk assessment of metals is identifying the most appropriate metal and biological species combinations for...

Why build a virtual brain? Large-scale neural simulations as jump start for cognitive computing

NASA Astrophysics Data System (ADS)

Colombo, Matteo

2017-03-01

Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates this claim and argues that the main challenge this era is facing is not the lack of biological realism. The challenge lies in identifying general neurocomputational principles for the design of artificial systems, which could display the robust flexibility characteristic of biological intelligence.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine.

PubMed

Maier, Dieter; Kalus, Wenzel; Wolff, Martin; Kalko, Susana G; Roca, Josep; Marin de Mas, Igor; Turan, Nil; Cascante, Marta; Falciani, Francesco; Hernandez, Miguel; Villà-Freixa, Jordi; Losko, Sascha

2011-03-05

To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype-phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene--disease and gene--compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

PubMed Central

2011-01-01

Background To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development. PMID:21375767

Personal protection during resuscitation of casualties contaminated with chemical or biological warfare agents--a survey of medical first responders.

PubMed

Brinker, Andrea; Prior, Kate; Schumacher, Jan

2009-01-01

The threat of mass casualties caused by an unconventional terrorist attack is a challenge for the public health system, with special implications for emergency medicine, anesthesia, and intensive care. Advanced life support of patients injured by chemical or biological warfare agents requires an adequate level of personal protection. The aim of this study was to evaluate the personal protection knowledge of emergency physicians and anesthetists who would be at the frontline of the initial health response to a chemical/biological warfare agent incident. After institutional review board approval, knowledge of personal protection measures among emergency medicine (n = 28) and anesthetics (n = 47) specialty registrars in the South Thames Region of the United Kingdom was surveyed using a standardized questionnaire. Participants were asked for the recommended level of personal protection if a chemical/biological warfare agent(s) casualty required advanced life support in the designated hospital resuscitation area. The best awareness within both groups was regarding severe acute respiratory syndrome, and fair knowledge was found regarding anthrax, plague, Ebola, and smallpox. In both groups, knowledge about personal protection requirements against chemical warfare agents was limited. Knowledge about personal protection measures for biological agents was acceptable, but was limited for chemical warfare agents. The results highlight the need to improve training and education regarding personal protection measures for medical first receivers.

Prospective Elementary Science Teachers' Understanding of Photosynthesis and Cellular Respiration in the Context of Multiple Biological Levels as Nested Systems

ERIC Educational Resources Information Center

Akçay, Süleyman

2017-01-01

In this study, Turkish prospective elementary science teachers' understanding of photosynthesis and cellular respiration has been analysed within the contexts of ecosystem knowledge, organism knowledge and interconnection knowledge (IK). In the analysis, concept maps developed by 74 prospective teachers were used. The study was carried out with…

What Happens to the Food We Eat? Children's Conceptions of the Structure and Function of the Digestive System.

ERIC Educational Resources Information Center

Teixeira, Francimar Martins

2000-01-01

Describes children's conceptions of the structure and function of the human digestive system based on an investigation carried out with children aged 4-10 (n=45). Finds that children possess biological knowledge as an independent knowledge domain from the age of four. Discusses acquisition of and barriers to scientific concepts related to human…

The Importance of Conducting Life Sciences Experiments on the Deep Space Gateway Platform

NASA Technical Reports Server (NTRS)

Bhattacharya, S.

2018-01-01

Over the last several decades important information has been gathered by conducting life science experiments on the Space Shuttle and on the International Space Station. It is now time to leverage that scientific knowledge, as well as aspects of the hardware that have been developed to support the biological model systems, to NASA's next frontier - the Deep Space Gateway. In order to facilitate long duration deep space exploration for humans, it is critical for NASA to understand the effects of long duration, low dose, deep space radiation on biological systems. While carefully controlled ground experiments on Earth-based radiation facilities have provided valuable preliminary information, we still have a significant knowledge gap on the biological responses of organisms to chronic low doses of the highly ionizing particles encountered beyond low Earth orbit. Furthermore, the combined effects of altered gravity and radiation have the potential to cause greater biological changes than either of these parameters alone. Therefore a thorough investigation of the biological effects of a cis-lunar environment will facilitate long term human exploration of deep space.

The "What Is a System" Reflection Interview as a Knowledge Integration Activity for High School Students' Understanding of Complex Systems in Human Biology

ERIC Educational Resources Information Center

Tripto, Jaklin; Ben-Zvi Assaraf, Orit; Snapir, Zohar; Amit, Miriam

2016-01-01

This study examined the reflection interview as a tool for assessing and facilitating the use of "systems language" amongst 11th grade students who have recently completed their first year of high school biology. Eighty-three students composed two concept maps in the 10th grade--one at the beginning of the school year and one at its end.…

On the optimal design of molecular sensing interfaces with lipid bilayer assemblies - A knowledge based approach

NASA Astrophysics Data System (ADS)

Siontorou, Christina G.

2012-12-01

Biosensors are analytic devices that incorporate a biochemical recognition system (biological, biologicalderived or biomimic: enzyme, antibody, DNA, receptor, etc.) in close contact with a physicochemical transducer (electrochemical, optical, piezoelectric, conductimetric, etc.) that converts the biochemical information, produced by the specific biological recognition reaction (analyte-biomolecule binding), into a chemical or physical output signal, related to the concentration of the analyte in the measuring sample. The biosensing concept is based on natural chemoreception mechanisms, which are feasible over/within/by means of a biological membrane, i.e., a structured lipid bilayer, incorporating or attached to proteinaceous moieties that regulate molecular recognition events which trigger ion flux changes (facilitated or passive) through the bilayer. The creation of functional structures that are similar to natural signal transduction systems, correlating and interrelating compatibly and successfully the physicochemical transducer with the lipid film that is self-assembled on its surface while embedding the reconstituted biological recognition system, and at the same time manage to satisfy the basic conditions for measuring device development (simplicity, easy handling, ease of fabrication) is far from trivial. The aim of the present work is to present a methodological framework for designing such molecular sensing interfaces, functioning within a knowledge-based system built on an ontological platform for supplying sub-systems options, compatibilities, and optimization parameters.

Tracing organizing principles: learning from the history of systems biology.

PubMed

Green, Sara; Wolkenhauer, Olaf

2013-01-01

With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to "reverse engineer" the functional organization of biological systems using methodologies from mathematics, engineering and computer science while taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational and system-level properties, ii) the inherent critique of reductionism and fragmentation of knowledge resulting from overspecialization, and iii) the insight that the ideal of formulating abstract organizing principles is complementary to, rather than conflicting with, the aim of formulating detailed explanations of biological mechanisms. We argue that looking back not only helps us understand the current practice but also points to possible future directions for systems biology.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

PubMed

Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; De Keersmaecker, Sigrid C J; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L; Shin, Sook-il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M; Zengler, Karsten; Palsson, Bernhard O; Adkins, Joshua N; Bumann, Dirk

2011-01-18

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

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

Thiele, Ines; Hyduke, Daniel R.; Steeb, Benjamin

2011-01-01

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of thismore » reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Finally, taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.« less

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

Structural and Network-based Methods for Knowledge-Based Systems

DTIC Science & Technology

2011-12-01

depth) provide important information about knowledge gaps in the KB. For example, if SuccessEstimate (causes-EventEvent, Typhoid - Fever , 1, 3) is...equal to 0, it points toward lack of biological knowledge about Typhoid - Fever in our KB. Similar information can also be obtained from the...position of the consequent. ⋃ ( ( ) ) Therefore, if Q does not contain Typhoid - Fever , then obtaining

Multi-level and hybrid modelling approaches for systems biology.

PubMed

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Integrating systems biology models and biomedical ontologies

PubMed Central

2011-01-01

Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms. PMID:21835028

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance

DOE PAGES

Kalluri, Udaya C.; Yin, Hengfu; Yang, Xiaohan; ...

2014-11-03

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host thatmore » carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Finally, synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance.« less

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance

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

Kalluri, Udaya C.; Yin, Hengfu; Yang, Xiaohan

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host thatmore » carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Finally, synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance.« less

Computation as the mechanistic bridge between precision medicine and systems therapeutics.

PubMed

Hansen, J; Iyengar, R

2013-01-01

Over the past 50 years, like molecular cell biology, medicine and pharmacology have been driven by a reductionist approach. The focus on individual genes and cellular components as disease loci and drug targets has been a necessary step in understanding the basic mechanisms underlying tissue/organ physiology and drug action. Recent progress in genomics and proteomics, as well as advances in other technologies that enable large-scale data gathering and computational approaches, is providing new knowledge of both normal and disease states. Systems-biology approaches enable integration of knowledge from different types of data for precision medicine and systems therapeutics. In this review, we describe recent studies that contribute to these emerging fields and discuss how together these fields can lead to a mechanism-based therapy for individual patients.

Computation as the Mechanistic Bridge Between Precision Medicine and Systems Therapeutics

PubMed Central

Hansen, J; Iyengar, R

2014-01-01

Over the past 50 years, like molecular cell biology, medicine and pharmacology have been driven by a reductionist approach. The focus on individual genes and cellular components as disease loci and drug targets has been a necessary step in understanding the basic mechanisms underlying tissue/organ physiology and drug action. Recent progress in genomics and proteomics, as well as advances in other technologies that enable large-scale data gathering and computational approaches, is providing new knowledge of both normal and disease states. Systems-biology approaches enable integration of knowledge from different types of data for precision medicine and systems therapeutics. In this review, we describe recent studies that contribute to these emerging fields and discuss how together these fields can lead to a mechanism-based therapy for individual patients. PMID:23212109

Development of the Neuron Assessment for Measuring Biology Students’ Use of Experimental Design Concepts and Representations

PubMed Central

Dasgupta, Annwesa P.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

Researchers, instructors, and funding bodies in biology education are unanimous about the importance of developing students’ competence in experimental design. Despite this, only limited measures are available for assessing such competence development, especially in the areas of molecular and cellular biology. Also, existing assessments do not measure how well students use standard symbolism to visualize biological experiments. We propose an assessment-design process that 1) provides background knowledge and questions for developers of new “experimentation assessments,” 2) elicits practices of representing experiments with conventional symbol systems, 3) determines how well the assessment reveals expert knowledge, and 4) determines how well the instrument exposes student knowledge and difficulties. To illustrate this process, we developed the Neuron Assessment and coded responses from a scientist and four undergraduate students using the Rubric for Experimental Design and the Concept-Reasoning Mode of representation (CRM) model. Some students demonstrated sound knowledge of concepts and representations. Other students demonstrated difficulty with depicting treatment and control group data or variability in experimental outcomes. Our process, which incorporates an authentic research situation that discriminates levels of visualization and experimentation abilities, shows potential for informing assessment design in other disciplines. PMID:27146159

[Multicenter evaluation of the Nutri-Expert Telematic System in diabetic patients].

PubMed

Turnin, M C; Bolzonella-Pene, C; Dumoulin, S; Cerf, I; Charpentier, G; Sandre-Banon, D; Valensi, P; Grenier, J L; Cathelineau, G; Mattei, C

1995-02-01

Nutri-Expert is a system for self-monitoring and dietetic education, accessible through Minitel. A preliminary randomised evaluation of one hundred diabetic patients in the Midi-Pyrénées region showed that Nutri-Expert improved dietetic knowledge, dietary habits and metabolic balance. The aim of the present study was to show that the system can be successfully prescribed to patients by physicians outside the center which originated it, indicating the benefit of a wider use of Nutri-Expert, among the diabetic population. One hundred and fifty-five patients, recruited by six French centres of diabetology, used Nutri-Expert from their homes for six months. Clinical examination, tests of dietetic knowledge and biological tests, including lipid fractions, were carried out before and after six months of use. After six months, there was a significant improvement in the patients' dietetic knowledge and in some biological parameters. Nutri-Expert is thus useful even when prescribed by a centre other than the hospital which devised the system. It is an additional beneficial tool in the ambulatory management of diabetic patients.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

USDA-ARS?s Scientific Manuscript database

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium...

Wilderness and well-being: Complexity, time, and psychological growth

Treesearch

Joar Vitterso

2002-01-01

This paper presents the argument for interdisciplinary wilderness research. The idea of interdisciplinarity is grounded in theories of emotion and psychological growth that are compatible with basic knowledge in other scientific disciplines, and in particular with concepts related to evolution. Considering humans as biological knowledge systems, designed by natural...

Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

NASA Astrophysics Data System (ADS)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function scores.

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

PubMed Central

Cook, Daniel L; Farley, Joel F; Tapscott, Stephen J

2001-01-01

Background: We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. Results: We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have used to explore the utility and feasibility of this approach to functional biology. Using example models, we demonstrate that a rather limited lexicon of icons and arrows suffices to describe complex cell-biological systems as discrete models that can be posted and linked on the internet. Conclusions: Given available computer and internet technology, BioD may be implemented as an extensible, multidisciplinary language that can be used to archive functional systems knowledge and be extended to support both qualitative and quantitative functional analysis. PMID:11305940

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

On the search for design principles in biological systems.

PubMed

Poyatos, Juan F

2012-01-01

The search for basic concepts and underlying principles was at the core of the systems approach to science and technology. This approach was somehow abandoned in mainstream biology after its initial proposal, due to the rise and success of molecular biology. This situation has changed. The accumulated knowledge of decades of molecular studies in combination with new technological advances, while further highlighting the intricacies of natural systems, is also bringing back the quest-for-principles research program. Here, I present two lessons that I derived from my own quest: the importance of studying biological information processing to identify common principles in seemingly unrelated contexts and the adequacy of using known design principles at one level of biological organization as a valuable tool to help recognizing principles at an alternative one. These and additional lessons should contribute to the ultimate goal of establishing principles able to integrate the many scales of biological complexity.

Nursing and the new biology: towards a realist, anti-reductionist approach to nursing knowledge.

PubMed

Nairn, Stuart

2014-10-01

As a system of knowledge, nursing has utilized a range of subjects and reconstituted them to reflect the thinking and practice of health care. Often drawn to a holistic model, nursing finds it difficult to resist the reductionist tendencies in biological and medical thinking. In this paper I will propose a relational approach to knowledge that is able to address this issue. The paper argues that biology is not characterized by one stable theory but is often a contentious topic and employs philosophically diverse models in its scientific research. Biology need not be seen as a reductionist science, but reductionism is nonetheless an important current within biological thinking. These reductionist currents can undermine nursing knowledge in four main ways. Firstly, that the conclusions drawn from reductionism go far beyond their data based on an approach that prioritizes biological explanations and eliminates others. Secondly, that the methods employed by biologists are sometimes weak, and the limitations are insufficiently acknowledged. Thirdly, that the assumptions that drive the research agenda are problematic, and finally that uncritical application of these ideas can be potentially disastrous for nursing practice. These issues are explored through an examination of the problems reductionism poses for the issue of gender, mental health, and altruism. I then propose an approach based on critical realism that adopts an anti-reductionist philosophy that utilizes the conceptual tools of emergence and a relational ontology. © 2014 John Wiley & Sons Ltd.

Ultra-Structure database design methodology for managing systems biology data and analyses

PubMed Central

Maier, Christopher W; Long, Jeffrey G; Hemminger, Bradley M; Giddings, Morgan C

2009-01-01

Background Modern, high-throughput biological experiments generate copious, heterogeneous, interconnected data sets. Research is dynamic, with frequently changing protocols, techniques, instruments, and file formats. Because of these factors, systems designed to manage and integrate modern biological data sets often end up as large, unwieldy databases that become difficult to maintain or evolve. The novel rule-based approach of the Ultra-Structure design methodology presents a potential solution to this problem. By representing both data and processes as formal rules within a database, an Ultra-Structure system constitutes a flexible framework that enables users to explicitly store domain knowledge in both a machine- and human-readable form. End users themselves can change the system's capabilities without programmer intervention, simply by altering database contents; no computer code or schemas need be modified. This provides flexibility in adapting to change, and allows integration of disparate, heterogenous data sets within a small core set of database tables, facilitating joint analysis and visualization without becoming unwieldy. Here, we examine the application of Ultra-Structure to our ongoing research program for the integration of large proteomic and genomic data sets (proteogenomic mapping). Results We transitioned our proteogenomic mapping information system from a traditional entity-relationship design to one based on Ultra-Structure. Our system integrates tandem mass spectrum data, genomic annotation sets, and spectrum/peptide mappings, all within a small, general framework implemented within a standard relational database system. General software procedures driven by user-modifiable rules can perform tasks such as logical deduction and location-based computations. The system is not tied specifically to proteogenomic research, but is rather designed to accommodate virtually any kind of biological research. Conclusion We find Ultra-Structure offers substantial benefits for biological information systems, the largest being the integration of diverse information sources into a common framework. This facilitates systems biology research by integrating data from disparate high-throughput techniques. It also enables us to readily incorporate new data types, sources, and domain knowledge with no change to the database structure or associated computer code. Ultra-Structure may be a significant step towards solving the hard problem of data management and integration in the systems biology era. PMID:19691849

Data Integration and Mining for Synthetic Biology Design.

PubMed

Mısırlı, Göksel; Hallinan, Jennifer; Pocock, Matthew; Lord, Phillip; McLaughlin, James Alastair; Sauro, Herbert; Wipat, Anil

2016-10-21

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

Systematic technology transfer from biology to engineering.

PubMed

Vincent, Julian F V; Mann, Darrell L

2002-02-15

Solutions to problems move only very slowly between different disciplines. Transfer can be greatly speeded up with suitable abstraction and classification of problems. Russian researchers working on the TRIZ (Teoriya Resheniya Izobretatelskikh Zadatch) method for inventive problem solving have identified systematic means of transferring knowledge between different scientific and engineering disciplines. With over 1500 person years of effort behind it, TRIZ represents the biggest study of human creativity ever conducted, whose aim has been to establish a system into which all known solutions can be placed, classified in terms of function. At present, the functional classification structure covers nearly 3 000 000 of the world's successful patents and large proportions of the known physical, chemical and mathematical knowledge-base. Additional tools are the identification of factors which prevent the attainment of new technology, leading directly to a system of inventive principles which will resolve the impasse, a series of evolutionary trends of development, and to a system of methods for effecting change in a system (Su-fields). As yet, the database contains little biological knowledge despite early recognition by the instigator of TRIZ (Genrich Altshuller) that one day it should. This is illustrated by natural systems evolved for thermal stability and the maintenance of cleanliness.

Synthetic biology approaches in cancer immunotherapy, genetic network engineering, and genome editing.

PubMed

Chakravarti, Deboki; Cho, Jang Hwan; Weinberg, Benjamin H; Wong, Nicole M; Wong, Wilson W

2016-04-18

Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.

[Habitability and biological life support systems for man].

PubMed

Gazenko, O G; Grigor'ev, A I; Meleshko, G I; Shepelev, E Ia

1990-01-01

This paper discusses general concepts and specific details of the habitability of space stations and planetary bases completely isolated from the Earth for long periods of time. It emphasizes inadequacy of the present-day knowledge about natural conditions that provide a biologically acceptable environment on the Earth as well as lack of information about life support systems as a source of consumables (oxygen, water, food) and a tool for waste management. The habitability of advanced space vehicles is closely related to closed bioregenerative systems used as life support systems.

Systems Toxicology: From Basic Research to Risk Assessment

PubMed Central

2014-01-01

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment. PMID:24446777

Systems toxicology: from basic research to risk assessment.

PubMed

Sturla, Shana J; Boobis, Alan R; FitzGerald, Rex E; Hoeng, Julia; Kavlock, Robert J; Schirmer, Kristin; Whelan, Maurice; Wilks, Martin F; Peitsch, Manuel C

2014-03-17

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.

Research Plan for Study of Biological and Ecological Effects of the Solar Power Satellite Transmission System

NASA Technical Reports Server (NTRS)

Newsom, B. D.

1978-01-01

A programmatic research plan for a three year study is presented to generate knowledge on effects of the continuous wave 2.45 GHz microwave power transmission that the Solar Power Satellite might have on biological and ecological elements, within and around the rectenna receiving site.

Empirical study using network of semantically related associations in bridging the knowledge gap.

PubMed

Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

2014-11-27

The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance.

PubMed

Kalluri, Udaya C; Yin, Hengfu; Yang, Xiaohan; Davison, Brian H

2014-12-01

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host that carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Safety of High Speed Guided Ground Transportation Systems : Review of Existing EMF Guidelines, Standards and Regulations

DOT National Transportation Integrated Search

1993-08-01

To assess the state of knowledge about anticipated electric and magnetic field (EMF) exposures from electrical transportation systems, including electrically powered rail and magnetically levitated (maglev), research concerning biological effects of ...

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

PubMed Central

Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

2014-01-01

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid kinetics/dynamics, literature-recorded pathways and transcription factor (TF) information. PMID:25162401

Selection platforms for directed evolution in synthetic biology

PubMed Central

Tizei, Pedro A.G.; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B.

2016-01-01

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules–gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function–be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. PMID:27528765

Selection platforms for directed evolution in synthetic biology.

PubMed

Tizei, Pedro A G; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B

2016-08-15

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. © 2016 The Author(s).

The Metals in the Biological Periodic System of the Elements: Concepts and Conjectures

PubMed Central

Maret, Wolfgang

2016-01-01

A significant number of chemical elements are either essential for life with known functions, or present in organisms with poorly defined functional outcomes. We do not know all the essential elements with certainty and we know even less about the functions of apparently non-essential elements. In this article, I discuss a basis for a biological periodic system of the elements and that biochemistry should include the elements that are traditionally part of inorganic chemistry and not only those that are in the purview of organic chemistry. A biological periodic system of the elements needs to specify what “essential” means and to which biological species it refers. It represents a snapshot of our present knowledge and is expected to undergo further modifications in the future. An integrated approach of biometal sciences called metallomics is required to understand the interactions of metal ions, the biological functions that their chemical structures acquire in the biological system, and how their usage is fine-tuned in biological species and in populations of species with genetic variations (the variome). PMID:26742035

Development and implementation of an expert system to improve the control of nitrification and denitrification in the Vic wastewater treatment plant.

PubMed

Ribas, F; Rodríguez-Roda, I; Serrat, J; Clara, P; Comas, J

2008-05-01

Wastewater treatment plants employ various physical, chemical and biological processes to reduce pollutants from raw wastewater. One of the most important is the biological nitrogen removal process through nitrification and denitrification steps taking place in various sections of the biological reactor. One of the most extensively used configurations to achieve the biological nitrogen removal is an activated sludge system using oxidation ditch or extended aeration. To improve nitrogen removal in the wastewater treatment plant (WWTP) of Vic (Catalonia, NE Spain), the automatic aeration control system was complemented with an Expert System to always provide the most appropriate aeration or anoxia sequence based on the values of ammonium and nitrates given by an automatic analyzer. This article illustrates the development and implementation of this knowledge-based system within the framework of a Decision Support System, which performs SCADA functions. The paper also shows that the application of the decision support system in the Vic WWTP resulted in significant improvements to the biological nitrogen removal.

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

PubMed Central

Klinke, David J.

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900’s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. PMID:25139179

In silico model-based inference: a contemporary approach for hypothesis testing in network biology.

PubMed

Klinke, David J

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers.

Development of the Neuron Assessment for Measuring Biology Students' Use of Experimental Design Concepts and Representations.

PubMed

Dasgupta, Annwesa P; Anderson, Trevor R; Pelaez, Nancy J

2016-01-01

Researchers, instructors, and funding bodies in biology education are unanimous about the importance of developing students' competence in experimental design. Despite this, only limited measures are available for assessing such competence development, especially in the areas of molecular and cellular biology. Also, existing assessments do not measure how well students use standard symbolism to visualize biological experiments. We propose an assessment-design process that 1) provides background knowledge and questions for developers of new "experimentation assessments," 2) elicits practices of representing experiments with conventional symbol systems, 3) determines how well the assessment reveals expert knowledge, and 4) determines how well the instrument exposes student knowledge and difficulties. To illustrate this process, we developed the Neuron Assessment and coded responses from a scientist and four undergraduate students using the Rubric for Experimental Design and the Concept-Reasoning Mode of representation (CRM) model. Some students demonstrated sound knowledge of concepts and representations. Other students demonstrated difficulty with depicting treatment and control group data or variability in experimental outcomes. Our process, which incorporates an authentic research situation that discriminates levels of visualization and experimentation abilities, shows potential for informing assessment design in other disciplines. © 2016 A. P. Dasgupta et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Systems biology approach to bioremediation

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

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potentialmore » for making bioremediation breakthroughs and illuminating the ‘black box’.« less

3D molecular models of whole HIV-1 virions generated with cellPACK

PubMed Central

Goodsell, David S.; Autin, Ludovic; Forli, Stefano; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems biology data with packing algorithms to assemble comprehensive 3D models of cell-scale structures in molecular detail. This report describes the biological data, modeling parameters and cellPACK methods used to specify and construct editable models for HIV-1. Anticipating that cellPACK interfaces under development will enable researchers from diverse backgrounds to critique and improve the biological models, we discuss how cellPACK can be used as a framework to unify different types of data across all scales of biology. PMID:25253262

Introducing Evolution to Non-Biology Majors via the Fossil Record: A Case Study from the Israeli High School System.

ERIC Educational Resources Information Center

Dodick, Jeff; Orion, Nir

2003-01-01

Discusses challenges faced in the teaching and learning of evolution. Presents a curricular program and a case study on evolutionary biology. Investigates students' conceptual knowledge after exposure to the program "From Dinosaurs to Darwin," which focuses on fossil records as evidence of evolution. (Contains 32 references.) (YDS)

The Use of Avian Focal Species for Conservation Planning in California

Treesearch

Mary K. Chase; Geoffrey R. Geupel

2005-01-01

Conservationists often try to facilitate the complex task of protecting biological diversity by choosing a subset of species from a larger community to help them plan their conservation objectives. Biological knowledge about these species then is used to plan reserve systems or to guide habitat restoration and management efforts, with the assumption that the...

An Evolutionary Perspective on Learning Disability in Mathematics

PubMed Central

Geary, David C.

2015-01-01

A distinction between potentially evolved, or biologically-primary forms of cognition, and the culturally-specific, or biologically-secondary forms of cognition that are built from primary systems is used to explore mathematical learning disability (MLD). Using this model, MLD could result from deficits in the brain and cognitive systems that support biologically-primary mathematical competencies, or from the brain and cognitive systems that support the modification of primary systems for the creation of secondary knowledge and secondary cognitive competencies. The former include visuospatial long-term and working memory and the intraparietal sulcus, whereas the latter include the central executive component of working memory and the anterior cingulate cortex and lateral prefrontal cortex. Different forms of MLD are discussed as related to each of the cognitive and brain systems. PMID:17650991

Using graph theory to analyze biological networks

PubMed Central

2011-01-01

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. PMID:21527005

Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier

PubMed Central

Culibrk, Luka; Croft, Carys A.

2016-01-01

Abstract Opportunistic fungal infections are an increasing threat for global health, and for immunocompromised patients in particular. These infections are characterized by interaction between fungal pathogen and host cells. The exact mechanisms and the attendant variability in host and fungal pathogen interaction remain to be fully elucidated. The field of systems biology aims to characterize a biological system, and utilize this knowledge to predict the system's response to stimuli such as fungal exposures. A multi-omics approach, for example, combining data from genomics, proteomics, metabolomics, would allow a more comprehensive and pan-optic “two systems” biology of both the host and the fungal pathogen. In this review and literature analysis, we present highly specialized and nascent methods for analysis of multiple -omes of biological systems, in addition to emerging single-molecule visualization techniques that may assist in determining biological relevance of multi-omics data. We provide an overview of computational methods for modeling of gene regulatory networks, including some that have been applied towards the study of an interacting host and pathogen. In sum, comprehensive characterizations of host–fungal pathogen systems are now possible, and utilization of these cutting-edge multi-omics strategies may yield advances in better understanding of both host biology and fungal pathogens at a systems scale. PMID:26885725

Pacific Northwest Laboratory annual report for 1993 to the DOE Office of Energy Research. Part 1: Biomedical Sciences

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

Lumetta, C.C.; Park, J.F.

1994-03-01

This report summarizes FY 1993 progress in biological and general life sciences research programs conducted for the Department of Energy`s Office of Health and Environmental REsearch (OHER) at Pacific Northwest Laboratory (PNL). This research provides knowledge of fundamental principles necessary to identify, understand, and anticipate the long-term health consequences of exposure to energy-related radiation and chemicals. The Biological Research section contains reports of studies using laboratory animals, in vitro cell systems, and molecular biological systems. This research includes studies of the impact of radiation, radionuclides, and chemicals on biological responses at all levels of biological organization. The General Life Sciencesmore » Research section reports research conducted for the OHER human genome program.« less

On the formalization and reuse of scientific research.

PubMed

King, Ross D; Liakata, Maria; Lu, Chuan; Oliver, Stephen G; Soldatova, Larisa N

2011-10-07

The reuse of scientific knowledge obtained from one investigation in another investigation is basic to the advance of science. Scientific investigations should therefore be recorded in ways that promote the reuse of the knowledge they generate. The use of logical formalisms to describe scientific knowledge has potential advantages in facilitating such reuse. Here, we propose a formal framework for using logical formalisms to promote reuse. We demonstrate the utility of this framework by using it in a worked example from biology: demonstrating cycles of investigation formalization [F] and reuse [R] to generate new knowledge. We first used logic to formally describe a Robot scientist investigation into yeast (Saccharomyces cerevisiae) functional genomics [f(1)]. With Robot scientists, unlike human scientists, the production of comprehensive metadata about their investigations is a natural by-product of the way they work. We then demonstrated how this formalism enabled the reuse of the research in investigating yeast phenotypes [r(1) = R(f(1))]. This investigation found that the removal of non-essential enzymes generally resulted in enhanced growth. The phenotype investigation was then formally described using the same logical formalism as the functional genomics investigation [f(2) = F(r(1))]. We then demonstrated how this formalism enabled the reuse of the phenotype investigation to investigate yeast systems-biology modelling [r(2) = R(f(2))]. This investigation found that yeast flux-balance analysis models fail to predict the observed changes in growth. Finally, the systems biology investigation was formalized for reuse in future investigations [f(3) = F(r(2))]. These cycles of reuse are a model for the general reuse of scientific knowledge.

Formative Assessment Pre-Test to Identify College Students' Prior Knowledge, Misconceptions and Learning Difficulties in Biology

ERIC Educational Resources Information Center

Lazarowitz, Reuven; Lieb, Carl

2006-01-01

A formative assessment pretest was administered to undergraduate students at the beginning of a science course in order to find out their prior knowledge, misconceptions and learning difficulties on the topic of the human respiratory system and energy issues. Those findings could provide their instructors with the valuable information required in…

Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions.

PubMed

Rehm, Markus; Prehn, Jochen H M

2013-06-01

Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. All rights reserved.

Effects of Biology Teachers' Professional Knowledge and Cognitive Activation on Students' Achievement

ERIC Educational Resources Information Center

Förtsch, Christian; Werner, Sonja; von Kotzebue, Lena; Neuhaus, Birgit J.

2016-01-01

This study examined the effects of teachers' biology-specific dimensions of professional knowledge--pedagogical content knowledge (PCK) and content knowledge (CK)--and cognitively activating biology instruction, as a feature of instructional quality, on students' learning. The sample comprised 39 German secondary school teachers whose lessons on…

A cross-cultural comparison of biology lessons between China and Germany: a video study

NASA Astrophysics Data System (ADS)

Liu, Ning; Neuhaus, Birgit Jana

2017-08-01

Given the globalization of science education and the different cultures between China and Germany, we tried to compare and explain the differences on teacher questions and real life instances in biology lessons between the two countries from a culture-related perspective. 22 biology teachers from China and 21 biology teachers from Germany participated in this study. Each teacher was videotaped for one lesson on the unit blood and circulatory system. Before the teaching unit, students' prior knowledge was tested with a pretest. After the teaching unit, students' content knowledge was tested with a posttest. The aim of the knowledge tests here was for the better selection of the four samples for qualitative comparison in the two countries. The quantitative analysis showed that more lower-order teacher questions and more real life instances that were introduced after learning relevant concepts were in Chinese lessons than in German lessons. There were no significant differences in the frequency of higher-order questions or real life instances that were introduced before learning concepts. Qualitative analysis showed that both German teachers guided students to analyze the reasoning process of Landsteiner experiment, but nor Chinese teachers did that. The findings reflected the subtle influence of culture on classroom teaching. Relatively, Chinese biology teachers focused more on learning content and the application of the content in real life; German biology teachers emphasized more on invoking students' reasoning and divergent thinking.

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

The role of low-grade inflammation and metabolic flexibility in aging and nutritional modulation thereof: a systems biology approach.

PubMed

Calçada, Dulce; Vianello, Dario; Giampieri, Enrico; Sala, Claudia; Castellani, Gastone; de Graaf, Albert; Kremer, Bas; van Ommen, Ben; Feskens, Edith; Santoro, Aurelia; Franceschi, Claudio; Bouwman, Jildau

2014-01-01

Aging is a biological process characterized by the progressive functional decline of many interrelated physiological systems. In particular, aging is associated with the development of a systemic state of low-grade chronic inflammation (inflammaging), and with progressive deterioration of metabolic function. Systems biology has helped in identifying the mediators and pathways involved in these phenomena, mainly through the application of high-throughput screening methods, valued for their molecular comprehensiveness. Nevertheless, inflammation and metabolic regulation are dynamical processes whose behavior must be understood at multiple levels of biological organization (molecular, cellular, organ, and system levels) and on multiple time scales. Mathematical modeling of such behavior, with incorporation of mechanistic knowledge on interactions between inflammatory and metabolic mediators, may help in devising nutritional interventions capable of preventing, or ameliorating, the age-associated functional decline of the corresponding systems. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Text mining and its potential applications in systems biology.

PubMed

Ananiadou, Sophia; Kell, Douglas B; Tsujii, Jun-ichi

2006-12-01

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

Knowledge Transfer in Biology and Translation across External Representations: Experts' Views and Challenges for Learning

ERIC Educational Resources Information Center

Schonborn, Konrad J.; Bogeholz, Susanne

2009-01-01

Recent curriculum reform promotes core competencies such as desired "content knowledge" and "communication" for meaningful learning in biology. Understanding in biology is demonstrated when pupils can apply acquired knowledge to new tasks. This process requires the transfer of knowledge and the subordinate process of translation across external…

Heterogeneous database integration in biomedicine.

PubMed

Sujansky, W

2001-08-01

The rapid expansion of biomedical knowledge, reduction in computing costs, and spread of internet access have created an ocean of electronic data. The decentralized nature of our scientific community and healthcare system, however, has resulted in a patchwork of diverse, or heterogeneous, database implementations, making access to and aggregation of data across databases very difficult. The database heterogeneity problem applies equally to clinical data describing individual patients and biological data characterizing our genome. Specifically, databases are highly heterogeneous with respect to the data models they employ, the data schemas they specify, the query languages they support, and the terminologies they recognize. Heterogeneous database systems attempt to unify disparate databases by providing uniform conceptual schemas that resolve representational heterogeneities, and by providing querying capabilities that aggregate and integrate distributed data. Research in this area has applied a variety of database and knowledge-based techniques, including semantic data modeling, ontology definition, query translation, query optimization, and terminology mapping. Existing systems have addressed heterogeneous database integration in the realms of molecular biology, hospital information systems, and application portability.

Generation of the Dimensional Embryology Application (App) for Visualization of Early Chick and Frog Embryonic Development

ERIC Educational Resources Information Center

Webb, Rebecca L.; Bilitski, James; Zerbee, Alyssa; Symans, Alexandra; Chop, Alexandra; Seitz, Brianne; Tran, Cindy

2015-01-01

The study of embryonic development of multiple organisms, including model organisms such as frogs and chicks, is included in many undergraduate biology programs, as well as in a variety of graduate programs. As our knowledge of biological systems increases and the amount of material to be taught expands, the time spent instructing students about…

Collaboratively charting the gene-to-phenotype network of human congenital heart defects

PubMed Central

2010-01-01

Background How to efficiently integrate the daily practice of molecular biologists, geneticists, and clinicians with the emerging computational strategies from systems biology is still much of an open question. Description We built on the recent advances in Wiki-based technologies to develop a collaborative knowledge base and gene prioritization portal aimed at mapping genes and genomic regions, and untangling their relations with corresponding human phenotypes, congenital heart defects (CHDs). This portal is not only an evolving community repository of current knowledge on the genetic basis of CHDs, but also a collaborative environment for the study of candidate genes potentially implicated in CHDs - in particular by integrating recent strategies for the statistical prioritization of candidate genes. It thus serves and connects the broad community that is facing CHDs, ranging from the pediatric cardiologist and clinical geneticist to the basic investigator of cardiogenesis. Conclusions This study describes the first specialized portal to collaboratively annotate and analyze gene-phenotype networks. Of broad interest to the biological community, we argue that such portals will play a significant role in systems biology studies of numerous complex biological processes. CHDWiki is accessible at http://www.esat.kuleuven.be/~bioiuser/chdwiki PMID:20193066

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

Artificial Immune System Approaches for Aerospace Applications

NASA Technical Reports Server (NTRS)

KrishnaKumar, Kalmanje; Koga, Dennis (Technical Monitor)

2002-01-01

Artificial Immune Systems (AIS) combine a priori knowledge with the adapting capabilities of biological immune system to provide a powerful alternative to currently available techniques for pattern recognition, modeling, design, and control. Immunology is the science of built-in defense mechanisms that are present in all living beings to protect against external attacks. A biological immune system can be thought of as a robust, adaptive system that is capable of dealing with an enormous variety of disturbances and uncertainties. Biological immune systems use a finite number of discrete "building blocks" to achieve this adaptiveness. These building blocks can be thought of as pieces of a puzzle which must be put together in a specific way-to neutralize, remove, or destroy each unique disturbance the system encounters. In this paper, we outline AIS models that are immediately applicable to aerospace problems and identify application areas that need further investigation.

DAISY: a new software tool to test global identifiability of biological and physiological systems.

PubMed

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D'Angiò, Leontina

2007-10-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/.

Student Teachers' Pedagogical Content Knowledge for Teaching Systems Thinking: Effects of Different Interventions

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Hörsch, Christian; Schuler, Stephan; Riess, Werner

2017-01-01

Systems' thinking has become increasingly relevant not only in education for sustainable development but also in everyday life. Even if teachers know the dynamics and complexity of living systems in biology and geography, they might not be able to effectively explain it to students. Teachers need an understanding of systems and their behaviour…

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

PubMed

Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

PubMed Central

Chen, Yi-An; Tripathi, Lokesh P.; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org PMID:26989145

Robotics-inspired biology.

PubMed

Gravish, Nick; Lauder, George V

2018-03-29

For centuries, designers and engineers have looked to biology for inspiration. Biologically inspired robots are just one example of the application of knowledge of the natural world to engineering problems. However, recent work by biologists and interdisciplinary teams have flipped this approach, using robots and physical models to set the course for experiments on biological systems and to generate new hypotheses for biological research. We call this approach robotics-inspired biology; it involves performing experiments on robotic systems aimed at the discovery of new biological phenomena or generation of new hypotheses about how organisms function that can then be tested on living organisms. This new and exciting direction has emerged from the extensive use of physical models by biologists and is already making significant advances in the areas of biomechanics, locomotion, neuromechanics and sensorimotor control. Here, we provide an introduction and overview of robotics-inspired biology, describe two case studies and suggest several directions for the future of this exciting new research area. © 2018. Published by The Company of Biologists Ltd.

Joining Forces: The Chemical Biology-Medicinal Chemistry Continuum.

PubMed

Plowright, Alleyn T; Ottmann, Christian; Arkin, Michelle; Auberson, Yves P; Timmerman, Henk; Waldmann, Herbert

2017-09-21

The scientific advances being made across all disciplines are creating ever-increasing opportunities to enhance our knowledge of biological systems and how they relate to human disease. One of the central driving forces in discovering new medicines is medicinal chemistry, where the design and synthesis of novel compounds has led to multiple drugs. Chemical biology, sitting at the interface of many disciplines, has now emerged as a major contributor to the understanding of biological systems and is becoming an integral part of drug discovery. Bringing chemistry and biology much closer and blurring the boundaries between disciplines is creating new opportunities to probe and understand biology; both disciplines play key roles and need to join forces and work together effectively to synergize their impact. The power of chemical biology will then reach its full potential and drive innovation, leading to the discovery of transformative medicines to treat patients. Advances in cancer biology and drug discovery highlight this potential. Copyright © 2017 Elsevier Ltd. All rights reserved.

Middle and High School Students' Conceptions of Climate Change Mitigation and Adaptation Strategies

ERIC Educational Resources Information Center

Bofferding, Laura; Kloser, Matthew

2015-01-01

Both scientists and policy-makers emphasize the importance of education for influencing pro-environmental behavior and minimizing the effects of climate change on biological and physical systems. Education has the potential to impact students' system knowledge--their understanding of the variables that affect the climate system--and action…

The `What is a system' reflection interview as a knowledge integration activity for high school students' understanding of complex systems in human biology

NASA Astrophysics Data System (ADS)

Tripto, Jaklin; Ben-Zvi Assaraf, Orit; Snapir, Zohar; Amit, Miriam

2016-03-01

This study examined the reflection interview as a tool for assessing and facilitating the use of 'systems language' amongst 11th grade students who have recently completed their first year of high school biology. Eighty-three students composed two concept maps in the 10th grade-one at the beginning of the school year and one at its end. The first part of the interview is dedicated to guiding the students through comparing their two concept maps and by means of both explicit and non-explicit teaching. Our study showed that the explicit guidance in comparing the two concept maps was more effective than the non-explicit, eliciting a variety of different, more specific, types of interactions and patterns (e.g. 'hierarchy', 'dynamism', 'homeostasis') in the students' descriptions of the human body system. The reflection interview as a knowledge integration activity was found to be an effective tool for assessing the subjects' conceptual models of 'system complexity', and for identifying those aspects of a system that are most commonly misunderstood.

Developing Rational-Empirical Views of Intelligent Adaptive Behavior

DTIC Science & Technology

2004-08-01

biological frame to the information processing model and outline our understanding of intentions and beliefs that co-exist with rational and...notion that the evolution of cognition has produced memory/ knowledge systems that specialize in the processing of particular types of information ...1 PERMIS 2004 Developing Rational-Empirical Views of Intelligent Adaptive Behavior Gary Berg-Cross, Knowledge Strategies Potomac, Maryland

Effects of Subject-Matter Knowledge in the Teaching of Biology and Physics.

ERIC Educational Resources Information Center

Hashweh, Maher Z.

An analysis of science teacher's knowledge of specific biology and physics topics and the effects of this knowledge on their planning for instruction and on simulated teaching are discussed in this report. Six experienced secondary school teachers participated in the study. Each teacher's knowledge of a biology topic and a physics topic was…

77 FR 1942 - Homeland Security Science and Technology Advisory Committee (HSSTAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-12

... developments in systems engineering, cyber- security, knowledge management and how best to leverage related... contribution to a diverse range of science and technology topic areas (including chemical, biological, and... technology capabilities and needs, and the latest thinking in systems engineering), and their depth of...

ModeLang: a new approach for experts-friendly viral infections modeling.

PubMed

Wasik, Szymon; Prejzendanc, Tomasz; Blazewicz, Jacek

2013-01-01

Computational modeling is an important element of systems biology. One of its important applications is modeling complex, dynamical, and biological systems, including viral infections. This type of modeling usually requires close cooperation between biologists and mathematicians. However, such cooperation often faces communication problems because biologists do not have sufficient knowledge to understand mathematical description of the models, and mathematicians do not have sufficient knowledge to define and verify these models. In many areas of systems biology, this problem has already been solved; however, in some of these areas there are still certain problematic aspects. The goal of the presented research was to facilitate this cooperation by designing seminatural formal language for describing viral infection models that will be easy to understand for biologists and easy to use by mathematicians and computer scientists. The ModeLang language was designed in cooperation with biologists and its computer implementation was prepared. Tests proved that it can be successfully used to describe commonly used viral infection models and then to simulate and verify them. As a result, it can make cooperation between biologists and mathematicians modeling viral infections much easier, speeding up computational verification of formulated hypotheses.

ModeLang: A New Approach for Experts-Friendly Viral Infections Modeling

PubMed Central

Blazewicz, Jacek

2013-01-01

Computational modeling is an important element of systems biology. One of its important applications is modeling complex, dynamical, and biological systems, including viral infections. This type of modeling usually requires close cooperation between biologists and mathematicians. However, such cooperation often faces communication problems because biologists do not have sufficient knowledge to understand mathematical description of the models, and mathematicians do not have sufficient knowledge to define and verify these models. In many areas of systems biology, this problem has already been solved; however, in some of these areas there are still certain problematic aspects. The goal of the presented research was to facilitate this cooperation by designing seminatural formal language for describing viral infection models that will be easy to understand for biologists and easy to use by mathematicians and computer scientists. The ModeLang language was designed in cooperation with biologists and its computer implementation was prepared. Tests proved that it can be successfully used to describe commonly used viral infection models and then to simulate and verify them. As a result, it can make cooperation between biologists and mathematicians modeling viral infections much easier, speeding up computational verification of formulated hypotheses. PMID:24454531

Managing bioengineering complexity with AI techniques.

PubMed

Beal, Jacob; Adler, Aaron; Yaman, Fusun

2016-10-01

Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Discrimination of dynamical system models for biological and chemical processes.

PubMed

Lorenz, Sönke; Diederichs, Elmar; Telgmann, Regina; Schütte, Christof

2007-06-01

In technical chemistry, systems biology and biotechnology, the construction of predictive models has become an essential step in process design and product optimization. Accurate modelling of the reactions requires detailed knowledge about the processes involved. However, when concerned with the development of new products and production techniques for example, this knowledge often is not available due to the lack of experimental data. Thus, when one has to work with a selection of proposed models, the main tasks of early development is to discriminate these models. In this article, a new statistical approach to model discrimination is described that ranks models wrt. the probability with which they reproduce the given data. The article introduces the new approach, discusses its statistical background, presents numerical techniques for its implementation and illustrates the application to examples from biokinetics.

Creative design inspired by biological knowledge: Technologies and methods

NASA Astrophysics Data System (ADS)

Tan, Runhua; Liu, Wei; Cao, Guozhong; Shi, Yuan

2018-05-01

Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

An Educational Program of Mechatronics for Multidisciplinary Knowledge Acquisition

NASA Astrophysics Data System (ADS)

Watanuki, Keiichi; Kojima, Kazuyuki

Recently, as the technologies surrounding mechanical engineering have improved remarkably, the expectations for students who graduate from departments of mechanical engineering have increased. For example, in order to develop a mechatronics system, a student needs to integrate a wide variety of technologies, such as mechanical engineering, electrical and electronics engineering, and information technology. Therefore, from the perspective of educators, the current education system, which stresses expertizing each technology, should be replaced by an education system that stresses integrating multidisciplinary knowledge. In this paper, a trial education program for students of the department of mechanical engineering in our university, in which students are required to integrate multidisciplinary knowledge in order to develop a biologically-based robot, is described. Finally, the efficacy of the program is analyzed.

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

Bedform development and morphodynamics in mixed cohesive sediment substrates: the importance of winnowing and flocculation

NASA Astrophysics Data System (ADS)

Ye, Leiping; Parsons, Daniel; Manning, Andrew

2016-04-01

There remains a lack of process-based knowledge of sediment dynamics within flows over bedforms generated in complex mixtures of cohesionless sand and biologically-active cohesive muds in natural estuarine flow systems. The work to be presented forms a part of the UK NERC "COHesive BEDforms (COHBED)" project which aims to fill this gap in knowledge. Herein results from a field survey in sub-tidal zone of Dee estuary (NW, England) and a set of large-scale laboratory experiments, conducted using mixtures of non-cohesive sands, cohesive muds and Xanthan gum (as a proxy for the biological stickiness of Extracellular Polymeric Substances (EPS)) will be presented. The results indicate the significance of biological-active cohesive sediments in controlling winnowing rates and flocculation dynamics, which contributes significantly to rates of bedform evolution.

The Future of Weapons of Mass Destruction: Their Nature and Role in 2030

DTIC Science & Technology

2014-06-01

substantial improvements are al- lowed under the rubric of life extension. Other states are not so constrained and may find different ways to develop pure...The foregoing capabilities do not involve genetic manipulation or bioen- gineering; they utilize longstanding biological knowledge and processes. More...sophisticated understanding of biological systems (genomic and proteomic infor- mation) and processes ( genetic modification, bioengineering) for

The motivation to control and the origin of mind: exploring the life-mind joint point in the Tree of Knowledge System.

PubMed

Geary, David C

2005-01-01

The evolved function of brain, cognitive, affective, conscious-psychological, and behavioral systems is to enable animals to attempt to gain control of the social (e.g., mates), biological (e.g., prey), and physical (e.g., nesting spots) resources that have tended to covary with survival and reproductive outcomes during the species' evolutionary history. These resources generate information patterns that range from invariant to variant. Invariant information is consistent across generations and within lifetimes (e.g., the prototypical shape of a human face) and is associated with modular brain and cognitive systems that coalesce around the domains of folk psychology, folk biology, and folk physics. The processing of information in these domains is implicit and results in automatic bottom-up behavioral responses. Variant information varies across generations and within lifetimes (e.g., as in social dynamics) and is associated with plastic brain and cognitive systems and explicit, consciously driven top-down behavioral responses. The fundamentals of this motivation-to-control model are outlined and links are made to Henriques' (2004) Tree of Knowledge System and Behavioral Investment Theory.

The Integration of Javanese Indigenous Knowledge in Biology Learning Resources Development

NASA Astrophysics Data System (ADS)

Anazifa, D.; Hadi, R. F.

2017-02-01

The student’s difficulties in learning and understanding Biology concepts are caused by the adoption of scientific phenomenon that not suitable with the environment they live in. Students who comes from the Javanese background sometimes find the Biology concepts hard to understand. Science content that comes from the West sometimes is not suitable with the student’s background, because the cultural and geographical background that underlining the science development are different. It can potentially cause the clash in constructing knowledge of students. The proportion of western knowledge and indigenous knowledge has to be balanced, in order to give the scientific rationale of the natural phenomenon that faced by students in everyday life. The ethnoscience experienced by student is still in the form of concrete experience as a result of the interaction with the nature. As one of the largest tribe in Indonesia, Javanese has many unique cultures that can be adopted in science classroom especially in Biology class. The role on ethnoscience in the context of developing Biology learning resources is to connect the science concept with the real world situation. By considering indigenous knowledge as one of learning resources, teachers can start to adjust the Javanese indigenous knowledge into the curriculum. This paper is literature review which will present the background, rationale, and procedure in integrating Javanese indigenous knowledge into Biology classroom as learning resources. The integration of Javanese indigenous knowledge in Biology learning resources development is necessary in order to connect the Biology concept into real situation.

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Academic Preparation in Biology and Advocacy for Teaching Evolution: Biology versus Non-Biology Teachers

ERIC Educational Resources Information Center

Nehm, Ross H.; Kim, Sun Young; Sheppard, Keith

2009-01-01

Despite considerable focus on evolution knowledge-belief relationships, little research has targeted populations with strong content backgrounds, such as undergraduate degrees in biology. This study (1) measured precertified biology and non-biology teachers' (n = 167) knowledge of evolution and the nature of science; (2) quantified teacher…

Cognitive Processes in Folk Ornithology: The Identification of Gulls. Working Papers of the Language Behavior Research Laboratory, No. 42.

ERIC Educational Resources Information Center

Hunn, Eugene

Recent studies of folk biology clearly reveal the detailed empirical knowledge of living things which is an important and characteristic element of pre-scientific cultures. This paper attempts a contribution to the study of such systems of knowledge by analyzing the comparable skills of a few American birdwatchers. The process of identification of…

Predictive Models and Computational Embryology

EPA Science Inventory

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

A pharma perspective on the systems medicine and pharmacology of inflammation.

PubMed

Lahoz-Beneytez, Julio; Schnizler, Katrin; Eissing, Thomas

2015-02-01

Biological systems are complex and comprehend multiple scales of organisation. Hence, holistic approaches are necessary to capture the behaviour of these entities from the molecular and cellular to the whole organism level. This also applies to the understanding and treatment of different diseases. Traditional systems biology has been successful in describing different biological phenomena at the cellular level, but it still lacks of a holistic description of the multi-scale interactions within the body. The importance of the physiological context is of particular interest in inflammation. Regulatory agencies have urged the scientific community to increase the translational power of bio-medical research and it has been recognised that modelling and simulation could be a path to follow. Interestingly, in pharma R&D, modelling and simulation has been employed since a long time ago. Systems pharmacology, and particularly physiologically based pharmacokinetic/pharmacodynamic models, serve as a suitable framework to integrate the available and emerging knowledge at different levels of the drug development process. Systems medicine and pharmacology of inflammation will potentially benefit from this framework in order to better understand inflammatory diseases and to help to transfer the vast knowledge on the molecular and cellular level into a more physiological context. Ultimately, this may lead to reliable predictions of clinical outcomes such as disease progression or treatment efficacy, contributing thereby to a better care of patients. Copyright © 2014 Elsevier Inc. All rights reserved.

Biocuration at the Saccharomyces genome database.

PubMed

Skrzypek, Marek S; Nash, Robert S

2015-08-01

Saccharomyces Genome Database is an online resource dedicated to managing information about the biology and genetics of the model organism, yeast (Saccharomyces cerevisiae). This information is derived primarily from scientific publications through a process of human curation that involves manual extraction of data and their organization into a comprehensive system of knowledge. This system provides a foundation for further analysis of experimental data coming from research on yeast as well as other organisms. In this review we will demonstrate how biocuration and biocurators add a key component, the biological context, to our understanding of how genes, proteins, genomes and cells function and interact. We will explain the role biocurators play in sifting through the wealth of biological data to incorporate and connect key information. We will also discuss the many ways we assist researchers with their various research needs. We hope to convince the reader that manual curation is vital in converting the flood of data into organized and interconnected knowledge, and that biocurators play an essential role in the integration of scientific information into a coherent model of the cell. © 2015 Wiley Periodicals, Inc.

Biocuration at the Saccharomyces Genome Database

PubMed Central

Skrzypek, Marek S.; Nash, Robert S.

2015-01-01

Saccharomyces Genome Database is an online resource dedicated to managing information about the biology and genetics of the model organism, yeast (Saccharomyces cerevisiae). This information is derived primarily from scientific publications through a process of human curation that involves manual extraction of data and their organization into a comprehensive system of knowledge. This system provides a foundation for further analysis of experimental data coming from research on yeast as well as other organisms. In this review we will demonstrate how biocuration and biocurators add a key component, the biological context, to our understanding of how genes, proteins, genomes and cells function and interact. We will explain the role biocurators play in sifting through the wealth of biological data to incorporate and connect key information. We will also discuss the many ways we assist researchers with their various research needs. We hope to convince the reader that manual curation is vital in converting the flood of data into organized and interconnected knowledge, and that biocurators play an essential role in the integration of scientific information into a coherent model of the cell. PMID:25997651

Paratransgenesis applied for control of tsetse transmitted sleeping sickness.

PubMed

Aksoy, Serap; Weiss, Brian; Attardo, Geoffrey

2008-01-01

African trypanosomiasis (sleeping sickness) is a major cause of morbidity and mortality in Subsaharan Africa for human and animal health. In the absence of effective vaccines and efficacious drugs, vector control is an alternative intervention tool to break the disease cycle. This chapter describes the vectorial and symbiotic biology of tsetse with emphasis on the current knowledge on tsetse symbiont genomics and functional biology, and tsetse's trypanosome transmission capability. The ability to culture one of tsetse's commensal symbiotic microbes, Sodalis in vitro has allowed for the development of a genetic transformation system for this organism. Tsetse can be repopulated with the modified Sodalis symbiont, which can express foreign gene products (an approach we refer to as paratransgenic expression system). Expanding knowledge on tsetse immunity effectors, on genomics of tsetse symbionts and on tsetse's parasite transmission biology stands to enhance the development and potential application of paratransgenesis as a new vector-control strategy. We describe the hallmarks of the paratransgenic transformation technology where the modified symbionts expressing trypanocidal compounds can be used to manipulate host functions and lead to the control of trypanosomiasis by blocking trypanosome transmission in the tsetse vector.

Knowledge discovery and system biology in molecular medicine: an application on neurodegenerative diseases.

PubMed

Fattore, Matteo; Arrigo, Patrizio

2005-01-01

The possibility to study an organism in terms of system theory has been proposed in the past, but only the advancement of molecular biology techniques allow us to investigate the dynamical properties of a biological system in a more quantitative and rational way than before . These new techniques can gave only the basic level view of an organisms functionality. The comprehension of its dynamical behaviour depends on the possibility to perform a multiple level analysis. Functional genomics has stimulated the interest in the investigation the dynamical behaviour of an organism as a whole. These activities are commonly known as System Biology, and its interests ranges from molecules to organs. One of the more promising applications is the 'disease modeling'. The use of experimental models is a common procedure in pharmacological and clinical researches; today this approach is supported by 'in silico' predictive methods. This investigation can be improved by a combination of experimental and computational tools. The Machine Learning (ML) tools are able to process different heterogeneous data sources, taking into account this peculiarity, they could be fruitfully applied to support a multilevel data processing (molecular, cellular and morphological) that is the prerequisite for the formal model design; these techniques can allow us to extract the knowledge for mathematical model development. The aim of our work is the development and implementation of a system that combines ML and dynamical models simulations. The program is addressed to the virtual analysis of the pathways involved in neurodegenerative diseases. These pathologies are multifactorial diseases and the relevance of the different factors has not yet been well elucidated. This is a very complex task; in order to test the integrative approach our program has been limited to the analysis of the effects of a specific protein, the Cyclin dependent kinase 5 (CDK5) which relies on the induction of neuronal apoptosis. The system has a modular structure centred on a textual knowledge discovery approach. The text mining is the only way to enhance the capability to extract ,from multiple data sources, the information required for the dynamical simulator. The user may access the publically available modules through the following site: http://biocomp.ge.ismac.cnr.it.

Thiol/disulfide redox states in signaling and sensing

PubMed Central

Go, Young-Mi; Jones, Dean P.

2015-01-01

Rapid advances in redox systems biology are creating new opportunities to understand complexities of human disease and contributions of environmental exposures. New understanding of thiol-disulfide systems have occurred during the past decade as a consequence of the discoveries that thiol and disulfide systems are maintained in kinetically controlled steady-states displaced from thermodynamic equilibrium, that a widely distributed family of NADPH oxidases produces oxidants that function in cell signaling, and that a family of peroxiredoxins utilize thioredoxin as a reductant to complement the well-studied glutathione antioxidant system for peroxide elimination and redox regulation. This review focuses on thiol/disulfide redox state in biologic systems and the knowledge base available to support development of integrated redox systems biology models to better understand the function and dysfunction of thiol-disulfide redox systems. In particular, central principles have emerged concerning redox compartmentalization and utility of thiol/disulfide redox measures as indicators of physiologic function. Advances in redox proteomics show that, in addition to functioning in protein active sites and cell signaling, cysteine residues also serve as redox sensors to integrate biologic functions. These advances provide a framework for translation of redox systems biology concepts to practical use in understanding and treating human disease. Biological responses to cadmium, a widespread environmental agent, are used to illustrate the utility of these advances to the understanding of complex pleiotropic toxicities. PMID:23356510

PANDORA: keyword-based analysis of protein sets by integration of annotation sources.

PubMed

Kaplan, Noam; Vaaknin, Avishay; Linial, Michal

2003-10-01

Recent advances in high-throughput methods and the application of computational tools for automatic classification of proteins have made it possible to carry out large-scale proteomic analyses. Biological analysis and interpretation of sets of proteins is a time-consuming undertaking carried out manually by experts. We have developed PANDORA (Protein ANnotation Diagram ORiented Analysis), a web-based tool that provides an automatic representation of the biological knowledge associated with any set of proteins. PANDORA uses a unique approach of keyword-based graphical analysis that focuses on detecting subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA currently supports SwissProt keywords, NCBI Taxonomy, InterPro entries and the hierarchical classification terms from ENZYME, SCOP and GO databases. The integrated study of several annotation sources simultaneously allows a representation of biological relations of structure, function, cellular location, taxonomy, domains and motifs. PANDORA is also integrated into the ProtoNet system, thus allowing testing thousands of automatically generated clusters. We illustrate how PANDORA enhances the biological understanding of large, non-uniform sets of proteins originating from experimental and computational sources, without the need for prior biological knowledge on individual proteins.

Data to knowledge: how to get meaning from your result.

PubMed

Berman, Helen M; Gabanyi, Margaret J; Groom, Colin R; Johnson, John E; Murshudov, Garib N; Nicholls, Robert A; Reddy, Vijay; Schwede, Torsten; Zimmerman, Matthew D; Westbrook, John; Minor, Wladek

2015-01-01

Structural and functional studies require the development of sophisticated 'Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB 'super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results.

A framework for evolutionary systems biology

PubMed Central

Loewe, Laurence

2009-01-01

Background Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Results Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. Conclusion EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications. PMID:19239699

Exploring Biology Teachers' Pedagogical Content Knowledge in the Teaching of Genetics in Swaziland Science Classrooms

ERIC Educational Resources Information Center

Mthethwa-Kunene, Eunice; Onwu, Gilbert Oke; de Villiers, Rian

2015-01-01

This study explored the pedagogical content knowledge (PCK) and its development of four experienced biology teachers in the context of teaching school genetics. PCK was defined in terms of teacher content knowledge, pedagogical knowledge and knowledge of students' preconceptions and learning difficulties. Data sources of teacher knowledge base…

Holistic systems biology approaches to molecular mechanisms of human helper T cell differentiation to functionally distinct subsets.

PubMed

Chen, Z; Lönnberg, T; Lahesmaa, R

2013-08-01

Current knowledge of helper T cell differentiation largely relies on data generated from mouse studies. To develop therapeutical strategies combating human diseases, understanding the molecular mechanisms how human naïve T cells differentiate to functionally distinct T helper (Th) subsets as well as studies on human differentiated Th cell subsets is particularly valuable. Systems biology approaches provide a holistic view of the processes of T helper differentiation, enable discovery of new factors and pathways involved and generation of new hypotheses to be tested to improve our understanding of human Th cell differentiation and immune-mediated diseases. Here, we summarize studies where high-throughput systems biology approaches have been exploited to human primary T cells. These studies reveal new factors and signalling pathways influencing T cell differentiation towards distinct subsets, important for immune regulation. Such information provides new insights into T cell biology and into targeting immune system for therapeutic interventions. © 2013 John Wiley & Sons Ltd.

DAISY: a new software tool to test global identifiability of biological and physiological systems

PubMed Central

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D’Angiò, Leontina

2009-01-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/. PMID:17707944

Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

PubMed

Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

2017-03-01

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Making evolutionary biology a basic science for medicine

PubMed Central

Nesse, Randolph M.; Bergstrom, Carl T.; Ellison, Peter T.; Flier, Jeffrey S.; Gluckman, Peter; Govindaraju, Diddahally R.; Niethammer, Dietrich; Omenn, Gilbert S.; Perlman, Robert L.; Schwartz, Mark D.; Thomas, Mark G.; Stearns, Stephen C.; Valle, David

2010-01-01

New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease. PMID:19918069

Evolution in health and medicine Sackler colloquium: Making evolutionary biology a basic science for medicine.

PubMed

Nesse, Randolph M; Bergstrom, Carl T; Ellison, Peter T; Flier, Jeffrey S; Gluckman, Peter; Govindaraju, Diddahally R; Niethammer, Dietrich; Omenn, Gilbert S; Perlman, Robert L; Schwartz, Mark D; Thomas, Mark G; Stearns, Stephen C; Valle, David

2010-01-26

New applications of evolutionary biology in medicine are being discovered at an accelerating rate, but few physicians have sufficient educational background to use them fully. This article summarizes suggestions from several groups that have considered how evolutionary biology can be useful in medicine, what physicians should learn about it, and when and how they should learn it. Our general conclusion is that evolutionary biology is a crucial basic science for medicine. In addition to looking at established evolutionary methods and topics, such as population genetics and pathogen evolution, we highlight questions about why natural selection leaves bodies vulnerable to disease. Knowledge about evolution provides physicians with an integrative framework that links otherwise disparate bits of knowledge. It replaces the prevalent view of bodies as machines with a biological view of bodies shaped by evolutionary processes. Like other basic sciences, evolutionary biology needs to be taught both before and during medical school. Most introductory biology courses are insufficient to establish competency in evolutionary biology. Premedical students need evolution courses, possibly ones that emphasize medically relevant aspects. In medical school, evolutionary biology should be taught as one of the basic medical sciences. This will require a course that reviews basic principles and specific medical applications, followed by an integrated presentation of evolutionary aspects that apply to each disease and organ system. Evolutionary biology is not just another topic vying for inclusion in the curriculum; it is an essential foundation for a biological understanding of health and disease.

Predictive Models and Computational Toxicology (II IBAMTOX)

EPA Science Inventory

EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

The Lymphatic System and Pancreatic Cancer

PubMed Central

Fink, Darci M.; Steele, Maria M.; Hollingsworth, Michael A.

2016-01-01

This review summarizes current knowledge of the biology, pathology and clinical understanding of lymphatic invasion and metastasis in pancreatic cancer. We discuss the clinical and biological consequences of lymphatic invasion and metastasis, including paraneoplastic effects on immune responses and consider the possible benefit of therapies to treat tumors that are localized to lymphatics. A review of current techniques and methods to study interactions between tumors and lymphatics is presented. PMID:26742462

Of truth and pathways: chasing bits of information through myriads of articles.

PubMed

Krauthammer, Michael; Kra, Pauline; Iossifov, Ivan; Gomez, Shawn M; Hripcsak, George; Hatzivassiloglou, Vasileios; Friedman, Carol; Rzhetsky, Andrey

2002-01-01

Knowledge on interactions between molecules in living cells is indispensable for theoretical analysis and practical applications in modern genomics and molecular biology. Building such networks relies on the assumption that the correct molecular interactions are known or can be identified by reading a few research articles. However, this assumption does not necessarily hold, as truth is rather an emerging property based on many potentially conflicting facts. This paper explores the processes of knowledge generation and publishing in the molecular biology literature using modelling and analysis of real molecular interaction data. The data analysed in this article were automatically extracted from 50000 research articles in molecular biology using a computer system called GeneWays containing a natural language processing module. The paper indicates that truthfulness of statements is associated in the minds of scientists with the relative importance (connectedness) of substances under study, revealing a potential selection bias in the reporting of research results. Aiming at understanding the statistical properties of the life cycle of biological facts reported in research articles, we formulate a stochastic model describing generation and propagation of knowledge about molecular interactions through scientific publications. We hope that in the future such a model can be useful for automatically producing consensus views of molecular interaction data.

Simulations in Medicine and Biology: Insights and perspectives

NASA Astrophysics Data System (ADS)

Spyrou, George M.

2015-01-01

Modern medicine and biology have been transformed into quantitative sciences of high complexity, with challenging objectives. The aims of medicine are related to early diagnosis, effective therapy, accurate intervention, real time monitoring, procedures/systems/instruments optimization, error reduction, and knowledge extraction. Concurrently, following the explosive production of biological data concerning DNA, RNA, and protein biomolecules, a plethora of questions has been raised in relation to their structure and function, the interactions between them, their relationships and dependencies, their regulation and expression, their location, and their thermodynamic characteristics. Furthermore, the interplay between medicine and biology gives rise to fields like molecular medicine and systems biology which are further interconnected with physics, mathematics, informatics, and engineering. Modelling and simulation is a powerful tool in the fields of Medicine and Biology. Simulating the phenomena hidden inside a diagnostic or therapeutic medical procedure, we are able to obtain control on the whole system and perform multilevel optimization. Furthermore, modelling and simulation gives insights in the various scales of biological representation, facilitating the understanding of the huge amounts of derived data and the related mechanisms behind them. Several examples, as well as the insights and the perspectives of simulations in biomedicine will be presented.

Student teachers' pedagogical content knowledge for teaching systems thinking: effects of different interventions

NASA Astrophysics Data System (ADS)

Rosenkränzer, Frank; Hörsch, Christian; Schuler, Stephan; Riess, Werner

2017-09-01

Systems' thinking has become increasingly relevant not only in education for sustainable development but also in everyday life. Even if teachers know the dynamics and complexity of living systems in biology and geography, they might not be able to effectively explain it to students. Teachers need an understanding of systems and their behaviour (content knowledge), and they also need to know how systems thinking can be fostered in students (pedagogical content knowledge (PCK)). But the effective development of teachers' professional knowledge in teaching systems thinking is empirically uncertain. From a larger study (SysThema) that investigated teaching systems thinking, this article reports the effects of the three different interventions (technical course, didactic course and mixed course) in student teachers' PCK for teaching systems thinking. The results show that student teachers' PCK for teaching systems thinking can be promoted in teacher education. The conclusion to be drawn from our findings is that a technically orientated course without didactical aspects seems to be less effective in fostering student teachers' PCK for teaching systems thinking. The results inform educators in enhancing curricula of future academic track and non-academic track teacher education.

Fostering Students' Conceptual Knowledge in Biology in the Context of German National Education Standards

NASA Astrophysics Data System (ADS)

Förtsch, Christian; Dorfner, Tobias; Baumgartner, Julia; Werner, Sonja; von Kotzebue, Lena; Neuhaus, Birgit J.

2018-04-01

The German National Education Standards (NES) for biology were introduced in 2005. The content part of the NES emphasizes fostering conceptual knowledge. However, there are hardly any indications of what such an instructional implementation could look like. We introduce a theoretical framework of an instructional approach to foster students' conceptual knowledge as demanded in the NES (Fostering Conceptual Knowledge) including instructional practices derived from research on single core ideas, general psychological theories, and biology-specific features of instructional quality. First, we aimed to develop a rating manual, which is based on this theoretical framework. Second, we wanted to describe current German biology instruction according to this approach and to quantitatively analyze its effectiveness. And third, we aimed to provide qualitative examples of this approach to triangulate our findings. In a first step, we developed a theoretically devised rating manual to measure Fostering Conceptual Knowledge in videotaped lessons. Data for quantitative analysis included 81 videotaped biology lessons of 28 biology teachers from different German secondary schools. Six hundred forty students completed a questionnaire on their situational interest after each lesson and an achievement test. Results from multilevel modeling showed significant positive effects of Fostering Conceptual Knowledge on students' achievement and situational interest. For qualitative analysis, we contrasted instruction of four teachers, two with high and two with low student achievement and situational interest using the qualitative method of thematic analysis. Qualitative analysis revealed five main characteristics describing Fostering Conceptual Knowledge. Therefore, implementing Fostering Conceptual Knowledge in biology instruction seems promising. Examples of how to implement Fostering Conceptual Knowledge in instruction are shown and discussed.

Where Does the Drink Go?

ERIC Educational Resources Information Center

Tunnicliffe, Sue Dale

2004-01-01

In England the National Curriculum does not specifically mention the excretory system at key stages 1 and 2. Research by Reiss and Tunnicliffe (2001, 2002) has shown that children's knowledge of the organs and organ systems in their bodies increases with age but remains incomplete, even at maturity, unless they specialise in studying biology. The…

Amplification without instability: applying fluid dynamical insights in chemistry and biology

NASA Astrophysics Data System (ADS)

McCoy, Jonathan H.

2013-11-01

While amplification of small perturbations often arises from instability, transient amplification is possible locally even in asymptotically stable systems. That is, knowledge of a system's stability properties can mislead one's intuition for its transient behaviors. This insight, which has an interesting history in fluid dynamics, has more recently been rediscovered in ecology. Surprisingly, many nonlinear fluid dynamical and ecological systems share linear features associated with transient amplification of noise. This paper aims to establish that these features are widespread in many other disciplines concerned with noisy systems, especially chemistry, cell biology and molecular biology. Here, using classic nonlinear systems and the graphical language of network science, we explore how the noise amplification problem can be reframed in terms of activatory and inhibitory interactions between dynamical variables. The interaction patterns considered here are found in a great variety of systems, ranging from autocatalytic reactions and activator-inhibitor systems to influential models of nerve conduction, glycolysis, cell signaling and circadian rhythms.

Teachers' Journal Club: Bridging between the Dynamics of Biological Discoveries and Biology Teachers

ERIC Educational Resources Information Center

Brill, Gilat; Falk, Hedda; Yarden, Anat

2003-01-01

Since biology is one of the most dynamic research fields within the natural sciences, the gap between the accumulated knowledge in biology and the knowledge that is taught in schools, increases rapidly with time. Our long-term objective is to develop means to bridge between the dynamics of biological discoveries and the biology teachers and…

Do Zoo Visitors Need Zoology Knowledge to Understand Conservation Messages? An Exploration of the Public Understanding of Animal Biology and of the Conservation of Biodiversity in a Zoo Setting

ERIC Educational Resources Information Center

Dove, Tracy; Byrne, Jenny

2014-01-01

This study explores the current knowledge and understanding about animal biology of zoo visitors and investigates whether knowledge of animal biology influences the ability of people to understand how human activity affects biodiversity. Zoos can play a role in the development of scientific literacy in the fields of animal biology and biodiversity…

Systems biology of the structural proteome.

PubMed

Brunk, Elizabeth; Mih, Nathan; Monk, Jonathan; Zhang, Zhen; O'Brien, Edward J; Bliven, Spencer E; Chen, Ke; Chang, Roger L; Bourne, Philip E; Palsson, Bernhard O

2016-03-11

The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

Development, Evaluation, and Validation of a Paper-and-Pencil Test for Measuring Two Components of Biology Teachers' Pedagogical Content Knowledge Concerning the "Cardiovascular System"

ERIC Educational Resources Information Center

Schmelzing, Stephan; van Driel, Jan H.; Jüttner, Melanie; Brandenbusch, Stefanie; Sandmann, Angela; Neuhaus, Birgit J.

2013-01-01

One main focus of teacher education research concentrates on teachers' pedagogical content knowledge (PCK). It has been shown that teachers' PCK correlates with teaching effectiveness as well as with students' achievement gains. Teachers' PCK should be analyzed as one of the main important components to evaluate professional…

Planting molecular functions in an ecological context with Arabidopsis thaliana.

PubMed

Krämer, Ute

2015-03-25

The vascular plant Arabidopsis thaliana is a central genetic model and universal reference organism in plant and crop science. The successful integration of different fields of research in the study of A. thaliana has made a large contribution to our molecular understanding of key concepts in biology. The availability and active development of experimental tools and resources, in combination with the accessibility of a wealth of cumulatively acquired knowledge about this plant, support the most advanced systems biology approaches among all land plants. Research in molecular ecology and evolution has also brought the natural history of A. thaliana into the limelight. This article showcases our current knowledge of the natural history of A. thaliana from the perspective of the most closely related plant species, providing an evolutionary framework for interpreting novel findings and for developing new hypotheses based on our knowledge of this plant.

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

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

Genome Editing of Erythroid Cell Culture Model Systems.

PubMed

Yik, Jinfen J; Crossley, Merlin; Quinlan, Kate G R

2018-01-01

Genome editing to introduce specific mutations or to knock out genes in model cell systems has become an efficient platform for research in the fields of molecular biology, genetics, and cell biology. With recent rapid improvements in genome editing techniques, bench-top manipulation of the genome in cell culture has become progressively easier. The application of this knowledge to erythroid cell culture systems now allows the rapid analysis of the downstream effects of virtually any engineered gene disruption or modification in cell systems. Here, we describe a CRISPR/Cas9-based approach to making genomic modifications in erythroid lineage cells which we have successfully used in both murine (MEL) and human (K562) erythroleukaemia immortalized cell lines.

Synthetic biology and the ethics of knowledge

PubMed Central

Douglas, Thomas; Savulescu, Julian

2011-01-01

Synthetic biologists aim to generate biological organisms according to rational design principles. Their work may have many beneficial applications, but it also raises potentially serious ethical concerns. In this article, we consider what attention the discipline demands from bioethicists. We argue that the most important issue for ethicists to examine is the risk that knowledge from synthetic biology will be misused, for example, in biological terrorism or warfare. To adequately address this concern, bioethics will need to broaden its scope, contemplating not just the means by which scientific knowledge is produced, but also what kinds of knowledge should be sought and disseminated. PMID:20935316

Toward systems metabolic engineering of Aspergillus and Pichia species for the production of chemicals and biofuels.

PubMed

Caspeta, Luis; Nielsen, Jens

2013-05-01

Recently genome sequence data have become available for Aspergillus and Pichia species of industrial interest. This has stimulated the use of systems biology approaches for large-scale analysis of the molecular and metabolic responses of Aspergillus and Pichia under defined conditions, which has resulted in much new biological information. Case-specific contextualization of this information has been performed using comparative and functional genomic tools. Genomics data are also the basis for constructing genome-scale metabolic models, and these models have helped in the contextualization of knowledge on the fundamental biology of Aspergillus and Pichia species. Furthermore, with the availability of these models, the engineering of Aspergillus and Pichia is moving from traditional approaches, such as random mutagenesis, to a systems metabolic engineering approach. Here we review the recent trends in systems biology of Aspergillus and Pichia species, highlighting the relevance of these developments for systems metabolic engineering of these organisms for the production of hydrolytic enzymes, biofuels and chemicals from biomass. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

PubMed Central

Liao, David; Tlsty, Thea D.

2014-01-01

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments. PMID:25097752

Mainstreaming Caenorhabditis elegans in experimental evolution.

PubMed

Gray, Jeremy C; Cutter, Asher D

2014-03-07

Experimental evolution provides a powerful manipulative tool for probing evolutionary process and mechanism. As this approach to hypothesis testing has taken purchase in biology, so too has the number of experimental systems that use it, each with its own unique strengths and weaknesses. The depth of biological knowledge about Caenorhabditis nematodes, combined with their laboratory tractability, positions them well for exploiting experimental evolution in animal systems to understand deep questions in evolution and ecology, as well as in molecular genetics and systems biology. To date, Caenorhabditis elegans and related species have proved themselves in experimental evolution studies of the process of mutation, host-pathogen coevolution, mating system evolution and life-history theory. Yet these organisms are not broadly recognized for their utility for evolution experiments and remain underexploited. Here, we outline this experimental evolution work undertaken so far in Caenorhabditis, detail simple methodological tricks that can be exploited and identify research areas that are ripe for future discovery.

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

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

Biological knowledge is more tentative than physics knowledge: Taiwan high school adolescents' views about the nature of biology and physics.

PubMed

Tsai, Chin-Chung

2006-01-01

Many educational psychologists believe that students' beliefs about the nature of knowledge, called epistemological beliefs, play an essential role in their learning process. Educators also stress the importance of helping students develop a better understanding of the nature of knowledge. The tentative and creative nature of science is often highlighted by contemporary science educators. However, few previous studies have investigated students' views of more specific knowledge domains, such as biology and physics. Consequently, this study developed a questionnaire to assess students' views specifically about the tentative and creative nature of biology and physics. From a survey of 428 Taiwanese high school adolescents, this study found that although students showed an understanding of the tentative and creative nature of biology and physics, they expressed stronger agreement as to the tentativeness of biology than that of physics. In addition, male students tended to agree more than did females that physics had tentative and creative features and that biology had tentative features. Also, students with more years of science education tended to show more agreement regarding the creative nature of physics and biology than those with fewer years.

TERATOLOGY v2.0 – building a path forward

EPA Science Inventory

Unraveling the complex relationships between environmental factors and early life susceptibility in assessing the risk for adverse pregnancy outcomes requires advanced knowledge of biological systems. Large datasets and deep data-mining tools are emerging resources for predictive...

Student Perceived and Determined Knowledge of Biology Concepts in an Upper-Level Biology Course

ERIC Educational Resources Information Center

Ziegler, Brittany; Montplaisir, Lisa

2014-01-01

Students who lack metacognitive skills can struggle with the learning process. To be effective learners, students should recognize what they know and what they do not know. This study examines the relationship between students' perception of their knowledge and determined knowledge in an upper-level biology course utilizing a pre/posttest…

A unique large-scale undergraduate research experience in molecular systems biology for non-mathematics majors.

PubMed

Kappler, Ulrike; Rowland, Susan L; Pedwell, Rhianna K

2017-05-01

Systems biology is frequently taught with an emphasis on mathematical modeling approaches. This focus effectively excludes most biology, biochemistry, and molecular biology students, who are not mathematics majors. The mathematical focus can also present a misleading picture of systems biology, which is a multi-disciplinary pursuit requiring collaboration between biochemists, bioinformaticians, and mathematicians. This article describes an authentic large-scale undergraduate research experience (ALURE) in systems biology that incorporates proteomics, bacterial genomics, and bioinformatics in the one exercise. This project is designed to engage students who have a basic grounding in protein chemistry and metabolism and no mathematical modeling skills. The pedagogy around the research experience is designed to help students attack complex datasets and use their emergent metabolic knowledge to make meaning from large amounts of raw data. On completing the ALURE, participants reported a significant increase in their confidence around analyzing large datasets, while the majority of the cohort reported good or great gains in a variety of skills including "analysing data for patterns" and "conducting database or internet searches." An environmental scan shows that this ALURE is the only undergraduate-level system-biology research project offered on a large-scale in Australia; this speaks to the perceived difficulty of implementing such an opportunity for students. We argue however, that based on the student feedback, allowing undergraduate students to complete a systems-biology project is both feasible and desirable, even if the students are not maths and computing majors. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(3):235-248, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology.

PubMed

Weckwerth, Wolfram

2011-12-10

Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO(2)-neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as Miscanthus and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, fungi, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution. Copyright © 2011 Elsevier B.V. All rights reserved.

Using the Biology Card Sorting Task to Measure Changes in Conceptual Expertise during Postsecondary Biology Education

ERIC Educational Resources Information Center

Bissonnette, Sarah A.; Combs, Elijah D.; Nagami, Paul H.; Byers, Victor; Fernandez, Juliana; Le, Dinh; Realin, Jared; Woodham, Selina; Smith, Julia I.; Tanner, Kimberly D.

2017-01-01

While there have been concerted efforts to reform undergraduate biology toward teaching students to organize their conceptual knowledge like experts, there are few tools that attempt to measure this. We previously developed the Biology Card Sorting Task (BCST), designed to probe how individuals organize their conceptual biological knowledge.…

Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't

PubMed Central

Roudi, Yasser; Nirenberg, Sheila; Latham, Peter E.

2009-01-01

One of the most critical problems we face in the study of biological systems is building accurate statistical descriptions of them. This problem has been particularly challenging because biological systems typically contain large numbers of interacting elements, which precludes the use of standard brute force approaches. Recently, though, several groups have reported that there may be an alternate strategy. The reports show that reliable statistical models can be built without knowledge of all the interactions in a system; instead, pairwise interactions can suffice. These findings, however, are based on the analysis of small subsystems. Here, we ask whether the observations will generalize to systems of realistic size, that is, whether pairwise models will provide reliable descriptions of true biological systems. Our results show that, in most cases, they will not. The reason is that there is a crossover in the predictive power of pairwise models: If the size of the subsystem is below the crossover point, then the results have no predictive power for large systems. If the size is above the crossover point, then the results may have predictive power. This work thus provides a general framework for determining the extent to which pairwise models can be used to predict the behavior of large biological systems. Applied to neural data, the size of most systems studied so far is below the crossover point. PMID:19424487

A Problem-Sorting Task Detects Changes in Undergraduate Biological Expertise over a Single Semester

PubMed Central

Hoskinson, Anne-Marie; Maher, Jessica Middlemis; Bekkering, Cody; Ebert-May, Diane

2017-01-01

Calls for undergraduate biology reform share similar goals: to produce people who can organize, use, connect, and communicate about biological knowledge. Achieving these goals requires students to gain disciplinary expertise. Experts organize, access, and apply disciplinary knowledge differently than novices, and expertise is measurable. By asking introductory biology students to sort biological problems, we investigated whether they changed how they organized and linked biological ideas over one semester of introductory biology. We administered the Biology Card Sorting Task to 751 students enrolled in their first or second introductory biology course focusing on either cellular–molecular or organismal–population topics, under structured or unstructured sorting conditions. Students used a combination of superficial, deep, and yet-uncharacterized ways of organizing and connecting biological knowledge. In some cases, this translated to more expert-like ways of organizing knowledge over a single semester, best predicted by whether students were enrolled in their first or second semester of biology and by the sorting condition completed. In addition to illuminating differences between novices and experts, our results show that card sorting is a robust way of detecting changes in novices’ biological expertise—even in heterogeneous populations of novice biology students over the time span of a single semester. PMID:28408406

No question about exciting questions in cell biology.

PubMed

Pollard, Thomas D

2013-12-01

Although we have a good grasp of many important processes in cell biology, including knowledge of many molecules involved and how they interact with each other, we still do not understand most of the dynamical features that are the essence of living systems. Fortunately, we now have the ability to dissect biological systems in enough detail to understand their dynamics, including the use of mathematical models to account for past observations and predict future experiments. This deep level of mechanistic understanding should be our goal—not simply to satisfy our scientific curiosity, but also to understand the causes of disease well enough to predict risks, make early diagnoses, and treat effectively. Many big questions remain to be answered before we reach this goal of understanding cellular dynamics.

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

Attractor Signaling Models for Discovery of Combinatorial Therapies

DTIC Science & Technology

2013-09-01

year!survival!rate!for!this! disease ! less!than!15%.!Over!the!years,!many!specific!mechanisms!associated!with!drug!resistance!in!lung!cancer! have!been...reprogramming of pluripotent stem cells [4]. More- over, it has been suggested that a biological system in a chronic or therapy-resistant disease state can...designing new therapeutic methods for complex diseases such as can- cer. Even if our knowledge of biological networks is in- complete, fast progress

Attractor Signaling Models for Discovery of Combinatorial Therapies

DTIC Science & Technology

2014-11-01

acquired!drug!resistance!still!makes!the!5-year!survival!rate!for!this! disease ! less!than!15%.!Over!the!years,!many!specific!mechanisms!associated!with!drug...Moreover, it has been suggested that a biological system in a chronic or therapy- resistant disease state can be seen as a network that has become...therapeutic methods for complex diseases such as cancer. Even if our knowledge of biological networks is incomplete, rapid progress is currently being

Data to knowledge: how to get meaning from your result

PubMed Central

Berman, Helen M.; Gabanyi, Margaret J.; Groom, Colin R.; Johnson, John E.; Murshudov, Garib N.; Nicholls, Robert A.; Reddy, Vijay; Schwede, Torsten; Zimmerman, Matthew D.; Westbrook, John; Minor, Wladek

2015-01-01

Structural and functional studies require the development of sophisticated ‘Big Data’ technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB ‘super’ laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results. PMID:25610627

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

Using Student Self-Assessment of Biological Concepts in an Introductory Biology Course.

ERIC Educational Resources Information Center

Heinze-Fry, Jane Ann

1992-01-01

Describes the author's methods to establish what students enrolled in an introductory biology course for nonmajors know about biology prior to instruction. The project also compared preinstructional knowledge to postinstructional knowledge. Beginning students knew the least about plant transport/chemical control and cellular metabolism. Students…

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods.

PubMed

Gabanyi, Margaret J; Adams, Paul D; Arnold, Konstantin; Bordoli, Lorenza; Carter, Lester G; Flippen-Andersen, Judith; Gifford, Lida; Haas, Juergen; Kouranov, Andrei; McLaughlin, William A; Micallef, David I; Minor, Wladek; Shah, Raship; Schwede, Torsten; Tao, Yi-Ping; Westbrook, John D; Zimmerman, Matthew; Berman, Helen M

2011-07-01

The Protein Structure Initiative's Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org ) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI's high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology.

Integrated Computational Analysis of Genes Associated with Human Hereditary Insensitivity to Pain. A Drug Repurposing Perspective

PubMed Central

Lötsch, Jörn; Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred

2017-01-01

Genes causally involved in human insensitivity to pain provide a unique molecular source of studying the pathophysiology of pain and the development of novel analgesic drugs. The increasing availability of “big data” enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 20 genes causally involved in human hereditary insensitivity to pain with the knowledge about the functions of thousands of genes. An integrated computational analysis proposed that among the functions of this set of genes, the processes related to nervous system development and to ceramide and sphingosine signaling pathways are particularly important. This is in line with earlier suggestions to use these pathways as therapeutic target in pain. Following identification of the biological processes characterizing hereditary insensitivity to pain, the biological processes were used for a similarity analysis with the functions of n = 4,834 database-queried drugs. Using emergent self-organizing maps, a cluster of n = 22 drugs was identified sharing important functional features with hereditary insensitivity to pain. Several members of this cluster had been implicated in pain in preclinical experiments. Thus, the present concept of machine-learned knowledge discovery for pain research provides biologically plausible results and seems to be suitable for drug discovery by identifying a narrow choice of repurposing candidates, demonstrating that contemporary machine-learned methods offer innovative approaches to knowledge discovery from available evidence. PMID:28848388

Defence mechanisms: the role of physiology in current and future environmental protection paradigms

PubMed Central

Glover, Chris N

2018-01-01

Abstract Ecological risk assessments principally rely on simplified metrics of organismal sensitivity that do not consider mechanism or biological traits. As such, they are unable to adequately extrapolate from standard laboratory tests to real-world settings, and largely fail to account for the diversity of organisms and environmental variables that occur in natural environments. However, an understanding of how stressors influence organism health can compensate for these limitations. Mechanistic knowledge can be used to account for species differences in basal biological function and variability in environmental factors, including spatial and temporal changes in the chemical, physical and biological milieu. Consequently, physiological understanding of biological function, and how this is altered by stressor exposure, can facilitate proactive, predictive risk assessment. In this perspective article, existing frameworks that utilize physiological knowledge (e.g. biotic ligand models, adverse outcomes pathways and mechanistic effect models), are outlined, and specific examples of how mechanistic understanding has been used to predict risk are highlighted. Future research approaches and data needs for extending the incorporation of physiological information into ecological risk assessments are discussed. Although the review focuses on chemical toxicants in aquatic systems, physical and biological stressors and terrestrial environments are also briefly considered. PMID:29564135

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Limnology. Student Fieldbook.

ERIC Educational Resources Information Center

Jones, Michael

This student fieldbook provides exercises for a three-week course in limnology. Exercises emphasize applications of knowledge in chemistry, physics, and biology to understand the natural operation of freshwater systems. Fourteen field exercises include: (1) testing for water quality; (2) determination of water temperature, turbidity, dissolved…

The micronutrient genomics project: a community-driven knowledge base for micronutrient research

USDA-ARS?s Scientific Manuscript database

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it...

A Computational Framework for Bioimaging Simulation.

PubMed

Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.

Systems biology of stored blood cells: can it help to extend the expiration date?

PubMed

Paglia, Giuseppe; Palsson, Bernhard Ø; Sigurjonsson, Olafur E

2012-12-05

With increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics. Copyright © 2012 Elsevier B.V. All rights reserved.

A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying

PubMed Central

2014-01-01

Background In-silico models that attempt to capture and describe the physiological behavior of biological organisms, including humans, are intrinsically complex and time consuming to build and simulate in a computing environment. The level of detail of description incorporated in the model depends on the knowledge of the system’s behavior at that level. This knowledge is gathered from the literature and/or improved by knowledge obtained from new experiments. Thus model development is an iterative developmental procedure. The objective of this paper is to describe a new plug and play scheme that offers increased flexibility and ease-of-use for modeling and simulating physiological behavior of biological organisms. Methods This scheme requires the modeler (user) first to supply the structure of the interacting components and experimental data in a tabular format. The behavior of the components described in a mathematical form, also provided by the modeler, is externally linked during simulation. The advantage of the plug and play scheme for modeling is that it requires less programming effort and can be quickly adapted to newer modeling requirements while also paving the way for dynamic model building. Results As an illustration, the paper models the dynamics of gastric emptying behavior experienced by humans. The flexibility to adapt the model to predict the gastric emptying behavior under varying types of nutrient infusion in the intestine (ileum) is demonstrated. The predictions were verified with a human intervention study. The error in predicting the half emptying time was found to be less than 6%. Conclusions A new plug-and-play scheme for biological systems modeling was developed that allows changes to the modeled structure and behavior with reduced programming effort, by abstracting the biological system into a network of smaller sub-systems with independent behavior. In the new scheme, the modeling and simulation becomes an automatic machine readable and executable task. PMID:24917054

Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

PubMed

Gizak, Agnieszka; Rakus, Dariusz

2016-01-11

Molecular and cellular biology methodology is traditionally based on the reasoning called "the mechanistic explanation". In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems' complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

IntegromeDB: an integrated system and biological search engine.

PubMed

Baitaluk, Michael; Kozhenkov, Sergey; Dubinina, Yulia; Ponomarenko, Julia

2012-01-19

With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.

Extending human perception of electromagnetic radiation to the UV region through biologically inspired photochromic fuzzy logic (BIPFUL) systems.

PubMed

Gentili, Pier Luigi; Rightler, Amanda L; Heron, B Mark; Gabbutt, Christopher D

2016-01-25

Photochromic fuzzy logic systems have been designed that extend human visual perception into the UV region. The systems are founded on a detailed knowledge of the activation wavelengths and quantum yields of a series of thermally reversible photochromic compounds. By appropriate matching of the photochromic behaviour unique colour signatures are generated in response differing UV activation frequencies.

Biological Stability of Drinking Water: Controlling Factors, Methods, and Challenges.

PubMed

Prest, Emmanuelle I; Hammes, Frederik; van Loosdrecht, Mark C M; Vrouwenvelder, Johannes S

2016-01-01

Biological stability of drinking water refers to the concept of providing consumers with drinking water of same microbial quality at the tap as produced at the water treatment facility. However, uncontrolled growth of bacteria can occur during distribution in water mains and premise plumbing, and can lead to hygienic (e.g., development of opportunistic pathogens), aesthetic (e.g., deterioration of taste, odor, color) or operational (e.g., fouling or biocorrosion of pipes) problems. Drinking water contains diverse microorganisms competing for limited available nutrients for growth. Bacterial growth and interactions are regulated by factors, such as (i) type and concentration of available organic and inorganic nutrients, (ii) type and concentration of residual disinfectant, (iii) presence of predators, such as protozoa and invertebrates, (iv) environmental conditions, such as water temperature, and (v) spatial location of microorganisms (bulk water, sediment, or biofilm). Water treatment and distribution conditions in water mains and premise plumbing affect each of these factors and shape bacterial community characteristics (abundance, composition, viability) in distribution systems. Improved understanding of bacterial interactions in distribution systems and of environmental conditions impact is needed for better control of bacterial communities during drinking water production and distribution. This article reviews (i) existing knowledge on biological stability controlling factors and (ii) how these factors are affected by drinking water production and distribution conditions. In addition, (iii) the concept of biological stability is discussed in light of experience with well-established and new analytical methods, enabling high throughput analysis and in-depth characterization of bacterial communities in drinking water. We discussed, how knowledge gained from novel techniques will improve design and monitoring of water treatment and distribution systems in order to maintain good drinking water microbial quality up to consumer's tap. A new definition and methodological approach for biological stability is proposed.

Biological Stability of Drinking Water: Controlling Factors, Methods, and Challenges

PubMed Central

Prest, Emmanuelle I.; Hammes, Frederik; van Loosdrecht, Mark C. M.; Vrouwenvelder, Johannes S.

2016-01-01

Biological stability of drinking water refers to the concept of providing consumers with drinking water of same microbial quality at the tap as produced at the water treatment facility. However, uncontrolled growth of bacteria can occur during distribution in water mains and premise plumbing, and can lead to hygienic (e.g., development of opportunistic pathogens), aesthetic (e.g., deterioration of taste, odor, color) or operational (e.g., fouling or biocorrosion of pipes) problems. Drinking water contains diverse microorganisms competing for limited available nutrients for growth. Bacterial growth and interactions are regulated by factors, such as (i) type and concentration of available organic and inorganic nutrients, (ii) type and concentration of residual disinfectant, (iii) presence of predators, such as protozoa and invertebrates, (iv) environmental conditions, such as water temperature, and (v) spatial location of microorganisms (bulk water, sediment, or biofilm). Water treatment and distribution conditions in water mains and premise plumbing affect each of these factors and shape bacterial community characteristics (abundance, composition, viability) in distribution systems. Improved understanding of bacterial interactions in distribution systems and of environmental conditions impact is needed for better control of bacterial communities during drinking water production and distribution. This article reviews (i) existing knowledge on biological stability controlling factors and (ii) how these factors are affected by drinking water production and distribution conditions. In addition, (iii) the concept of biological stability is discussed in light of experience with well-established and new analytical methods, enabling high throughput analysis and in-depth characterization of bacterial communities in drinking water. We discussed, how knowledge gained from novel techniques will improve design and monitoring of water treatment and distribution systems in order to maintain good drinking water microbial quality up to consumer’s tap. A new definition and methodological approach for biological stability is proposed. PMID:26870010

Farm to Table and beyond: Helping Students Make Sense of the Global Food System

ERIC Educational Resources Information Center

Koch, Pamela; Barton, Angela Calabrese; Contento, Isobel; Crabtree, Margo

2008-01-01

It is not enough for students to acquire knowledge about how food is produced and processed; they must also come to understand the biological and environmental contexts in which food production, processing, and transportation take place. Through diagramming, students begin to understand that our food system has a series of interacting parts and…

Introducing the Concept of Biocatalysis in the Classroom: The Conversion of Cholesterol to Provitamin D[subscript 3

ERIC Educational Resources Information Center

De Luca, Belén M.; Nudel, Clara B.; Gonzalez, Rodrigo H.; Nusblat, Alejandro D.

2017-01-01

Biocatalysis is a fundamental concept in biotechnology. The topic integrates knowledge of several disciplines; therefore, it was included in the course "design and optimization of biological systems" which is offered in the biochemistry curricula. We selected the ciliate tetrahymena as an example of a eukaryotic system with potential for…

Relations of Cognitive and Motivational Variables with Students' Human Circulatory System Achievement in Traditional and Learning Cycle Classrooms

ERIC Educational Resources Information Center

Sadi, Özlem; Çakiroglu, Jale

2014-01-01

This study is aimed at investigating the relationships among students' relevant prior knowledge, meaningful learning orientation, reasoning ability, self-efficacy, locus of control, attitudes toward biology and achievement with the human circulatory system (HCS) using the learning cycle (LC) and the traditional classroom setting. The study was…

Student Perceived and Determined Knowledge of Biology Concepts in an Upper-Level Biology Course.

PubMed

Ziegler, Brittany; Montplaisir, Lisa

2014-01-01

Students who lack metacognitive skills can struggle with the learning process. To be effective learners, students should recognize what they know and what they do not know. This study examines the relationship between students' perception of their knowledge and determined knowledge in an upper-level biology course utilizing a pre/posttest approach. Significant differences in students' perception of their knowledge and their determined knowledge exist at the beginning (pretest) and end (posttest) of the course. Alignment between student perception and determined knowledge was significantly more accurate on the posttest compared with the pretest. Students whose determined knowledge was in the upper quartile had significantly better alignment between their perception and determined knowledge on the pre- and posttest than students in the lower quartile. No difference exists between how students perceived their knowledge between upper- and lower-quartile students. There was a significant difference in alignment of perception and determined knowledge between males and females on the posttest, with females being more accurate in their perception of knowledge. This study provides evidence of discrepancies that exist between what students perceive they know and what they actually know. © 2014 B. Ziegler and L. Montplaisir. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A year (2014-2015) of plants in Proteomics journal. Progress in wet and dry methodologies, moving from protein catalogs, and the view of classic plant biochemists.

PubMed

Sanchez-Lucas, Rosa; Mehta, Angela; Valledor, Luis; Cabello-Hurtado, Francisco; Romero-Rodrıguez, M Cristina; Simova-Stoilova, Lyudmila; Demir, Sekvan; Rodriguez-de-Francisco, Luis E; Maldonado-Alconada, Ana M; Jorrin-Prieto, Ana L; Jorrín-Novo, Jesus V

2016-03-01

The present review is an update of the previous one published in Proteomics 2015 Reviews special issue [Jorrin-Novo, J. V. et al., Proteomics 2015, 15, 1089-1112] covering the July 2014-2015 period. It has been written on the bases of the publications that appeared in Proteomics journal during that period and the most relevant ones that have been published in other high-impact journals. Methodological advances and the contribution of the field to the knowledge of plant biology processes and its translation to agroforestry and environmental sectors will be discussed. This review has been organized in four blocks, with a starting general introduction (literature survey) followed by sections focusing on the methodology (in vitro, in vivo, wet, and dry), proteomics integration with other approaches (systems biology and proteogenomics), biological information, and knowledge (cell communication, receptors, and signaling), ending with a brief mention of some other biological and translational topics to which proteomics has made some contribution. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

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

2018-01-01

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

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Biological effects and mechanisms of shortwave radiation: a review.

PubMed

Yu, Chao; Peng, Rui-Yun

2017-01-01

With the increasing knowledge of shortwave radiation, it is widely used in wireless communications, radar observations, industrial manufacturing, and medical treatments. Despite of the benefits from shortwave, these wide applications expose humans to the risk of shortwave electromagnetic radiation, which is alleged to cause potential damage to biological systems. This review focused on the exposure to shortwave electromagnetic radiation, considering in vitro, in vivo and epidemiological results that have provided insight into the biological effects and mechanisms of shortwave. Additionally, some protective measures and suggestions are discussed here in the hope of obtaining more benefits from shortwave with fewer health risks.

Getting to the guts of the matter: the status and potential of 'omics' research of parasitic protists of the human gastrointestinal system.

PubMed

Jex, Aaron R; Koehler, Anson V; Ansell, Brendan R; Baker, Louise; Karunajeewa, Harin; Gasser, Robin B

2013-11-01

Parasitic protists are a major cause of diarrhoeal illnesses in humans globally. Collectively, enteric pathogens exceed all other forms of infectious disease, in terms of their estimated global prevalence and socioeconomic impact. They have a disproportionately high impact on children in impoverished communities, leading to acute (diarrhoea, vomiting, dehydration and death) and chronic disease (malabsorption, malnutrition, physical and cognitive stunting and predisposition to chronic, non-communicable disease) consequences. However, historically, investment in research and disease control measures has been disproportionately poor, leading to their current classification as neglected pathogens. A sound understanding of their biology is essential in underpinning detection, treatment and control efforts. One major tool in rapidly improving our knowledge of these parasites is the use of biological systems, including 'omic' technologies. In recent years, these tools have shown significant success when applied to enteric protists. This review summarises much of this knowledge and highlights the significant remaining knowledge gaps. A major focus of the present review was to provide a perspective on a way forward to address these gaps using advanced biotechnologies. Copyright © 2013 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

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

Young, Eric J.; Burton, Rodney; Mahalik, Jyoti P.

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as “building blocks” for a rangemore » of customized intracellular scaffolds. As a result, we summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering.« less

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

DOE PAGES

Young, Eric J.; Burton, Rodney; Mahalik, Jyoti P.; ...

2017-07-31

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as “building blocks” for a rangemore » of customized intracellular scaffolds. As a result, we summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering.« less

Engineering the Bacterial Microcompartment Domain for Molecular Scaffolding Applications

PubMed Central

Young, Eric J.; Burton, Rodney; Mahalik, Jyoti P.; Sumpter, Bobby G.; Fuentes-Cabrera, Miguel; Kerfeld, Cheryl A.; Ducat, Daniel C.

2017-01-01

As synthetic biology advances the intricacy of engineered biological systems, the importance of spatial organization within the cellular environment must not be marginalized. Increasingly, biological engineers are investigating means to control spatial organization within the cell, mimicking strategies used by natural pathways to increase flux and reduce cross-talk. A modular platform for constructing a diverse set of defined, programmable architectures would greatly assist in improving yields from introduced metabolic pathways and increasing insulation of other heterologous systems. Here, we review recent research on the shell proteins of bacterial microcompartments and discuss their potential application as “building blocks” for a range of customized intracellular scaffolds. We summarize the state of knowledge on the self-assembly of BMC shell proteins and discuss future avenues of research that will be important to realize the potential of BMC shell proteins as predictively assembling and programmable biological materials for bioengineering. PMID:28824573

BioSmalltalk: a pure object system and library for bioinformatics.

PubMed

Morales, Hernán F; Giovambattista, Guillermo

2013-09-15

We have developed BioSmalltalk, a new environment system for pure object-oriented bioinformatics programming. Adaptive end-user programming systems tend to become more important for discovering biological knowledge, as is demonstrated by the emergence of open-source programming toolkits for bioinformatics in the past years. Our software is intended to bridge the gap between bioscientists and rapid software prototyping while preserving the possibility of scaling to whole-system biology applications. BioSmalltalk performs better in terms of execution time and memory usage than Biopython and BioPerl for some classical situations. BioSmalltalk is cross-platform and freely available (MIT license) through the Google Project Hosting at http://code.google.com/p/biosmalltalk hernan.morales@gmail.com Supplementary data are available at Bioinformatics online.

Neuromorphic sensory systems.

PubMed

Liu, Shih-Chii; Delbruck, Tobi

2010-06-01

Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience. We discuss recent progress in realizing neuromorphic sensory systems which mimic the biological retina and cochlea, and subsequent sensor processing. The main trends are the increasing number of sensors and sensory systems that communicate through asynchronous digital signals analogous to neural spikes; the improved performance and usability of these sensors; and novel sensory processing methods which capitalize on the timing of spikes from these sensors. Experiments using these sensors can impact how we think the brain processes sensory information. 2010 Elsevier Ltd. All rights reserved.

Assessment of knowledge of participants on basic molecular biology techniques after 5-day intensive molecular biology training workshops in Nigeria.

PubMed

Yisau, J I; Adagbada, A O; Bamidele, T; Fowora, M; Brai, B I C; Adebesin, O; Bamidele, M; Fesobi, T; Nwaokorie, F O; Ajayi, A; Smith, S I

2017-07-08

The deployment of molecular biology techniques for diagnosis and research in Nigeria is faced with a number of challenges, including the cost of equipment and reagents coupled with the dearth of personnel skilled in the procedures and handling of equipment. Short molecular biology training workshops were conducted at the Nigerian Institute of Medical Research (NIMR), to improve the knowledge and skills of laboratory personnel and academics in health, research, and educational facilities. Five-day molecular biology workshops were conducted annually between 2011 and 2014, with participants drawn from health, research facilities, and the academia. The courses consisted of theoretical and practical sessions. The impact of the workshops on knowledge and skill acquisition was evaluated by pre- and post-tests which consisted of 25 multiple choice and other questions. Sixty-five participants took part in the workshops. The mean knowledge of molecular biology as evaluated by the pre- and post-test assessments were 8.4 (95% CI 7.6-9.1) and 13.0 (95 CI 11.9-14.1), respectively. The mean post-test score was significantly greater than the mean pre-test score (p < 0.0001). The five-day molecular biology workshop significantly increased the knowledge and skills of participants in molecular biology techniques. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):313-317, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

Normal morphogenesis of epithelial tissues and progression of epithelial tumors

PubMed Central

Wang, Chun-Chao; Jamal, Leen; Janes, Kevin A.

2011-01-01

Epithelial cells organize into various tissue architectures that largely maintain their structure throughout the life of an organism. For decades, the morphogenesis of epithelial tissues has fascinated scientists at the interface of cell, developmental, and molecular biology. Systems biology offers ways to combine knowledge from these disciplines by building integrative models that are quantitative and predictive. Can such models be useful for gaining a deeper understanding of epithelial morphogenesis? Here, we take inventory of some recurring themes in epithelial morphogenesis that systems approaches could strive to capture. Predictive understanding of morphogenesis at the systems level would prove especially valuable for diseases such as cancer, where epithelial tissue architecture is profoundly disrupted. PMID:21898857

Computational Tools for Stem Cell Biology

PubMed Central

Bian, Qin; Cahan, Patrick

2016-01-01

For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the last several years, a new sub-discipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single-cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate. PMID:27318512

The 1990-1991 NASA space biology accomplishments

NASA Technical Reports Server (NTRS)

Halstead, Thora W. (Editor)

1993-01-01

This report consists of individual technical summaries of research projects of NASA's Space Biology Program, for research conducted during the period May 1990 through May 1991. This program includes both plant and animal research, and is dedicated to understanding the role of gravity and other environmental factors on biological systems and to using the microgravity of the space environment as a tool to advance fundamental scientific knowledge in the biological sciences to improve the quality of life on Earth and contribute to NASA's goal of manned exploration of space. The summaries for each project include a description of the research, a list of the accomplishments, an explanation of the significance of the accomplishments, and a list of publications.

Computational Tools for Stem Cell Biology.

PubMed

Bian, Qin; Cahan, Patrick

2016-12-01

For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the past several years, a new subdiscipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

EPA Science Inventory

With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...

Literature Mining and Knowledge Discovery Tools for Virtual Tissues

EPA Science Inventory

Virtual Tissues (VTs) are in silico models that simulate the cellular fabric of tissues to analyze complex relationships and predict multicellular behaviors in specific biological systems such as the mature liver (v-Liver™) or developing embryo (v-Embryo™). VT models require inpu...

Preservice Biology Teachers' Professional Knowledge: Structure and Learning Opportunities

ERIC Educational Resources Information Center

Großschedl, Jörg; Harms, Ute; Kleickmann, Thilo; Glowinski, Ingrid

2015-01-01

What learning opportunities in higher education promote the development of content knowledge (CK), pedagogical content knowledge (PCK), and pedagogical knowledge (PK)? In order to investigate this question, a cross-sectional study with a total of 274 German preservice biology teachers (21.5% male, average age 22.8 years) was conducted in German…

Primary School Student Teachers' Perceived and Actual Knowledge in Biology

ERIC Educational Resources Information Center

Eija, Yli-Panula; Eila, Jeronen; Pongsakdi, Nonmanut

2017-01-01

Individuals' perceptions of their knowledge can have an important role in shaping their cognition and influencing their behaviour. However, there has been a scarcity of studies in biology on how perceived knowledge relates to actual knowledge. The focus of this article is on quantitative results analysing and interpreting student teachers'…

High School Biology Students' Knowledge and Certainty about Diffusion and Osmosis Concepts

ERIC Educational Resources Information Center

Odom, Arthur L.; Barrow, Lloyd H.

2007-01-01

The purpose of this study was to investigate students' understanding about scientifically acceptable content knowledge by exploring the relationship between knowledge of diffusion and osmosis and the students' certainty in their content knowledge. Data was collected from a high school biology class with the Diffusion and Osmosis Diagnostic Test…

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Introduction to biological complexity as a missing link in drug discovery.

PubMed

Gintant, Gary A; George, Christopher H

2018-06-06

Despite a burgeoning knowledge of the intricacies and mechanisms responsible for human disease, technological advances in medicinal chemistry, and more efficient assays used for drug screening, it remains difficult to discover novel and effective pharmacologic therapies. Areas covered: By reference to the primary literature and concepts emerging from academic and industrial drug screening landscapes, the authors propose that this disconnect arises from the inability to scale and integrate responses from simpler model systems to outcomes from more complex and human-based biological systems. Expert opinion: Further collaborative efforts combining target-based and phenotypic-based screening along with systems-based pharmacology and informatics will be necessary to harness the technological breakthroughs of today to derive the novel drug candidates of tomorrow. New questions must be asked of enabling technologies-while recognizing inherent limitations-in a way that moves drug development forward. Attempts to integrate mechanistic and observational information acquired across multiple scales frequently expose the gap between our knowledge and our understanding as the level of complexity increases. We hope that the thoughts and actionable items highlighted will help to inform the directed evolution of the drug discovery process.

User-centered evaluation of Arizona BioPathway: an information extraction, integration, and visualization system.

PubMed

Quiñones, Karin D; Su, Hua; Marshall, Byron; Eggers, Shauna; Chen, Hsinchun

2007-09-01

Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This paper presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature-viewing method. Relation aggregation significantly contributes to knowledge-acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multiview, relation-based interface that supports user-controlled exploration of pathway information across multiple granularities.

Fundamentals of pulmonary drug delivery.

PubMed

Groneberg, D A; Witt, C; Wagner, U; Chung, K F; Fischer, A

2003-04-01

Aerosol administration of peptide-based drugs plays an important role in the treatment of pulmonary and systemic diseases and the unique cellular properties of airway epithelium offers a great potential to deliver new compounds. As the relative contributions from the large airways to the alveolar space are important to the local and systemic availability, the sites and mechanism of uptake and transport of different target compounds have to be characterized. Among the different respiratory cells, the ciliated epithelial cells of the larger and smaller airways and the type I and type II pneumocytes are the key players in pulmonary drug transport. With their diverse cellular characteristics, each of these cell types displays a unique uptake possibility. Next to the knowledge of these cellular aspects, the nature of aerosolized drugs, characteristics of delivery systems and the depositional and pulmonary clearance mechanisms display major targets to optimize pulmonary drug delivery. Based on the growing knowledge on pulmonary cell biology and pathophysiology due to modern methods of molecular biology, the future characterization of pulmonary drug transport pathways can lead to new strategies in aerosol drug therapy.

Radiobiology of systemic radiation therapy.

PubMed

Murray, David; McEwan, Alexander J

2007-02-01

Although systemic radionuclide therapy (SRT) is effective as a palliative therapy in patients with metastatic cancer, there has been limited success in expanding patterns of utilization and in bringing novel systemic radiotherapeutic agents to routine clinical use. Although there are many factors that contribute to this situation, we hypothesize that a better understanding of the radiobiology and mechanism of action of SRT will facilitate the development of future compounds and the future designs of prospective clinical trials. If these trials can be rationalized to the biological basis of the therapy, it is likely that the long-term outcome would be enhanced therapeutic efficacy. In this review, we provide perspectives of the current state of low-dose-rate (LDR) radiation research and offer linkages where appropriate with current clinical knowledge. These include the recently described phenomena of low-dose hyper-radiosensitivity-increased radioresistance (LDH-IRR), adaptive responses, and biological bystander effects. Each of these areas require a major reconsideration of existing models for radiation action and an understanding of how this knowledge will integrate into the evolution of clinical SRT practice. Validation of a role in vivo for both LDH-IRR and biological bystander effects in SRT would greatly impact the way we would assess therapeutic response to SRT, the design of clinical trials of novel SRT radiopharmaceuticals, and risk estimates for both therapeutic and diagnostic radiopharmaceuticals. We believe that the current state of research in LDR effects offers a major opportunity to the nuclear medicine community to address the basic science of clinical SRT practice, to use this new knowledge to expand the use and roles of SRT, and to facilitate the introduction of new therapeutic radiopharmaceuticals.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

The acquisition of biological knowledge during childhood: Cognitive conflict or tabula rasa?

NASA Astrophysics Data System (ADS)

Lawson, Anton E.

Clinical interviews were conducted with three elementary school children, who varied in age but not in family or school environment, to determine the extent to which they held naive misconceptions about important biological topics and to determine agewise trends in the development of biological knowledge. Does early biological knowledge acquisition follow a pattern of spontaneous naive theory construction and cognitive conflict or does it follow a pattern of gradual accretion to an initially blank slate? Contrary to findings in the physical sciences, little evidence was found for biological misconceptions as knowledge acquisition appeared to more directly follow the gradual accretion hypothesis with the primary source of that knowledge adult authority rather than personal experience. However, conceptual change teaching is still advocated due to its ability to provoke students to consider and test alternative conceptions (even if they are not their own) as a means of encouraging the development of important general reasoning patterns utilized in the testing of causal hypotheses.

Developmental therapeutics for patients with breast cancer and central nervous system metastasis: current landscape and future perspectives.

PubMed

Costa, R; Carneiro, B A; Wainwright, D A; Santa-Maria, C A; Kumthekar, P; Chae, Y K; Gradishar, W J; Cristofanilli, M; Giles, F J

2017-01-01

Breast cancer is the second-leading cause of metastatic disease in the central nervous system (CNS). Recent advances in the biological understanding of breast cancer have facilitated an unprecedented increase of survival in a subset of patients presenting with metastatic breast cancer. Patients with HER2 positive (HER2+) or triple negative breast cancer are at highest risk of developing CNS metastasis, and typically experience a poor prognosis despite treatment with local and systemic therapies. Among the obstacles ahead in the realm of developmental therapeutics for breast cancer CNS metastasis is the improvement of our knowledge on its biological nuances and on the interaction of the blood–brain barrier with new compounds. This article reviews recent discoveries related to the underlying biology of breast cancer brain metastases, clinical progress to date and suggests rational approaches for investigational therapies.

Leukemia inhibitory factor: part of a large ingathering family.

PubMed

Taupin, J L; Pitard, V; Dechanet, J; Miossec, V; Gualde, N; Moreau, J F

1998-01-01

Leukemia Inhibitory Factor (LIF) has a wide variety of biological activities. It regulates the differentiation of embryonic stem cells, neural cells, osteoblasts, adipocytes, hepatocytes and kidney epithelial cells. It also triggers the proliferation of myoblasts, primordial germ cells and some endothelial cells. Many of these biological functions parallel those of interleukin-6, Oncostatin M, ciliary neurotrophic factor, interleukin-11 and cardiotrophin-1. These structurally related cytokines also share subunits of their receptors which could partially explain the redundancy in this system of soluble mediators. In vivo LIF proves important in regulating the inflammatory response by fine tuning of the delicate balance of at least four systems in the body, namely the immune, the hematopoietic, the nervous and the endocrine systems. Although we are far from its therapeutic applications, the fast increasing knowledge in this field may bring new insights for the understanding of the cytokine biology in general.

Does the transition to an active-learning environment for the introductory course reduce students' overall knowledge of the various disciplines in biology?

PubMed

Simurda, Maryanne C

2012-01-01

As biology education is being redesigned toward an interdisciplinary focus and as pedagogical trends move toward active-learning strategies and investigative experiences, a restructuring of the course content for the Introductory Biology course is necessary. The introductory course in biology has typically been a survey of all the biosciences. If the total number of topics covered is reduced, is the students' overall knowledge of biology also reduced? Our introductory course has been substantially modified away from surveying the biological sciences and toward providing a deep understanding of a particular biological topic, as well as focusing on developing students' analytical and communication skills. Because of this shift to a topic-driven approach for the introductory course, we were interested in assessing our graduating students' overall knowledge of the various biological disciplines. Using the Major Field Test - Biology (Educational Testing Service (ETS), Princeton, NJ), we compared the test performance of graduating students who had a traditional lecture-based introductory course to those who had a topic-driven active-learning introductory course. Our results suggest that eliminating the traditional survey of biology and, instead, focusing on quantitative and writing skills at the introductory level do not affect our graduating students' overall breadth of knowledge of the various biosciences.

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

Anaerobic soil disinfestation for soil borne disease control in strawberry and vegetable systems: Current knowledge and future directions

USDA-ARS?s Scientific Manuscript database

Anaerobic soil disinfestation (ASD), a biological alternative to soil fumigation, has been shown to control a wide range of soil-borne pathogens and nematodes in numerous crop production systems across Japan, the Netherlands and the U.S. A brief review of the status of the science behind ASD and its...

Information processing in bacteria: memory, computation, and statistical physics: a key issues review

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network—the main players (nodes) and their interactions (links)—in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review.

PubMed

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Prevention of Preharvest Sprouting through Hormone Engineering and Germination Recovery by Chemical Biology.

PubMed

Nonogaki, Mariko; Nonogaki, Hiroyuki

2017-01-01

Vivipary, germination of seeds on the maternal plant, is observed in nature and provides ecological advantages in certain wild species, such as mangroves. However, precocious seed germination in agricultural species, such as preharvest sprouting (PHS) in cereals, is a serious issue for food security. PHS reduces grain quality and causes economical losses to farmers. PHS can be prevented by translating the basic knowledge of hormone biology in seeds into technologies. Biosynthesis of abscisic acid (ABA), which is an essential hormone for seed dormancy, can be engineered to enhance dormancy and prevent PHS. Enhancing nine- cis -epoxycarotenoid dioxygenase (NCED), a rate-limiting enzyme of ABA biosynthesis, through a chemically induced gene expression system, has successfully been used to suppress germination of Arabidopsis seeds. The more advanced system NCED positive-feedback system, which amplifies ABA biosynthesis in a seed-specific manner without chemical induction, has also been developed. The proofs of concept established in the model species are now ready to be applied to crops. A potential problem is recovery of germination from hyperdormant crop grains. Hyperdormancy induced by the NCED systems can be reversed by inducing counteracting genes, such as NCED RNA interference or gibberellin (GA) biosynthesis genes. Alternatively, seed sensitivity to ABA can be modified to rescue germination using the knowledge of chemical biology. ABA antagonists, which were developed recently, have great potential to recover germination from the hyperdormant seeds. Combination of the dormancy-imposing and -releasing approaches will establish a comprehensive technology for PHS prevention and germination recovery.

Modeling limb-bud dysmorphogenesis in a predictive virtual embryo model

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational methods that integrate knowledge of biological systems and in vivo toxicities (www.epa.gov/ncct/toxcast/). Many ToxCast assays assess signaling pathways and c...

How Can We Use Bioinformatics to Predict Which Agents Will Cause Birth Defects?

EPA Science Inventory

The availability of genomic sequences from a growing number of human and model organisms has provided an explosion of data, information, and knowledge regarding biological systems and disease processes. High-throughput technologies such as DNA and protein microarray biochips are ...

Ground-based research with heavy ions for space radiation protection

NASA Astrophysics Data System (ADS)

Durante, M.; Kronenberg, A.

Human exposure to ionizing radiation is one of the acknowledged potential showstoppers for long duration manned interplanetary missions. Human exploratory missions cannot be safely performed without a substantial reduction of the uncertainties associated with different space radiation health risks, and the development of effective countermeasures. Most of our knowledge of the biological effects of heavy charged particles comes from accelerator-based experiments. During the 35th COSPAR meeting, recent ground-based experiments with high-energy iron ions were discussed, and these results are briefly summarised in this paper. High-quality accelerator-based research with heavy ions will continue to be the main source of knowledge of space radiation health effects and will lead to reductions of the uncertainties in predictions of human health risks. Efforts in materials science, nutrition and pharmaceutical sciences and their rigorous evaluation with biological model systems in ground-based accelerator experiments will lead to the development of safe and effective countermeasures to permit human exploration of the Solar System.

IntegromeDB: an integrated system and biological search engine

PubMed Central

2012-01-01

Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback. PMID:22260095

The 1992-1993 NASA Space Biology Accomplishments

NASA Technical Reports Server (NTRS)

Halstead, Thora W. (Editor)

1994-01-01

This report consists of individual technical summaries of research projects of NASA's Space Biology Program, for research conducted during the calendar years of 1992 and 1993. This program includes both plant and animal research, and is dedicated to understanding the role of gravity and the effects of microgravity on biological processes; determining the effects of the interaction of gravity and other environmental factors on biological systems; and using the microgravity of the space environment as a tool to advance fundamental scientific knowledge in the biological sciences to improve the quality of life on Earth and contribute to NASA's goal of manned exploration of space. The summaries for each project include a description of the research, a list of the accomplishments, an explanation of the significance of the accomplishments, and a list of publications.

ISYMOD: a knowledge warehouse for the identification, assembly and analysis of bacterial integrated systems.

PubMed

Chabalier, Julie; Capponi, Cécile; Quentin, Yves; Fichant, Gwennaele

2005-04-01

Complex biological functions emerge from interactions between proteins in stable supra-molecular assemblies and/or through transitory contacts. Most of the time protein partners of the assemblies are composed of one or several domains which exhibit different biochemical functions. Thus the study of cellular process requires the identification of different functional units and their integration in an interaction network; such complexes are referred to as integrated systems. In order to exploit with optimum efficiency the increased release of data, automated bioinformatics strategies are needed to identify, reconstruct and model such systems. For that purpose, we have developed a knowledge warehouse dedicated to the representation and acquisition of bacterial integrated systems involved in the exchange of the bacterial cell with its environment. ISYMOD is a knowledge warehouse that consistently integrates in the same environment the data and the methods used for their acquisition. This is achieved through the construction of (1) a domain knowledge base (DKB) devoted to the storage of the knowledge about the systems, their functional specificities, their partners and how they are related and (2) a methodological knowledge base (MKB) which depicts the task layout used to identify and reconstruct functional integrated systems. Instantiation of the DKB is obtained by solving the tasks of the MKB, whereas some tasks need instances of the DKB to be solved. AROM, an object-based knowledge representation system, has been used to design the DKB, and its task manager, AROMTasks, for developing the MKB. In this study two integrated systems, ABC transporters and two component systems, both involved in adaptation processes of a bacterial cell to its biotope, have been used to evaluate the feasibility of the approach.

Panel 3: Recent advances in anatomy, pathology, and cell biology in relation to otitis media pathogenesis.

PubMed

Cayé-Thomasen, Per; Hermansson, Ann; Bakaletz, Lauren; Hellstrøm, Sten; Kanzaki, Sho; Kerschner, Joseph; Lim, David; Lin, Jizhen; Mason, Kevin; Spratley, Jorge

2013-04-01

The pathogenesis of otitis media (OM) involves a number of factors related to the anatomy, pathology, and cell biology of the middle ear, the mastoid, the Eustachian tube, and the nasopharynx. Although some issues of pathogenesis are fairly well established, others are only marginally indicated by current knowledge, and yet others remain undisclosed. The objective of this article is to provide a state-of-the-art review on recent scientific achievements in the pathogenesis of OM, as related to anatomy, pathology, and cell biology. PubMed, Ovid Medline, and Cochrane Library. Articles published on the pathogenesis of OM and the anatomy, pathology, and cell biology of the middle ear, the mastoid, the Eustachian tube, and the nasopharynx between January 2007 and June 2011 were identified. Among almost 1900 abstracts, the authors selected 130 articles for full article review and inclusion in this report. New knowledge on a number of issues emerged, including cell-specific expression and function of fluid transportation and innate immune system molecules, mucous cell metaplasia, mucin expression, bacterial adherence, and epithelial internalization, as well as the occurrence, composition, dynamics, and potential role of bacterial biofilm. In addition, the potential role of gastroesophageal reflux disease and cigarette smoke exposure has been explored further. Over the past 4 years, considerable scientific progress has been made on the pathogenesis of OM, as related to issues of anatomy, pathology, and cell biology. Based on these new achievements and a sustained lack of essential knowledge, suggestions for future research are outlined.

Phylogenics & Tree-Thinking

ERIC Educational Resources Information Center

Baum, David A.; Offner, Susan

2008-01-01

Phylogenetic trees, which are depictions of the inferred evolutionary relationships among a set of species, now permeate almost all branches of biology and are appearing in increasing numbers in biology textbooks. While few state standards explicitly require knowledge of phylogenetics, most require some knowledge of evolutionary biology, and many…

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

AIDS Knowledge: The Media and the Biology Teacher.

ERIC Educational Resources Information Center

Vener, Arthur M.; Krupka, Lawrence R.

1988-01-01

Reports on a study to determine the level of knowledge college students possessed about Acquired Immune Deficiency Syndrome. Concluded that overall enhancement of knowledge occurred among young adults and that mass media was partially responsible. Lists biological terms necessary for understanding the disease. (RT)

Physical Complexity and Cognitive Evolution

NASA Astrophysics Data System (ADS)

Jedlicka, Peter

Our intuition tells us that there is a general trend in the evolution of nature, a trend towards greater complexity. However, there are several definitions of complexity and hence it is difficult to argue for or against the validity of this intuition. Christoph Adami has recently introduced a novel measure called physical complexity that assigns low complexity to both ordered and random systems and high complexity to those in between. Physical complexity measures the amount of information that an organism stores in its genome about the environment in which it evolves. The theory of physical complexity predicts that evolution increases the amount of `knowledge' an organism accumulates about its niche. It might be fruitful to generalize Adami's concept of complexity to the entire evolution (including the evolution of man). Physical complexity fits nicely into the philosophical framework of cognitive biology which considers biological evolution as a progressing process of accumulation of knowledge (as a gradual increase of epistemic complexity). According to this paradigm, evolution is a cognitive `ratchet' that pushes the organisms unidirectionally towards higher complexity. Dynamic environment continually creates problems to be solved. To survive in the environment means to solve the problem, and the solution is an embodied knowledge. Cognitive biology (as well as the theory of physical complexity) uses the concepts of information and entropy and views the evolution from both the information-theoretical and thermodynamical perspective. Concerning humans as conscious beings, it seems necessary to postulate an emergence of a new kind of knowledge - a self-aware and self-referential knowledge. Appearence of selfreflection in evolution indicates that the human brain reached a new qualitative level in the epistemic complexity.

Investigation of type-I interferon dysregulation by arenaviruses : a multidisciplinary approach.

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

Kozina, Carol L.; Moorman, Matthew Wallace; Branda, Catherine

2011-09-01

This report provides a detailed overview of the work performed for project number 130781, 'A Systems Biology Approach to Understanding Viral Hemorrhagic Fever Pathogenesis.' We report progress in five key areas: single cell isolation devices and control systems, fluorescent cytokine and transcription factor reporters, on-chip viral infection assays, molecular virology analysis of Arenavirus nucleoprotein structure-function, and development of computational tools to predict virus-host protein interactions. Although a great deal of work remains from that begun here, we have developed several novel single cell analysis tools and knowledge of Arenavirus biology that will facilitate and inform future publications and funding proposals.

Genetic heterogeneity in autism: From single gene to a pathway perspective.

PubMed

An, Joon Yong; Claudianos, Charles

2016-09-01

The extreme genetic heterogeneity of autism spectrum disorder (ASD) represents a major challenge. Recent advances in genetic screening and systems biology approaches have extended our knowledge of the genetic etiology of ASD. In this review, we discuss the paradigm shift from a single gene causation model to pathway perturbation model as a guide to better understand the pathophysiology of ASD. We discuss recent genetic findings obtained through next-generation sequencing (NGS) and examine various integrative analyses using systems biology and complex networks approaches that identify convergent patterns of genetic elements associated with ASD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Towards the engineering of in vitro systems.

PubMed

Hold, Christoph; Panke, Sven

2009-08-06

Synthetic biology aims at rationally implementing biological systems from scratch. Given the complexity of living systems and our current lack of understanding of many aspects of living cells, this is a major undertaking. The design of in vitro systems can be considerably easier, because they can consist of fewer constituents, are quasi time invariant, their parameter space can be better accessed and they can be much more easily perturbed and then analysed chemically and mathematically. However, even for simplified in vitro systems, following a comprehensively rational design procedure is still difficult. When looking at a comparatively simple system, such as a medium-sized enzymatic reaction network as it is represented by glycolysis, major issues such as a lack of comprehensive enzyme kinetics and of suitable knowledge on crucial design parameters remain. Nevertheless, in vitro systems are very suitable to overcome these obstacles and therefore well placed to act as a stepping stone to engineering living systems.

On the debate about teleology in biology: the notion of "teleological obstacle".

PubMed

Ribeiro, Manuel Gustavo Leitão; Larentis, Ariane Leites; Caldas, Lúcio Ayres; Garcia, Tomás Coelho; Terra, Letícia Labati; Herbst, Marcelo Hawrylak; Almeida, Rodrigo Volcan

2015-12-01

Among the epistemological obstacles described by Gaston Bachelard, we contend that unitary and pragmatic knowledge is correlated to the teleological categories of Ernst Mayr and is the basis for prevailing debate on the notion of "function" in biology. Given the proximity of the aspects highlighted by these authors, we propose to associate the role of teleological thinking in biology and the notion of unitary and pragmatic knowledge as an obstacle to scientific knowledge. Thus, teleological thinking persists acting as an epistemological obstacle in biology, according to Bachelardian terminology. Our investigation led us to formulate the "teleological obstacle," which we consider important for the future of biology and possibly other sciences.

Building confidence: an exploration of nurses undertaking a postgraduate biological science course.

PubMed

Van Wissen, Kim; McBride-Henry, Karen

2010-01-01

This study aimed to explore the impact of studying biological science at a postgraduate level and how this impacted on nursing practice. The term biological sciences in this research encompasses elements of physiology, genetics, biochemistry and pathophysiology. A qualitative research study was designed, that involved the dissemination of a pre- and post-course semi-structured questionnaire for a biological science course, as part of a Master of Nursing programme at a New Zealand University, thus exploring the impact of undertaking a postgraduate biological sciences course. The responses were analysed into themes, based on interpretive concepts. The primary themes revealed improvement in confidence as: confidence in communication, confidence in linking nursing theoretical knowledge to practice and confidence in clinical nursing knowledge. This study highlights the need to privilege clinically-derived nursing knowledge, and that confidence in this nursing knowledge and clinical practice can be instilled through employing the model of theory-guided practice.

[Physicians' knowledge in Israel on the biology and control of head lice].

PubMed

Mumcuoglu, Kosta Y; Mumcuoglu, Michael; Danilevich, Maria; Gilead, Leon

2008-10-01

Health providers such as physicians, nurses and pharmacists should be knowledgeable about the biology of head lice and the ways to control them effectively, in order to reduce the proportion of children infested with head lice. To evaluate the knowledge of physicians in Israel on the biology and epidemiology of lice, as well as their experience with infested individuals and their preferences for diagnosis, prophylaxis and control. An anonymous questionnaire with 37 questions was used. The first 20 questions addressed the general knowledge of physicians on lice biology and control, while the remaining 17 questions were related to their personal experience with lice and louse treatment. Out of 273 physicians interviewed 66.8% had good knowledge of lice, while the remaining 33.2% had some knowledge on lice. The difference between the groups of physicians with medium and good knowledge on lice was borderline significant (P=0.0722), with the dermatologists borderline significantly less knowledgeable than the rest (P=0.0765). Significant differences were found between those physicians with 4-6 or 11-20 years of professional experience and the remaining groups (twice P<0.001). Although the percentage of female physicians who had a good knowledge on louse biology and control was higher than male physicians (39.4% and 29.4%, respectively), the differences were borderline significant (P=0.09). Pediatricians and dermatologists examined significantly more children than family physicians and general practitioners (P <0.001). The results of this study suggest that healthcare professionals' knowledge is of paramount importance for the correct diagnosis and control of head louse infestations.

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Maze learning by a hybrid brain-computer system

NASA Astrophysics Data System (ADS)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system.

PubMed

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system

PubMed Central

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-01-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation. PMID:27619326

Systems Biology for Organotypic Cell Cultures

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

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

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

Workshop Report: Systems Biology for Organotypic Cell Cultures

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

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

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

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE PAGES

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

2016-11-14

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

Systems biology for organotypic cell cultures.

PubMed

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

2017-01-01

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

[Knowledge and power at a molecular level; biological psychiatry in a social context].

PubMed

Verhoeff, B

2009-01-01

How do we acquire our knowledge about psychiatric disorders and how did the current biologically way of thinking in psychiatry originate? With the help of the philosophy of Michel Foucault and Nikolas Rose this essay describes the conditions that made possible today's biological approach in psychiatry. It will become clear that research in the life sciences and the psychiatric knowledge arising from this research are shaped and formed in a complex network of social, economic, political and scientific forces. The biological approach to psychiatric disorders is the product of present-day relationships between scientific developments and commercial corporations.

Influence of Content Knowledge on Pedagogical Content Knowledge: The Case of Teaching Photosynthesis and Plant Growth

ERIC Educational Resources Information Center

Kapyla, Markku; Heikkinen, Jussi-Pekka; Asunta, Tuula

2009-01-01

The aim of the research was to investigate the effect of the amount and quality of content knowledge on pedagogical content knowledge (PCK). The biological content photosynthesis and plant growth was used as an example. The research sample consisted of 10 primary and 10 secondary (biology) teacher students. Questionnaires, lesson preparation task…

Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

NASA Astrophysics Data System (ADS)

Ewing, Tracy S.

The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

Biological organization of the extraocular muscles.

PubMed

Spencer, Robert F; Porter, John D

2006-01-01

Extraocular muscle is fundamentally distinct from other skeletal muscles. Here, we review the biological organization of the extraocular muscles with the intent of understanding this novel muscle group in the context of oculomotor system function. The specific objectives of this review are threefold. The first objective is to understand the anatomic arrangement of the extraocular muscles and their compartmental or layered organization in the context of a new concept of orbital mechanics, the active pulley hypothesis. The second objective is to present an integrated view of the morphologic, cellular, and molecular differences between extraocular and the more traditional skeletal muscles. The third objective is to relate recent data from functional and molecular biology studies to the established extraocular muscle fiber types. Developmental mechanisms that may be responsible for the divergence of the eye muscles from a skeletal muscle prototype also are considered. Taken together, a multidisciplinary understanding of extraocular muscle biology in health and disease provides insights into oculomotor system function and malfunction. Moreover, because the eye muscles are selectively involved or spared in a variety of neuromuscular diseases, knowledge of their biology may improve current pathogenic models of and treatments for devastating systemic diseases.

Genomics and metabolomics of post-weaning return to estrus

USDA-ARS?s Scientific Manuscript database

The weaning-to-estrus interval is a multifaceted trait that has the potential to substantially improve production efficiency in today's global swine industry, if variation in this measure can be reduced. Systems-biology approaches should help close the knowledge gap and increase selection tools and ...

EPA’s Children’s Environmental Health Roadmap: applying the 21st century vision to prenatal development (Teratology)

EPA Science Inventory

Understanding the complex relationships between environmental exposures and early life susceptibility in assessing the risk for adverse pregnancy outcomes requires advanced knowledge of biological systems. This broad research is one of several drivers for the Children’s Environme...

Synthetic biology projects in vitro.

PubMed

Forster, Anthony C; Church, George M

2007-01-01

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

Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...

Energy: Options and Issues.

ERIC Educational Resources Information Center

Walker, Harry O.

This book is intended to provide basic information about energy. The first three chapters describe energy supply and demand, uses and sources, and common energy terms. The next two chapters explain environmental and biological effects of energy systems. Twelve chapters that follow outline past history and technological knowledge of the following…

Embedded Literacy: Knowledge as Meaning

ERIC Educational Resources Information Center

Martin, J. R.

2013-01-01

This paper takes as point of departure the register variable field, and explores its application to the discourse of History and Biology in secondary school classrooms from the perspective of systemic functional linguistics. In particular it considers the functions of technicality and abstraction in these subject specific discourses, and their…

Developing a Passive Time-Activity Triage System In support of Consumer Ingredient Exposure Prioritization.

EPA Science Inventory

Chemical Hazard/toxicity assessment of chemicals relies on droves of chemical-biological data at the organism, tissue, cell, and biomolecular level of resolution. Big data in the context of exposure science relies on a comprehensive knowledge of societies’ and community act...

Developing a Passive Time-Activity Triage System In support of Consumer Ingredient Exposure Prioritization

EPA Science Inventory

Chemical Hazard/toxicity assessment of chemicals relies on droves of chemical-biological data at the organism, tissue, cell, and biomolecular level of resolution. Big data in the context of exposure science relies on a comprehensive knowledge of societies’ and community activity ...

Prior knowledge driven Granger causality analysis on gene regulatory network discovery

DOE PAGES

Yao, Shun; Yoo, Shinjae; Yu, Dantong

2015-08-28

Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

Bioregulatory systems medicine: an innovative approach to integrating the science of molecular networks, inflammation, and systems biology with the patient's autoregulatory capacity?

PubMed Central

Goldman, Alyssa W.; Burmeister, Yvonne; Cesnulevicius, Konstantin; Herbert, Martha; Kane, Mary; Lescheid, David; McCaffrey, Timothy; Schultz, Myron; Seilheimer, Bernd; Smit, Alta; St. Laurent, Georges; Berman, Brian

2015-01-01

Bioregulatory systems medicine (BrSM) is a paradigm that aims to advance current medical practices. The basic scientific and clinical tenets of this approach embrace an interconnected picture of human health, supported largely by recent advances in systems biology and genomics, and focus on the implications of multi-scale interconnectivity for improving therapeutic approaches to disease. This article introduces the formal incorporation of these scientific and clinical elements into a cohesive theoretical model of the BrSM approach. The authors review this integrated body of knowledge and discuss how the emergent conceptual model offers the medical field a new avenue for extending the armamentarium of current treatment and healthcare, with the ultimate goal of improving population health. PMID:26347656

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

The Sex Chromosomes of Frogs: Variability and Tolerance Offer Clues to Genome Evolution and Function

PubMed Central

Malcom, Jacob W.; Kudra, Randal S.; Malone, John H.

2014-01-01

Frog sex chromosomes offer an ideal system for advancing our understanding of genome evolution and function because of the variety of sex determination systems in the group, the diversity of sex chromosome maturation states, the ease of experimental manipulation during early development. After briefly reviewing sex chromosome biology generally, we focus on what is known about frog sex determination, sex chromosome evolution, and recent, genomics-facilitated advances in the field. In closing we highlight gaps in our current knowledge of frog sex chromosomes, and suggest priorities for future research that can advance broad knowledge of gene dose and sex chromosome evolution. PMID:25031658

The relevance of traditional knowledge systems for ethnopharmacological research: theoretical and methodological contributions

PubMed Central

2010-01-01

Background Ethnopharmacology is at the intersection of the medical, natural, and social sciences. Despite its interdisciplinary nature, most ethnopharmacological research has been based on the combination of the chemical, biological, and pharmacological sciences. Far less attention has been given to the social sciences, including anthropology and the study of traditional knowledge systems. Methods I reviewed the literature on traditional knowledge systems highlighting its potential theoretical and methodological contributions to ethnopharmacology. Results I discuss three potential theoretical contributions of traditional knowledge systems to ethnopharmacological research. First, while many plants used in indigenous pharmacopoeias have active compounds, those compounds do not always act alone in indigenous healing systems. Research highlights the holistic nature of traditional knowledge systems and helps understand plant's efficacy in its cultural context. Second, research on traditional knowledge systems can improve our understanding of how ethnopharmacological knowledge is distributed in a society, and who benefits from it. Third, research on traditional knowledge systems can enhance the study of the social relations that enable the generation, maintenance, spread, and devolution of cultural traits and innovations, including ethnopharmacological knowledge. At a methodological level, some ethnopharmacologists have used anthropological tools to understand the context of plant use and local meanings of health and disease. I discuss two more potential methodological contributions of research on traditional knowledge systems to ethnopharmacological research. First, traditional knowledge systems research has developed methods that would help ethnopharmacologists understand how people classify illnesses and remedies, a fundamental aspect of folk medicinal plant selection criteria. Second, ethnopharmacologists could also borrow methods derived from cultural consensus theory to have a broader look at intracultural variation and at the analysis of transmission and loss of traditional ethnopharmacological knowledge. Conclusions Ethical considerations in the ethnopharmacology of the 21st century should go beyond the recognition of the Intellectual Property Rights or the acquisition of research permits, to include considerations on the healthcare of the original holders of ethnopharmacological knowledge. Ethnopharmacology can do more than speed up to recover the traditional knowledge of indigenous peoples to make it available for the development of new drugs. Ethnopharmacologists can work with health care providers in the developing world for the local implementation of ethnopharmacological research results. PMID:21083913

BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

PubMed

Rinaldi, Fabio; Ellendorff, Tilia Renate; Madan, Sumit; Clematide, Simon; van der Lek, Adrian; Mevissen, Theo; Fluck, Juliane

2016-01-01

Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological Expression Language (BEL), as training and test data. BEL is an advanced knowledge representation format which has been designed to be both human readable and machine processable. The specific goal of track 4 was to evaluate text mining systems capable of automatically constructing BEL statements from given evidence text, and of retrieving evidence text for given BEL statements. Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements. We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels. The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text. © The Author(s) 2016. Published by Oxford University Press.

How the study of Listeria monocytogenes has led to new concepts in biology.

PubMed

Rolhion, Nathalie; Cossart, Pascale

2017-06-01

The opportunistic intracellular bacterial pathogen Listeria monocytogenes has in 30 years emerged as an exceptional bacterial model system in infection biology. Research on this bacterium has provided considerable insight into how pathogenic bacteria adapt to mammalian hosts, invade eukaryotic cells, move intracellularly, interfere with host cell functions and disseminate within tissues. It also contributed to unveil features of normal host cell pathways and unsuspected functions of previously known cellular proteins. This review provides an updated overview of our knowledge on this pathogen. In many examples, findings on L. monocytogenes provided the basis for new concepts in bacterial regulation, cell biology and infection processes.

Agent-Based Modeling in Systems Pharmacology.

PubMed

Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

2015-11-01

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

Synthetic and systems biology for microbial production of commodity chemicals.

PubMed

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J; Keasling, Jay D; Martín, Héctor García

2016-01-01

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Synthetic and systems biology for microbial production of commodity chemicals

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

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J.

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges startmore » at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.« less

Synthetic and systems biology for microbial production of commodity chemicals

DOE PAGES

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J.; ...

2016-04-07

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges startmore » at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.« less

Biology. Student Investigations and Readings. Investigations in Natural Science.

ERIC Educational Resources Information Center

Renner, John W.; And Others

Investigations in Natural Science is a program in secondary school biology, chemistry, and physics based upon the description of science as a quest for knowledge, not the knowledge itself. This student manual contains the 18 biology investigations. These investigations focus on concepts related to: organisms; classification; populations;…

Improving the explanation capabilities of advisory systems

NASA Technical Reports Server (NTRS)

Porter, Bruce; Souther, Art

1993-01-01

A major limitation of current advisory systems (e.g., intelligent tutoring systems and expert systems) is their restricted ability to give explanations. The goal of our research is to develop and evaluate a flexible explanation facility, one that can dynamically generate responses to questions not anticipated by the system's designers and that can tailor these responses to individual users. To achieve this flexibility, we are developing a large knowledge base, a viewpoint construction facility, and a modeling facility. In the long term we plan to build and evaluate advisory systems with flexible explanation facilities for scientists in numerous domains. In the short term, we are focusing on a single complex domain in biological science, and we are working toward two important milestones: (1) building and evaluating an advisory system with a flexible explanation facility for freshman-level students studying biology; and (2) developing general methods and tools for building similar explanation facilities in other domains.

Improving the explanation capabilities of advisory systems

NASA Technical Reports Server (NTRS)

Porter, Bruce; Souther, Art

1994-01-01

A major limitation of current advisory systems (e.g., intelligent tutoring systems and expert systems) is their restricted ability to give explanations. The goal of our research is to develop and evaluate a flexible explanation facility, one that can dynamically generate responses to questions not anticipated by the system's designers and that can tailor these responses to individual users. To achieve this flexibility, we are developing a large knowledge base, a viewpoint construction facility, and a modeling facility. In the long term we plan to build and evaluate advisory systems with flexible explanation facilities for scientists in numerous domains. In the short term, we are focusing on a single complex domain in biological science, and we are working toward two important milestones: (1) building and evaluating an advisory system with a flexible explanation facility for freshman-level students studying biology, and (2) developing general methods and tools for building similar explanation facilities in other domains.

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Harrison, P. A.; Harrison, P. R.

1992-01-01

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Tools for knowledge acquisition within the NeuroScholar system and their application to anatomical tract-tracing data

PubMed Central

Burns, Gully APC; Cheng, Wei-Cheng

2006-01-01

Background Knowledge bases that summarize the published literature provide useful online references for specific areas of systems-level biology that are not otherwise supported by large-scale databases. In the field of neuroanatomy, groups of small focused teams have constructed medium size knowledge bases to summarize the literature describing tract-tracing experiments in several species. Despite years of collation and curation, these databases only provide partial coverage of the available published literature. Given that the scientists reading these papers must all generate the interpretations that would normally be entered into such a system, we attempt here to provide general-purpose annotation tools to make it easy for members of the community to contribute to the task of data collation. Results In this paper, we describe an open-source, freely available knowledge management system called 'NeuroScholar' that allows straightforward structured markup of the PDF files according to a well-designed schema to capture the essential details of this class of experiment. Although, the example worked through in this paper is quite specific to neuroanatomical connectivity, the design is freely extensible and could conceivably be used to construct local knowledge bases for other experiment types. Knowledge representations of the experiment are also directly linked to the contributing textual fragments from the original research article. Through the use of this system, not only could members of the community contribute to the collation task, but input data can be gathered for automated approaches to permit knowledge acquisition through the use of Natural Language Processing (NLP). Conclusion We present a functional, working tool to permit users to populate knowledge bases for neuroanatomical connectivity data from the literature through the use of structured questionnaires. This system is open-source, fully functional and available for download from [1]. PMID:16895608

The Innate and Adaptive Immune System as Targets for Biologic Therapies in Inflammatory Bowel Disease.

PubMed

Holleran, Grainne; Lopetuso, Loris; Petito, Valentina; Graziani, Cristina; Ianiro, Gianluca; McNamara, Deirdre; Gasbarrini, Antonio; Scaldaferri, Franco

2017-09-21

Inflammatory bowel disease (IBD) is an immune-mediated inflammatory condition causing inflammation of gastrointestinal and systemic cells, with an increasing prevalence worldwide. Many factors are known to trigger and maintain inflammation in IBD including the innate and adaptive immune systems, genetics, the gastrointestinal microbiome and several environmental factors. Our knowledge of the involvement of the immune system in the pathophysiology of IBD has advanced rapidly over the last two decades, leading to the development of several immune-targeted treatments with a biological source, known as biologic agents. The initial focus of these agents was directed against the pro-inflammatory cytokine tumor necrosis factor-α (TNF-α) leading to dramatic changes in the disease course for a proportion of patients with IBD. However, more recently, it has been shown that a significant proportion of patients do not respond to anti-TNF-α directed therapies, leading a shift to other inflammatory pathways and targets, including those of both the innate and adaptive immune systems, and targets linking both systems including anti-leukocyte trafficking agents-integrins and adhesion molecules. This review briefly describes the molecular basis of immune based gastrointestinal inflammation in IBD, and then describes how several current and future biologic agents work to manipulate these pathways, and their clinical success to date.

The Innate and Adaptive Immune System as Targets for Biologic Therapies in Inflammatory Bowel Disease

PubMed Central

Holleran, Grainne; Lopetuso, Loris; Petito, Valentina; Graziani, Cristina; Ianiro, Gianluca; McNamara, Deirdre; Gasbarrini, Antonio; Scaldaferri, Franco

2017-01-01

Inflammatory bowel disease (IBD) is an immune-mediated inflammatory condition causing inflammation of gastrointestinal and systemic cells, with an increasing prevalence worldwide. Many factors are known to trigger and maintain inflammation in IBD including the innate and adaptive immune systems, genetics, the gastrointestinal microbiome and several environmental factors. Our knowledge of the involvement of the immune system in the pathophysiology of IBD has advanced rapidly over the last two decades, leading to the development of several immune-targeted treatments with a biological source, known as biologic agents. The initial focus of these agents was directed against the pro-inflammatory cytokine tumor necrosis factor-α (TNF-α) leading to dramatic changes in the disease course for a proportion of patients with IBD. However, more recently, it has been shown that a significant proportion of patients do not respond to anti-TNF-α directed therapies, leading a shift to other inflammatory pathways and targets, including those of both the innate and adaptive immune systems, and targets linking both systems including anti-leukocyte trafficking agents-integrins and adhesion molecules. This review briefly describes the molecular basis of immune based gastrointestinal inflammation in IBD, and then describes how several current and future biologic agents work to manipulate these pathways, and their clinical success to date. PMID:28934123

Preservice Biology Teachers' Conceptions about the Tentative Nature of Theories and Models in Biology

ERIC Educational Resources Information Center

Reinisch, Bianca; Krüger, Dirk

2018-01-01

In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers (N = 10) were asked about their understanding of theories…

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

PubMed

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

Epigenomics and the concept of degeneracy in biological systems

PubMed Central

Mason, Paul H.; Barron, Andrew B.

2014-01-01

Researchers in the field of epigenomics are developing more nuanced understandings of biological complexity, and exploring the multiple pathways that lead to phenotypic expression. The concept of degeneracy—referring to the multiple pathways that a system recruits to achieve functional plasticity—is an important conceptual accompaniment to the growing body of knowledge in epigenomics. Distinct from degradation, redundancy and dilapidation; degeneracy refers to the plasticity of traits whose function overlaps in some environments, but diverges in others. While a redundant system is composed of repeated identical elements performing the same function, a degenerate system is composed of different elements performing similar or overlapping functions. Here, we describe the degenerate structure of gene regulatory systems from the basic genetic code to flexible epigenomic modifications, and discuss how these structural features have contributed to organism complexity, robustness, plasticity and evolvability. PMID:24335757

A Computational Framework for Bioimaging Simulation

PubMed Central

Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi

2015-01-01

Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508

Using an Adaptive Expertise Lens to Understand the Quality of Teachers' Classroom Implementation of Computer-Supported Complex Systems Curricula in High School Science

ERIC Educational Resources Information Center

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-01-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to…

Education and Training in the Social, Behavioral, and Economic Sciences: A Plan of Action. A Report to the National Science Foundation.

ERIC Educational Resources Information Center

Levine, Felice J.; Abler, Ronald F.; Rosich, Katherine J.

2004-01-01

Over the last quarter of a century, the world has undergone rapid change. Almost every aspect of human life is more complex and interdependent, requiring knowledge of human and social systems as well as physical and biological systems. The social, behavioral, and economic (SBE) sciences contribute penetrating insights on such issues as the causes…

Bone Quest - A Space-Based Science and Health Education Unit

NASA Technical Reports Server (NTRS)

Smith, Scott M.; David-Street, Janis E.; Abrams, Steve A.

2000-01-01

This proposal addresses the need for effective and innovative science and health education materials that focus on space bone biology and its implications for bone health on Earth. The focus of these materials, bone biology and health, will increase science knowledge as well as health awareness. Current investigations of the bone loss observed after long-duration space missions provide a link between studies of bone health in space, and studies of osteoporosis, a disease characterized by bone loss and progressive skeletal weakness. The overall goal of this project is to design and develop web-based and print-based materials for high school science students, that will address the following: a) knowledge of normal bone biology and bone biology in a microgravity environment; b) knowledge of osteoporosis; c) knowledge of treatment modalities for space- and Earth-based bone loss; and d} bone-related nutrition knowledge and behavior. To this end, we propose to design and develop a Bone Biology Tutorial which will instruct students about normal bone biology, bone biology in a microgravity environment, osteoporosis - its definition, detection, risk factors, and prevention, treatment modalities for space- and Earth-based bone loss, and the importance of nutrition in bone health. Particular emphasis will be placed on current trends in . adolescent nutrition, and their relationships to bone health. Additionally, we propose to design and develop two interactive nutrition/health ' education activities that will allow students to apply the information provided in the Bone Biology Tutorial. In the first, students will apply constructs provided in the Bone Biology Tutorial to design "Bone Health Plans" for space travelers.

Corrections to chance fluctuations: quantum mind in biological evolution?

PubMed

Damiani, Giuseppe

2009-01-01

According to neo-Darwinian theory, biological evolution is produced by natural selection of random hereditary variations. This assumption stems from the idea of a mechanical and deterministic world based on the laws of classic physics. However, the increased knowledge of relationships between metabolism, epigenetic systems, and editing of nucleic acids suggests the existence of self-organized processes of adaptive evolution in response to environmental stresses. Living organisms are open thermodynamic systems which use entropic decay of external source of electromagnetic energy to increase their internal dynamic order and to generate new genetic and epigenetic information with a high degree of coherency and teleonomic creativity. Sensing, information processing, and decision making of biological systems might be mainly quantum phenomena. Amplification of microscopic quantum events using the long-range correlation of fractal structures, at the borderline between deterministic order and unpredictable chaos, may be used to direct a reproducible transition of the biological systems towards a defined macroscopic state. The discoveries of many natural genetic engineering systems, the ability to choose the most effective solutions, and the emergence of complex forms of consciousness at different levels confirm the importance of mind-action directed processes in biological evolution, as suggested by Alfred Russel Wallace. Although the main Darwinian principles will remain a crucial component of our understanding of evolution, a radical rethinking of the conceptual structure of the neo-Darwinian theory is needed.

Engineering biological systems toward a sustainable bioeconomy.

PubMed

Lopes, Mateus Schreiner Garcez

2015-06-01

The nature of our major global risks calls for sustainable innovations to decouple economic growth from greenhouse gases emission. The development of sustainable technologies has been negatively impacted by several factors including sugar production costs, production scale, economic crises, hydraulic fracking development and the market inability to capture externality costs. However, advances in engineering of biological systems allow bridging the gap between exponential growth of knowledge about biology and the creation of sustainable value chains for a broad range of economic sectors. Additionally, industrial symbiosis of different biobased technologies can increase competitiveness and sustainability, leading to the development of eco-industrial parks. Reliable policies for carbon pricing and revenue reinvestments in disruptive technologies and in the deployment of eco-industrial parks could boost the welfare while addressing our major global risks toward the transition from a fossil to a biobased economy.

A Problem-Sorting Task Detects Changes in Undergraduate Biological Expertise over a Single Semester.

PubMed

Hoskinson, Anne-Marie; Maher, Jessica Middlemis; Bekkering, Cody; Ebert-May, Diane

2017-01-01

Calls for undergraduate biology reform share similar goals: to produce people who can organize, use, connect, and communicate about biological knowledge. Achieving these goals requires students to gain disciplinary expertise. Experts organize, access, and apply disciplinary knowledge differently than novices, and expertise is measurable. By asking introductory biology students to sort biological problems, we investigated whether they changed how they organized and linked biological ideas over one semester of introductory biology. We administered the Biology Card Sorting Task to 751 students enrolled in their first or second introductory biology course focusing on either cellular-molecular or organismal-population topics, under structured or unstructured sorting conditions. Students used a combination of superficial, deep, and yet-uncharacterized ways of organizing and connecting biological knowledge. In some cases, this translated to more expert-like ways of organizing knowledge over a single semester, best predicted by whether students were enrolled in their first or second semester of biology and by the sorting condition completed. In addition to illuminating differences between novices and experts, our results show that card sorting is a robust way of detecting changes in novices' biological expertise-even in heterogeneous populations of novice biology students over the time span of a single semester. © 2017 A.-M. Hoskinson et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License(http://creativecommons.org/licenses/by-nc-sa/3.0).

Environmental stressors influencing hormones and systems physiology in cattle

PubMed Central

2014-01-01

Environmental stressors undoubtedly influence organismal biology, specifically the endocrine system that, in turn, impact cattle at the systems physiology level. Despite the significant advances in understanding the genetic determinants of the ideal dairy or beef cow, there is a grave lack of understanding of the systems physiology and effects of the environmental stressors that interfere with the endocrine system. This is a major problem because the lack of such knowledge is preventing advances in understanding gene-environment interactions and developing science-based solutions to these challenges. In this review, we synthesize the current knowledge on the nature of the major environmental stressors, such as climate (heat, cold, wind, and humidity), nutrition (feeds, feeding systems, and endocrine disruptors) and management (housing density and conditions, transportation, weaning practices). We summarize the impact of each one of these factors on cattle at the systems level, and provide solutions for the challenges. PMID:24996419

A Knowledge Base for Teaching Biology Situated in the Context of Genetic Testing

NASA Astrophysics Data System (ADS)

van der Zande, Paul; Waarlo, Arend Jan; Brekelmans, Mieke; Akkerman, Sanne F.; Vermunt, Jan D.

2011-10-01

Recent developments in the field of genomics will impact the daily practice of biology teachers who teach genetics in secondary education. This study reports on the first results of a research project aimed at enhancing biology teacher knowledge for teaching genetics in the context of genetic testing. The increasing body of scientific knowledge concerning genetic testing and the related consequences for decision-making indicate the societal relevance of such a situated learning approach. What content knowledge do biology teachers need for teaching genetics in the personal health context of genetic testing? This study describes the required content knowledge by exploring the educational practice and clinical genetic practices. Nine experienced teachers and 12 respondents representing the clinical genetic practices (clients, medical professionals, and medical ethicists) were interviewed about the biological concepts and ethical, legal, and social aspects (ELSA) of testing they considered relevant to empowering students as future health care clients. The ELSA suggested by the respondents were complemented by suggestions found in the literature on genetic counselling. The findings revealed that the required teacher knowledge consists of multiple layers that are embedded in specific genetic test situations: on the one hand, the knowledge of concepts represented by the curricular framework and some additional concepts (e.g. multifactorial and polygenic disorder) and, on the other hand, more knowledge of ELSA and generic characteristics of genetic test practice (uncertainty, complexity, probability, and morality). Suggestions regarding how to translate these characteristics, concepts, and ELSA into context-based genetics education are discussed.

Prions: Introducing a Complex Scientific Controversy to a Biology Classroom

ERIC Educational Resources Information Center

Zaitsev, Igor V.

2009-01-01

Thomas Kuhn, in "The Structure of Scientific Revolutions," posited that science does not progress by the steady accumulation of knowledge, but rather by a system of competition among paradigms. They vie for supremacy through greater parsimony, explanatory power, and popularity among the community of scientists (Kuhn, 1962). The current…

Visualization Skills and Their Incorporation in Biology Curriculum

ERIC Educational Resources Information Center

Osodo, J.; Amory, A.; Graham-Jolly, M.; Indoshi, F. C.

2010-01-01

Many graduates of various levels and disciplines appear unable to practically apply their knowledge in problem solving situations. However, few education systems are adopting modern education practices such as visualization skills that intrinsically motivate and engage learners and are at the same time flexible enough to consider students'…

Backyard Botany: Using GPS Technology in the Science Classroom

ERIC Educational Resources Information Center

March, Kathryn A.

2012-01-01

Global Positioning System (GPS) technology can be used to connect students to the natural world and improve their skills in observation, identification, and classification. Using GPS devices in the classroom increases student interest in science, encourages team-building skills, and improves biology content knowledge. Additionally, it helps…

Proteomic approach to nanotoxicity.

PubMed

Matysiak, Magdalena; Kapka-Skrzypczak, Lucyna; Brzóska, Kamil; Gutleb, Arno C; Kruszewski, Marcin

2016-03-30

In recent years a large number of engineered nanomaterials (NMs) have been developed with promising technical benefits for consumers and medical appliances. In addition to already known potentially advantageous biological properties (antibiotic, antifungal and antiviral activity) of NMs, many new medical applications of NMs are foreseen, such as drug carriers, contrast agents, radiopharmaceuticals and many others. However, there is increasing concern about potential environmental and health effects due to NMs exposure. An increasing body of evidence suggests that NMs may trigger undesirable hazardous interactions with biological systems with potential to generate harmful effects. In this review we summarized a current state of knowledge on the proteomics approaches to nanotoxicity, including protein corona formation, in vitro and in vivo effects of exposure to NMs on proteome of different classes of organisms, from bacteria and plants to mammals. The effects of NMs on the proteome of environmentally relevant organisms are also described. Despite the benefit that development of nanotechnology may bring to the society, there are still major gaps of knowledge on the influence of nanomaterials on human health and the environment. Thus, it seems necessary to conduct further interdisciplinary research to fill the knowledge gaps in NM toxicity, using more holistic approaches than offered by conventional biological techniques. “OMICS” techniques will certainly help researchers in this field. In this paper we summarized the current stage of knowledge of the effects of nanoparticles on the proteome of different organisms, including those commonly used as an environmentally relevant indicator organisms.

The effects of explicit visual cues in reading biological diagrams

NASA Astrophysics Data System (ADS)

Ge, Yun-Ping; Unsworth, Len; Wang, Kuo-Hua

2017-03-01

Drawing on cognitive theories, this study intends to investigate the effects of explicit visual cues which have been proposed as a critical factor in facilitating understanding of biological images. Three diagrams from Taiwanese textbooks with implicit visual cues, involving the concepts of biological classification systems, fish taxonomy, and energy pyramid, were selected as the reading materials for the control group and reformatted in tree structure or with additional arrows as the diagrams for the treatment group. A quasi-experiment with an online reading test was conducted to examine the effect of the different image conditions on reading comprehension of the two groups. In total, 192 Taiwanese participants from year 7 were assigned randomly into either control group or treatment group according to the pre-test of relevant prior knowledge. The results indicated that not all explicit visual cues were significantly efficient. Only the explicit tree-structured diagrams cued significantly the key concepts of qualitative class-inclusion, parallel relations, and fish taxonomy. Meanwhile the effect of indexical arrows was not significant. The inconsistent effect of tree structure and arrows might be related to the extent of image reformation in which the tree-structured diagrams had undergone radical change of knowledge representation; meanwhile, the arrows had not changed the diagram structure of energy pyramid. The factor of prior knowledge was essential in considering the influence of image design as the effect of diagrams was very different for low and high prior knowledge students. Implications are drawn for the importance of visual design in textbooks.

Systems biology of lactic acid bacteria: a critical review

PubMed Central

2011-01-01

Understanding the properties of a system as emerging from the interaction of well described parts is the most important goal of Systems Biology. Although in the practice of Lactic Acid Bacteria (LAB) physiology we most often think of the parts as the proteins and metabolites, a wider interpretation of what a part is can be useful. For example, different strains or species can be the parts of a community, or we could study only the chemical reactions as the parts of metabolism (and forgetting about the enzymes that catalyze them), as is done in flux balance analysis. As long as we have some understanding of the properties of these parts, we can investigate whether their interaction leads to novel or unanticipated behaviour of the system that they constitute. There has been a tendency in the Systems Biology community to think that the collection and integration of data should continue ad infinitum, or that we will otherwise not be able to understand the systems that we study in their details. However, it may sometimes be useful to take a step back and consider whether the knowledge that we already have may not explain the system behaviour that we find so intriguing. Reasoning about systems can be difficult, and may require the application of mathematical techniques. The reward is sometimes the realization of unexpected conclusions, or in the worst case, that we still do not know enough details of the parts, or of the interactions between them. We will discuss a number of cases, with a focus on LAB-related work, where a typical systems approach has brought new knowledge or perspective, often counterintuitive, and clashing with conclusions from simpler approaches. Also novel types of testable hypotheses may be generated by the systems approach, which we will illustrate. Finally we will give an outlook on the fields of research where the systems approach may point the way for the near future. PMID:21995498

Applications of a formal approach to decipher discrete genetic networks.

PubMed

Corblin, Fabien; Fanchon, Eric; Trilling, Laurent

2010-07-20

A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language. In this article our formal and declarative approach is applied to three biological applications. The software environment that we developed allows to specifically address each application through a new class of biologically relevant queries. We show that we can describe easily and in a formal manner the partial knowledge about a genetic network. Moreover we show that this environment, based on a constraint algorithmic approach, offers a wide variety of functionalities, going beyond simple simulations, such as proof of consistency, model revision, prediction of properties, search for minimal models relatively to specified criteria. The formal approach proposed here deeply changes the way to proceed in the exploration of genetic and biochemical networks, first by avoiding the usual trial-and-error procedure, and second by placing the emphasis on sets of solutions, rather than a single solution arbitrarily chosen among many others. Last, the constraint approach promotes an integration of model and experimental data in a single framework.

Biolog(TM) ID as compared to 16S ribosomal RNA ID for environmental isolates from the deep subsurface

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

McKinsey, P.C.

2000-05-05

The U.S. Dept of Energy (DOE) Subsurface Microbial Culture Collection (SMCC) contains nearly 10,000 strains of microorganisms isolated from terrestrial subsurface environments. Many of the aerobic, gram-negative, chemoheterotrophs isolated from the DOE Savannah River Site (SRS) have previously been identified by phylogenetic analysis of 16S ribosomal RNA (rRNA) gene nucleotide sequences. These SMCC isolates are currently being examined using Biolog GN Microplates and the Biolog Microstation System in order to gain knowledge of their metabolic capabilities and to compare Biolog IDs with 16S IDs. To accommodate the particular needs of these subsurface isolates, which are often incapable of growing undermore » high-nutrient conditions, Biolog's recommendations for inoculating isolates into Biolog GN Microplates have been altered. The isolates are grown on low nutrient media, sodium thioglycolate (3mM) is added to the culture media to inhibit capsule formation, and a low density of bacteria is inoculated into the microplate. Using these altered inoculation criteria, 60 percent of these SMCC isolates have a Biolog genus ID that matches the 16S rRNA ID. These results indicate that the Biolog System can be a good means of identifying unusual environmental isolates, even when recommended inoculation procedures are altered to accommodate particular isolate needs.« less

Software For Design Of Life-Support Systems

NASA Technical Reports Server (NTRS)

Rudokas, Mary R.; Cantwell, Elizabeth R.; Robinson, Peter I.; Shenk, Timothy W.

1991-01-01

Design Assistant Workstation (DAWN) computer program is prototype of expert software system for analysis and design of regenerative, physical/chemical life-support systems that revitalize air, reclaim water, produce food, and treat waste. Incorporates both conventional software for quantitative mathematical modeling of physical, chemical, and biological processes and expert system offering user stored knowledge about materials and processes. Constructs task tree as it leads user through simulated process, offers alternatives, and indicates where alternative not feasible. Also enables user to jump from one design level to another.

Direct Experience with Nature and the Development of Biological Knowledge

ERIC Educational Resources Information Center

Longbottom, Sarah E.; Slaughter, Virginia

2016-01-01

Research Findings: An emerging consensus is that casual, direct contact with nature influences the development of children's biological knowledge. Here we review the existing literature on this topic, focusing on the effects of (a) rural versus urban rearing environments and (b) pet ownership and care on children's biological concepts and…

Teacher Education and the New Biology

ERIC Educational Resources Information Center

Reiss, Michael J.

2006-01-01

Recent years have seen a growth not only in biological knowledge but also, and more significantly for teacher education, in the types of knowledge manifested in biology. No longer, therefore, is it adequate for teachers to retain a Mertonian or a Popperian conception of science. Today's teachers of science need also to be able to help their…

A Problem-Sorting Task Detects Changes in Undergraduate Biological Expertise over a Single Semester

ERIC Educational Resources Information Center

Hoskinson, Anne-Marie; Maher, Jessica Middlemis; Bekkering, Cody; Ebert-May, Diane

2017-01-01

Calls for undergraduate biology reform share similar goals: to produce people who can organize, use, connect, and communicate about biological knowledge. Achieving these goals requires students to gain disciplinary expertise. Experts organize, access, and apply disciplinary knowledge differently than novices, and expertise is measurable. By asking…

Investigating Lebanese Grade Seven Biology Teachers Mathematical Knowledge and Skills: A Case Study

ERIC Educational Resources Information Center

Raad, Nawal Abou; Chatila, Hanadi

2016-01-01

This paper investigates Lebanese grade 7 biology teachers' mathematical knowledge and skills, by exploring how they explain a visual representation in an activity depending on the mathematical concept "Function". Twenty Lebanese in-service biology teachers participated in the study, and were interviewed about their explanation for the…

Biology. Teacher's Guide. Investigations in Natural Science.

ERIC Educational Resources Information Center

Renner, John W.; And Others

Investigations in Natural Science is a program in secondary school biology, chemistry, and physics based upon the description of science as a quest for knowledge, not the knowledge itself. This teaching guide is designed for use with the 18 biology investigations found in the student manual. These investigations focus on concepts related to:…

Current knowledge and attitudes: Russian olive biology, ecology and management

Treesearch

Sharlene E. Sing; Kevin J. Delaney

2016-01-01

The primary goals of a two-day Russian olive symposium held in February 2014 were to disseminate current knowledge and identify data gaps regarding Russian olive biology and ecology, distributions, integrated management, and to ascertain the feasibility and acceptance of a proposed program for classical biological control of Russian olive. The symposium was...

Local indicators of climate change: The potential contribution of local knowledge to climate research

PubMed Central

Reyes-García, Victoria; Fernández-Llamazares, Álvaro; Guèze, Maximilien; Garcés, Ariadna; Mallo, Miguel; Vila-Gómez, Margarita; Vilaseca, Marina

2016-01-01

Local knowledge has been proposed as a place-based tool to ground-truth climate models and to narrow their geographic sensitivity. To assess the potential role of local knowledge in our quest to understand better climate change and its impacts, we first need to critically review the strengths and weaknesses of local knowledge of climate change and the potential complementarity with scientific knowledge. With this aim, we conducted a systematic, quantitative meta-analysis of published peer-reviewed documents reporting local indicators of climate change (including both local observations of climate change and observed impacts on the biophysical and the social systems). Overall, primary data on the topic are not abundant, the methodological development is incipient, and the geographical extent is unbalanced. On the 98 case studies documented, we recorded the mention of 746 local indicators of climate change, mostly corresponding to local observations of climate change (40%), but also to observed impacts on the physical (23%), the biological (19%), and the socioeconomic (18%) systems. Our results suggest that, even if local observations of climate change are the most frequently reported type of change, the rich and fine-grained knowledge in relation to impacts on biophysical systems could provide more original contributions to our understanding of climate change at local scale. PMID:27642368

Associated impairment of the categories of conspecifics and biological entities: cognitive and neuroanatomical aspects of a new case.

PubMed

Capitani, Erminio; Chieppa, Francesca; Laiacona, Marcella

2010-05-01

Case A.C.A. presented an associated impairment of visual recognition and semantic knowledge for celebrities and biological objects. This case was relevant for (a) the neuroanatomical correlations, and (b) the relationship between visual recognition and semantics within the biological domain and the conspecifics domain. A.C.A. was not affected by anterior temporal damage. Her bilateral vascular lesions were localized on the medial and inferior temporal gyrus on the right and on the intermediate fusiform gyrus on the left, without concomitant lesions of the parahippocampal gyrus or posterior fusiform. Data analysis was based on a novel methodology developed to estimate the rate of stored items in the visual structural description system (SDS) or in the face recognition unit. For each biological object, no particular correlation was found between the visual information accessed through the semantic system and that tapped by the picture reality judgement. Findings are discussed with reference to whether a putative resource commonality is likely between biological objects and conspecifics, and whether or not either category may depend on an exclusive neural substrate.

Blackboard architecture for medical image interpretation

NASA Astrophysics Data System (ADS)

Davis, Darryl N.; Taylor, Christopher J.

1991-06-01

There is a growing interest in using sophisticated knowledge-based systems for biomedical image interpretation. We present a principled attempt to use artificial intelligence methodologies in interpreting lateral skull x-ray images. Such radiographs are routinely used in cephalometric analysis to provide quantitative measurements useful to clinical orthodontists. Manual and interactive methods of analysis are known to be error prone and previous attempts to automate this analysis typically fail to capture the expertise and adaptability required to cope with the variability in biological structure and image quality. An integrated model-based system has been developed which makes use of a blackboard architecture and multiple knowledge sources. A model definition interface allows quantitative models, of feature appearance and location, to be built from examples as well as more qualitative modelling constructs. Visual task definition and blackboard control modules allow task-specific knowledge sources to act on information available to the blackboard in a hypothesise and test reasoning cycle. Further knowledge-based modules include object selection, location hypothesis, intelligent segmentation, and constraint propagation systems. Alternative solutions to given tasks are permitted.

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms

ERIC Educational Resources Information Center

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S.

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections…

A machine-learned analysis of human gene polymorphisms modulating persisting pain points at major roles of neuroimmune processes.

PubMed

Kringel, Dario; Lippmann, Catharina; Parnham, Michael J; Kalso, Eija; Ultsch, Alfred; Lötsch, Jörn

2018-06-19

Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine learning techniques may combine this knowledge with results of genetic research gathered in any context, which permits the identification of the key biological processes involved in chronic sensitization to pain. Based on published evidence, a set of 110 genes carrying variants reported to be associated with modulation of the clinical phenotype of persisting pain in eight different clinical settings was submitted to unsupervised machine-learning aimed at functional clustering. Subsequently, a mathematically supported subset of genes, comprising those most consistently involved in persisting pain, was analyzed by means of computational functional genomics in the Gene Ontology knowledgebase. Clustering of genes with evidence for a modulation of persisting pain elucidated a functionally heterogeneous set. The situation cleared when the focus was narrowed to a genetic modulation consistently observed throughout several clinical settings. On this basis, two groups of biological processes, the immune system and nitric oxide signaling, emerged as major players in sensitization to persisting pain, which is biologically highly plausible and in agreement with other lines of pain research. The present computational functional genomics-based approach provided a computational systems-biology perspective on chronic sensitization to pain. Human genetic control of persisting pain points to the immune system as a source of potential future targets for drugs directed against persisting pain. Contemporary machine-learned methods provide innovative approaches to knowledge discovery from previous evidence. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Exploitation of biotechnology in a large company.

PubMed

Dart, E C

1989-08-31

Almost from the outset, most large companies saw the 'new biotechnology' not as a new business but as a set of very powerful techniques that, in time, would radically improve the understanding of biological systems. This new knowledge was generally seen by them as enhancing the process of invention and not as a substitute for tried and tested ways of meeting clearly identified targets. As the knowledge base grows, so the big-company response to biotechnology becomes more positive. Within ICI, biotechnology is now integrated into five bio-businesses (Pharmaceuticals, Agrochemicals, Seeds, Diagnostics and Biological Products). Within the Central Toxicology Laboratory it also contributes to the understanding of the mechanisms of toxic action of chemicals as part of assessing risk. ICI has entered two of these businesses (Seeds and Diagnostics) because it sees biotechnology making a major contribution to the profitability of each.

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.

Investigating Novice and Expert Conceptions of Genetically Modified Organisms

PubMed Central

Potter, Lisa M.; Bissonnette, Sarah A.; Knight, Jonathan D.; Tanner, Kimberly D.

2017-01-01

The aspiration of biology education is to give students tools to apply knowledge learned in the classroom to everyday life. Genetic modification is a real-world biological concept that relies on an in-depth understanding of the molecular behavior of DNA and proteins. This study investigated undergraduate biology students’ conceptions of genetically modified organisms (GMOs) when probed with real-world, molecular and cellular, and essentialist cues, and how those conceptions compared across biology expertise. We developed a novel written assessment tool and administered it to 120 non–biology majors, 154 entering biology majors, 120 advanced biology majors (ABM), and nine biology faculty. Results indicated that undergraduate biology majors rarely included molecular and cellular rationales in their initial explanations of GMOs. Despite ABM demonstrating that they have much of the biology knowledge necessary to understand genetic modification, they did not appear to apply this knowledge to explaining GMOs. Further, this study showed that all undergraduate student populations exhibited evidence of essentialist thinking while explaining GMOs, regardless of their level of biology training. Finally, our results suggest an association between scientifically accurate ideas and the application of molecular and cellular rationales, as well as an association between misconceptions and essentialist rationales. PMID:28821537

STARLIFE - An International Campaign to Study the Role of Galactic Cosmic Radiation in Astrobiological Model Systems

NASA Astrophysics Data System (ADS)

Moeller, Ralf; Raguse, Marina; Leuko, Stefan; Berger, Thomas; Hellweg, Christine Elisabeth; Fujimori, Akira; Okayasu, Ryuichi; Horneck, Gerda

2017-02-01

In-depth knowledge regarding the biological effects of the radiation field in space is required for assessing the radiation risks in space. To obtain this knowledge, a set of different astrobiological model systems has been studied within the STARLIFE radiation campaign during six irradiation campaigns (2013-2015). The STARLIFE group is an international consortium with the aim to investigate the responses of different astrobiological model systems to the different types of ionizing radiation (X-rays, γ rays, heavy ions) representing major parts of the galactic cosmic radiation spectrum. Low- and high-energy charged particle radiation experiments have been conducted at the Heavy Ion Medical Accelerator in Chiba (HIMAC) facility at the National Institute of Radiological Sciences (NIRS) in Chiba, Japan. X-rays or γ rays were used as reference radiation at the German Aerospace Center (DLR, Cologne, Germany) or Beta-Gamma-Service GmbH (BGS, Wiehl, Germany) to derive the biological efficiency of different radiation qualities. All samples were exposed under identical conditions to the same dose and qualities of ionizing radiation (i) allowing a direct comparison between the tested specimens and (ii) providing information on the impact of the space radiation environment on currently used astrobiological model organisms.

Effects of biology teachers' professional knowledge and cognitive activation on students' achievement

NASA Astrophysics Data System (ADS)

Förtsch, Christian; Werner, Sonja; von Kotzebue, Lena; Neuhaus, Birgit J.

2016-11-01

This study examined the effects of teachers' biology-specific dimensions of professional knowledge - pedagogical content knowledge (PCK) and content knowledge (CK) - and cognitively activating biology instruction, as a feature of instructional quality, on students' learning. The sample comprised 39 German secondary school teachers whose lessons on the topic neurobiology were videotaped twice. Teachers' instruction was coded with regard to cognitive activation using a rating manual. Multilevel path analysis results showed a positive significant effect of cognitive activation on students' learning and an indirect effect of teachers' PCK on students' learning mediated through cognitive activation. These findings highlight the importance of PCK in preservice biology teachers' education. Items of the rating manual may be used to provide exemplars of concrete teaching situations during university seminars for preservice teacher education or professional development initiatives for in-service teachers.

Biological warfare agents

PubMed Central

Thavaselvam, Duraipandian; Vijayaraghavan, Rajagopalan

2010-01-01

The recent bioterrorist attacks using anthrax spores have emphasized the need to detect and decontaminate critical facilities in the shortest possible time. There has been a remarkable progress in the detection, protection and decontamination of biological warfare agents as many instrumentation platforms and detection methodologies are developed and commissioned. Even then the threat of biological warfare agents and their use in bioterrorist attacks still remain a leading cause of global concern. Furthermore in the past decade there have been threats due to the emerging new diseases and also the re-emergence of old diseases and development of antimicrobial resistance and spread to new geographical regions. The preparedness against these agents need complete knowledge about the disease, better research and training facilities, diagnostic facilities and improved public health system. This review on the biological warfare agents will provide information on the biological warfare agents, their mode of transmission and spread and also the detection systems available to detect them. In addition the current information on the availability of commercially available and developing technologies against biological warfare agents has also been discussed. The risk that arise due to the use of these agents in warfare or bioterrorism related scenario can be mitigated with the availability of improved detection technologies. PMID:21829313

Co-production of knowledge: An Inuit Indigenous Knowledge perspective

NASA Astrophysics Data System (ADS)

Daniel, R.; Behe, C.

2017-12-01

A "co-production of knowledge" approach brings together different knowledge systems while building equitable and collaborative partnerships from `different ways of knowing.' Inuit Indigenous Knowledge is a systematic way of thinking applied to phenomena across biological, physical, cultural and spiritual systems; rooted with a holistic understanding of ecosystems (ICC Alaska 2016). A holistic image of Arctic environmental change is attained by bringing Indigenous Knowledge (IK) holders and scientists together through a co-production of knowledge framework. Experts from IK and science should be involved together from the inception of a project. IK should be respected as its own knowledge system and should not be translated into science. A co-production of knowledge approach is important in developing adaptation policies and practices, for sustainability and to address biodiversity conservation (Daniel et al. 2016). Co-production of knowledge is increasingly being recognized by the scientific community at-large. However, in many instances the concept is being incorrectly applied. This talk will build on the important components of co-production of knowledge from an Inuit perspective and specifically IK. In this presentation we will differentiate the co-production of knowledge from a multi-disciplinary approach or multi-evidence based decision-making. We underscore the role and value of different knowledge systems with different methodologies and the need for collaborative approaches in identifying research questions. We will also provide examples from our experiences with Indigenous communities and scientists in the Arctic. References: Inuit Circumpolar Council of Alaska. 2016. Alaskan Inuit Food Security Conceptual Framework: How to Assess the Arctic From An Inuit Perspective, 201pp. Daniel, R., C. Behe, J. Raymond-Yakoubian, E. Krummel, and S. Gearhead. Arctic Observing Summit White Paper Synthesis, Theme 6: Interfacing Indigenous Knowledge, Community-based Monitoring and Scientific Methods for Sustained Arctic Observations. http://www.arcticobservingsummit.org/sites/arcticobservingsummit.org/files/Daniel_Laing_Kielsen%20Holm_et_al-AOS2016-Theme-6-IK-CBM-Synthesis-updated-2016-04.pdf

Immunoisolation to prevent tissue graft rejection: Current knowledge and future use.

PubMed

David, Anu; Day, James; Shikanov, Ariella

2016-05-01

This review focuses on the concept of immunoisolation and how this method has evolved over the last few decades. The concept of immunoisolation came out of the need to protect allogeneic transplant tissue from the host immune system and avoid systemic side effects of immunosuppression. The latter remains a significant hurdle in clinical translation of using tissue transplants for restoring endocrine function in diabetes, growth hormone deficiency, and other conditions. Herein, we review the most significant works studying the use of hydrogels, specifically alginate and poly (ethylene glycol), and membranes for immunoisolation and discuss how this approach can be applied in reproductive biology. © 2016 by the Society for Experimental Biology and Medicine.

Toward patient-centered, personalized and personal decision support and knowledge management: a survey.

PubMed

Leong, T-Y

2012-01-01

This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care. The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations. Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support. Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and participatory health care model for patient-centered, personalized medicine. There is also an increasing emphasis on managing complexity with changing care models, processes, and settings.

ISOL@: an Italian SOLAnaceae genomics resource.

PubMed

Chiusano, Maria Luisa; D'Agostino, Nunzio; Traini, Alessandra; Licciardello, Concetta; Raimondo, Enrico; Aversano, Mario; Frusciante, Luigi; Monti, Luigi

2008-03-26

Present-day '-omics' technologies produce overwhelming amounts of data which include genome sequences, information on gene expression (transcripts and proteins) and on cell metabolic status. These data represent multiple aspects of a biological system and need to be investigated as a whole to shed light on the mechanisms which underpin the system functionality. The gathering and convergence of data generated by high-throughput technologies, the effective integration of different data-sources and the analysis of the information content based on comparative approaches are key methods for meaningful biological interpretations. In the frame of the International Solanaceae Genome Project, we propose here ISOLA, an Italian SOLAnaceae genomics resource. ISOLA (available at http://biosrv.cab.unina.it/isola) represents a trial platform and it is conceived as a multi-level computational environment.ISOLA currently consists of two main levels: the genome and the expression level. The cornerstone of the genome level is represented by the Solanum lycopersicum genome draft sequences generated by the International Tomato Genome Sequencing Consortium. Instead, the basic element of the expression level is the transcriptome information from different Solanaceae species, mainly in the form of species-specific comprehensive collections of Expressed Sequence Tags (ESTs). The cross-talk between the genome and the expression levels is based on data source sharing and on tools that enhance data quality, that extract information content from the levels' under parts and produce value-added biological knowledge. ISOLA is the result of a bioinformatics effort that addresses the challenges of the post-genomics era. It is designed to exploit '-omics' data based on effective integration to acquire biological knowledge and to approach a systems biology view. Beyond providing experimental biologists with a preliminary annotation of the tomato genome, this effort aims to produce a trial computational environment where different aspects and details are maintained as they are relevant for the analysis of the organization, the functionality and the evolution of the Solanaceae family.

A convenient dichotomy: critical eyes on the limits to biological knowledge

NASA Astrophysics Data System (ADS)

Milne, Catherine

2011-06-01

In The Secret Identity of a Biology Textbook: straight and naturally sexed, Jesse Bazzul and Heather Sykes conduct a case study of a biology textbook as an oppressive instructional material. Using queer theory they explore how the text of the biology textbook produces "truths" about sex, gender, and sexuality. Their analysis is complemented by the Forum papers by Jay Lemke and Francis Broadway who broaden the analysis examining the way that what counts as knowledge in science is a political decision while also encouraging authors, including Bazzul and Sykes, to also look critically at their own theoretical lenses. In this paper I pull together their ideas while exploring cultural contexts for a more nuanced representation of biological knowledge and the politics of what it means to know science.

Ames Life Science Data Archive: Translational Rodent Research at Ames

NASA Technical Reports Server (NTRS)

Wood, Alan E.; French, Alison J.; Ngaotheppitak, Ratana; Leung, Dorothy M.; Vargas, Roxana S.; Maese, Chris; Stewart, Helen

2014-01-01

The Life Science Data Archive (LSDA) office at Ames is responsible for collecting, curating, distributing and maintaining information pertaining to animal and plant experiments conducted in low earth orbit aboard various space vehicles from 1965 to present. The LSDA will soon be archiving data and tissues samples collected on the next generation of commercial vehicles; e.g., SpaceX & Cygnus Commercial Cargo Craft. To date over 375 rodent flight experiments with translational application have been archived by the Ames LSDA office. This knowledge base of fundamental research can be used to understand mechanisms that affect higher organisms in microgravity and help define additional research whose results could lead the way to closing gaps identified by the Human Research Program (HRP). This poster will highlight Ames contribution to the existing knowledge base and how the LSDA can be a resource to help answer the questions surrounding human health in long duration space exploration. In addition, it will illustrate how this body of knowledge was utilized to further our understanding of how space flight affects the human system and the ability to develop countermeasures that negate the deleterious effects of space flight. The Ames Life Sciences Data Archive (ALSDA) includes current descriptions of over 700 experiments conducted aboard the Shuttle, International Space Station (ISS), NASA/MIR, Bion/Cosmos, Gemini, Biosatellites, Apollo, Skylab, Russian Foton, and ground bed rest studies. Research areas cover Behavior and Performance, Bone and Calcium Physiology, Cardiovascular Physiology, Cell and Molecular Biology, Chronobiology, Developmental Biology, Endocrinology, Environmental Monitoring, Gastrointestinal Physiology, Hematology, Immunology, Life Support System, Metabolism and Nutrition, Microbiology, Muscle Physiology, Neurophysiology, Pharmacology, Plant Biology, Pulmonary Physiology, Radiation Biology, Renal, Fluid and Electrolyte Physiology, and Toxicology. These experiment descriptions and data can be accessed online via the public LSDA website (http://lsda.jsc.nasa.gov) and information can be requested via the Data Request form at http://lsda.jsc.nasa.gov/common/dataRequest/dataRequest.aspx or by contacting the ALSDA Office at: Alison.J.French@nasa.gov

Can we manage for biological diversity in the absence of science?

USGS Publications Warehouse

Trauger, D.L.; Hall, R.J.

1995-01-01

Conservation of biological diversity is dependent on sound scientific information about underlying ecological processes. Current knowledge of the composition, distribution, abundance and life cycles of most species of plants and animals is incomplete, insufficient, unreliable, or nonexistent. Contemporary managers are also confronted with additional levels of complexity related to varying degrees of knowledge and understanding about interactions of species and ecosystems. Consequently, traditional species-oriented management schemes may have unintended consequences and ecosystem-oriented management initiatives may fail in the face of inadequate or fragmentary information on the structure, function, and dynamics of biotic communities and ecological systems. Nevertheless, resource managers must make decisions and manage based on the best biological information currently available. Adaptive resource management may represent a management paradigm that allows managers to learn something about the species or systems that they are managing while they are managing, but potential pitfalls lurk for such approaches. In addition to lack of control over the primary physical, chemical, and ecological processes, managers also lack control over social, economic, and political parameters affecting resource management options. Moreover, appropriate goals may be difficult to identify and criteria for determining success may be elusive. Some management responsibilities do not lend themselves to adaptive strategies. Finally, the lessons learned from adaptive management are usually obtained from a highly situational context that may limit applicability in a wider range of situations or undermine confidence that problems and solutions were properly diagnosed and addressed. Several scenarios are critically examined where adaptive management approaches may be inappropriate or ineffective and where management for biological diversity may be infeasible or inefficient without a sound scientific basis. Whereas some level of management must exist to meet agency responsibilities, more research is needed to conserve biological diversity.

Using a "Primer Unit" in an Introductory Biology Course: "A Soft Landing"

ERIC Educational Resources Information Center

Marbach-Ad, Gili; Ribke, Melina; Gershoni, Jonathan M.

2006-01-01

This study aimed to facilitate students' entrance to an introductory cell biology course for biology majors. The most prominent difficulty in this introductory course, is students' poor background-knowledge, such as a lack of understanding of very basic concepts and terms, and the huge differences in students' background knowledge. In order to…

Public Understanding of Plant Biology: Voices from the Bottom of the Garden

ERIC Educational Resources Information Center

Watts, Mike

2015-01-01

Many household gardeners accumulate considerable knowledge of plant biology through a range of informal learning sources. This knowledge seldom relates to school biology and is driven by interest, keen motivation and what is termed here "vital relevance." A small opportunity sample of 12 gardeners (6 M, 6 F) is interviewed in terms of…

A Knowledge Base for Teaching Biology Situated in the Context of Genetic Testing

ERIC Educational Resources Information Center

van der Zande, Paul; Waarlo, Arend Jan; Brekelmans, Mieke; Akkerman, Sanne F.; Vermunt, Jan D.

2011-01-01

Recent developments in the field of genomics will impact the daily practice of biology teachers who teach genetics in secondary education. This study reports on the first results of a research project aimed at enhancing biology teacher knowledge for teaching genetics in the context of genetic testing. The increasing body of scientific knowledge…

Verbal Final Exam in Introductory Biology Yields Gains in Student Content Knowledge and Longitudinal Performance

ERIC Educational Resources Information Center

Luckie, Douglas B.; Rivkin, Aaron M.; Aubry, Jacob R.; Marengo, Benjamin J.; Creech, Leah R.; Sweeder, Ryan D.

2013-01-01

We studied gains in student learning over eight semesters in which an introductory biology course curriculum was changed to include optional verbal final exams (VFs). Students could opt to demonstrate their mastery of course material via structured oral exams with the professor. In a quantitative assessment of cell biology content knowledge,…

Representations of the Nature of Scientific Knowledge in Turkish Biology Textbooks

ERIC Educational Resources Information Center

Irez, Serhat

2016-01-01

Considering the impact of textbooks on learning, this study set out to assess representations of the nature of scientific knowledge in Turkish 9th grade biology textbooks. To this end, the ten most commonly used 9th grade biology textbooks were analyzed. A qualitative research approach was utilized and the textbooks were analyzed using…

Student Perceived and Determined Knowledge of Biology Concepts in an Upper-Level Biology Course

PubMed Central

Montplaisir, Lisa

2014-01-01

Students who lack metacognitive skills can struggle with the learning process. To be effective learners, students should recognize what they know and what they do not know. This study examines the relationship between students’ perception of their knowledge and determined knowledge in an upper-level biology course utilizing a pre/posttest approach. Significant differences in students’ perception of their knowledge and their determined knowledge exist at the beginning (pretest) and end (posttest) of the course. Alignment between student perception and determined knowledge was significantly more accurate on the posttest compared with the pretest. Students whose determined knowledge was in the upper quartile had significantly better alignment between their perception and determined knowledge on the pre- and posttest than students in the lower quartile. No difference exists between how students perceived their knowledge between upper- and lower-quartile students. There was a significant difference in alignment of perception and determined knowledge between males and females on the posttest, with females being more accurate in their perception of knowledge. This study provides evidence of discrepancies that exist between what students perceive they know and what they actually know. PMID:26086662

Women care about local knowledge, experiences from ethnomycology

PubMed Central

2012-01-01

Gender is one of the main variables that influence the distribution of local knowledge. We carried out a literature review concerning local mycological knowledge, paying special attention to data concerning women’s knowledge and comparative gender data. We found that unique features of local mycological knowledge allow people to successfully manage mushrooms. Women are involved in every stage of mushroom utilization from collection to processing and marketing. Local mycological knowledge includes the use mushrooms as food, medicine, and recreational objects as well as an aid to seasonal household economies. In many regions of the world, women are often the main mushroom collectors and possess a vast knowledge about mushroom taxonomy, biology, and ecology. Local experts play a vital role in the transmission of local mycological knowledge. Women participate in the diffusion of this knowledge as well as in its enrichment through innovation. Female mushroom collectors appreciate their mycological knowledge and pursue strategies and organization to reproduce it in their communities. Women mushroom gatherers are conscious of their knowledge, value its contribution in their subsistence systems, and proudly incorporate it in their cultural identity. PMID:22809491

Women care about local knowledge, experiences from ethnomycology.

PubMed

Garibay-Orijel, Roberto; Ramírez-Terrazo, Amaranta; Ordaz-Velázquez, Marisa

2012-07-18

Gender is one of the main variables that influence the distribution of local knowledge. We carried out a literature review concerning local mycological knowledge, paying special attention to data concerning women's knowledge and comparative gender data. We found that unique features of local mycological knowledge allow people to successfully manage mushrooms. Women are involved in every stage of mushroom utilization from collection to processing and marketing. Local mycological knowledge includes the use mushrooms as food, medicine, and recreational objects as well as an aid to seasonal household economies. In many regions of the world, women are often the main mushroom collectors and possess a vast knowledge about mushroom taxonomy, biology, and ecology. Local experts play a vital role in the transmission of local mycological knowledge. Women participate in the diffusion of this knowledge as well as in its enrichment through innovation. Female mushroom collectors appreciate their mycological knowledge and pursue strategies and organization to reproduce it in their communities. Women mushroom gatherers are conscious of their knowledge, value its contribution in their subsistence systems, and proudly incorporate it in their cultural identity.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

RNA interference: from biology to drugs and therapeutics.

PubMed

Appasani, Krishnarao

2004-07-01

RNA interference (RNAi) is a newly discovered and popular technology platform among researchers not only in the fields of RNA biology and molecular cell biology. It has created excitement in clinical sciences such as oncology, neurology, endocrinology, infectious diseases and drug discovery. There is an urgent need to educate and connect academic and industry researchers for the purpose of knowledge transfer. Thus, GeneExpression Systems of Waltham organized its Second International Conference in Waltham City (May 2-4, 2004, MA, USA) on the theme of 'RNA interference: From Biology to Drugs & Therapeutics.' About 200 participants and 32 speakers attended this two and half-day event which was arranged in six scientific and three technology sessions and ended with a panel discussion. This report covers a few representative talks from academia, biotech and the drug industry.

"The evil virus cell": Students‘ knowledge and beliefs about viruses

PubMed Central

Enzinger, Sonja M.; Fink, Andreas

2017-01-01

Education about virus biology at school is of pivotal interest to raise public awareness concerning means of disease transmission and, thus, methods to prevent infection, and to reduce unnecessary antibiotic treatment due to patient pressure on physicians in case of viral diseases such as influenza. This study aimed at making visible the knowledge of Austrian high school and university students with respect to virus biology, virus structure and health-education issues. The data presented here stem from comprehensive questionnaire analyses, including the task to draw a virus, from a cross-sectional study with 133 grade 7 and 199 grade 10 high school students, and 133 first-year biology and 181 first-year non-biology university students. Analyses were performed both quantitatively and qualitatively. ANOVA revealed a highly significant group effect for total knowledge relating to virus biology and health issues (F(3, 642) = 44.17, p < 0.01, η2p = 0.17). Specific post-hoc tests by means of the Tukey test showed significant differences between all groups (p < .01) with the exception of 1st year non-biology students and grade 10 high school students. Students enrolled in university-level biology outperformed all other groups, even though they had not yet encountered this topic at their courses; part of this phenomenon might be due to their affinity for learning about biological topics. However, even many first-year biology students had a high number of severe misconceptions, e.g., defining a virus as a pro- or eukaryotic cell, or falsely naming malaria as a viral disease. Since there was no significant difference in virus-related knowledge between high schools, virus biology seems to have been taught similarly among the tested schools. However, the majority of participants stated that the virus-related knowledge they had acquired at school was not sufficient. Based on the results presented here we urgently suggest improving and intensifying teaching this topic at school, since virus-related knowledge was by far too fragmentary among many participants. Such lack of health-relevant knowledge may contribute to pressure on physicians by patients to unnecessarily prescribe antibiotics, and possibly lead to potentially dangerous neglect concerning vaccination. The effectiveness of newly developed virus-related teaching units and material could be tested with the instrument used here. PMID:28350815

"The evil virus cell": Students' knowledge and beliefs about viruses.

PubMed

Simon, Uwe K; Enzinger, Sonja M; Fink, Andreas

2017-01-01

Education about virus biology at school is of pivotal interest to raise public awareness concerning means of disease transmission and, thus, methods to prevent infection, and to reduce unnecessary antibiotic treatment due to patient pressure on physicians in case of viral diseases such as influenza. This study aimed at making visible the knowledge of Austrian high school and university students with respect to virus biology, virus structure and health-education issues. The data presented here stem from comprehensive questionnaire analyses, including the task to draw a virus, from a cross-sectional study with 133 grade 7 and 199 grade 10 high school students, and 133 first-year biology and 181 first-year non-biology university students. Analyses were performed both quantitatively and qualitatively. ANOVA revealed a highly significant group effect for total knowledge relating to virus biology and health issues (F(3, 642) = 44.17, p < 0.01, η2p = 0.17). Specific post-hoc tests by means of the Tukey test showed significant differences between all groups (p < .01) with the exception of 1st year non-biology students and grade 10 high school students. Students enrolled in university-level biology outperformed all other groups, even though they had not yet encountered this topic at their courses; part of this phenomenon might be due to their affinity for learning about biological topics. However, even many first-year biology students had a high number of severe misconceptions, e.g., defining a virus as a pro- or eukaryotic cell, or falsely naming malaria as a viral disease. Since there was no significant difference in virus-related knowledge between high schools, virus biology seems to have been taught similarly among the tested schools. However, the majority of participants stated that the virus-related knowledge they had acquired at school was not sufficient. Based on the results presented here we urgently suggest improving and intensifying teaching this topic at school, since virus-related knowledge was by far too fragmentary among many participants. Such lack of health-relevant knowledge may contribute to pressure on physicians by patients to unnecessarily prescribe antibiotics, and possibly lead to potentially dangerous neglect concerning vaccination. The effectiveness of newly developed virus-related teaching units and material could be tested with the instrument used here.

Biomarkers for Uranium Risk Assessment for the Development of the CURE (Concerted Uranium Research in Europe) Molecular Epidemiological Protocol.

PubMed

Guéguen, Yann; Roy, Laurence; Hornhardt, Sabine; Badie, Christophe; Hall, Janet; Baatout, Sarah; Pernot, Eileen; Tomasek, Ladislav; Laurent, Olivier; Ebrahimian, Teni; Ibanez, Chrystelle; Grison, Stephane; Kabacik, Sylwia; Laurier, Dominique; Gomolka, Maria

2017-01-01

Despite substantial experimental and epidemiological research, there is limited knowledge of the uranium-induce health effects after chronic low-dose exposures in humans. Biological markers can objectively characterize pathological processes or environmental responses to uranium and confounding agents. The integration of such biological markers into a molecular epidemiological study would be a useful approach to improve and refine estimations of uranium-induced health risks. To initiate such a study, Concerted Uranium Research in Europe (CURE) was established, and involves biologists, epidemiologists and dosimetrists. The aims of the biological work package of CURE were: 1. To identify biomarkers and biological specimens relevant to uranium exposure; 2. To define standard operating procedures (SOPs); and 3. To set up a common protocol (logistic, questionnaire, ethical aspects) to perform a large-scale molecular epidemiologic study in uranium-exposed cohorts. An intensive literature review was performed and led to the identification of biomarkers related to: 1. retention organs (lungs, kidneys and bone); 2. other systems/organs with suspected effects (cardiovascular system, central nervous system and lympho-hematopoietic system); 3. target molecules (DNA damage, genomic instability); and 4. high-throughput methods for the identification of new biomarkers. To obtain high-quality biological materials, SOPs were established for the sampling and storage of different biospecimens. A questionnaire was developed to assess potential confounding factors. The proposed strategy can be adapted to other internal exposures and should improve the characterization of the biological and health effects that are relevant for risk assessment.

NASA's GeneLab Phase II: Federated Search and Data Discovery

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Costes, Sylvain V.; Tran, Peter B.

2017-01-01

GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

Advances in Omics and Bioinformatics Tools for Systems Analyses of Plant Functions

PubMed Central

Mochida, Keiichi; Shinozaki, Kazuo

2011-01-01

Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances. PMID:22156726

NASAs GeneLab Phase II: Federated Search and Data Discovery

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Costes, Sylvain; Tran, Peter

2017-01-01

GeneLab is currently being developed by NASA to accelerate open science biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics (omics) data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

Genomics, "Discovery Science," Systems Biology, and Causal Explanation: What Really Works?

PubMed

Davidson, Eric H

2015-01-01

Diverse and non-coherent sets of epistemological principles currently inform research in the general area of functional genomics. Here, from the personal point of view of a scientist with over half a century of immersion in hypothesis driven scientific discovery, I compare and deconstruct the ideological bases of prominent recent alternatives, such as "discovery science," some productions of the ENCODE project, and aspects of large data set systems biology. The outputs of these types of scientific enterprise qualitatively reflect their radical definitions of scientific knowledge, and of its logical requirements. Their properties emerge in high relief when contrasted (as an example) to a recent, system-wide, predictive analysis of a developmental regulatory apparatus that was instead based directly on hypothesis-driven experimental tests of mechanism.

Teaching statistics in biology: using inquiry-based learning to strengthen understanding of statistical analysis in biology laboratory courses.

PubMed

Metz, Anneke M

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.

Behavior of nanoceria in biologically-relevant environments

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

Kumar, Amit; Das, Soumen; Munusamy, Prabhakaran

2014-09-08

Cerium oxide nanoparticles (CNPs) have gained a considerable attention in biological research due to their anti-oxidant like behaviour and regenerative nature. The current literature on CNPs reports many successful attempts on harnessing the beneficial therapeutic properties in biology. However studies have also shown toxicity effect with some types of CNPs. This review discusses issues associated with the behaviours of CNPs in biological systems and identifies key knowledge gaps. We explore how salient physicochemical properties (size, surface chemistry, surface stabilizers) contribute to the potential positive and negative aspects of nanoceria in biological systems. Based on variations of results reported in themore » literature, important issues need to be addressed. Are we really studying the same particles with slight variations in size and physicochemical properties or do the particles being examined have fundamentally different behaviours? Are the variations observed in the result of differences in the initial properties of the particles or the results of downstream effects that emerge as the particles are prepared for specific studies and they interact with biological or other environmental moieties? How should particles be appropriately prepared for relevant environmental/toxicology/safety studies? It is useful to recognize that nanoparticles encompass some of the same complexities and variability associated with biological components« less

Research Frontiers in Bioinspired Energy: Molecular-Level Learning from Natural Systems: A Workshop

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

Zolandz, Dorothy

An interactive, multidisciplinary, public workshop, organized by a group of experts in biochemistry, biophysics, chemical and biomolecular engineering, chemistry, microbial metabolism, and protein structure and function, was held on January 6-7, 2011 in Washington, DC. Fundamental insights into the biological energy capture, storage, and transformation processes provided by speakers was featured in this workshop which included topics such as microbes living in extreme environments such as hydrothermal vents or caustic soda lakes (extremophiles) provided a fascinating basis for discussing the exploration and development of new energy systems. Breakout sessions and extended discussions among the multidisciplinary groups of participants in themore » workshop fostered information sharing and possible collaborations on future bioinspired research. Printed and web-based materials that summarize the committee's assessment of what transpired at the workshop were prepared to advance further understanding of fundamental chemical properties of biological systems within and between the disciplines. In addition, webbased materials (including two animated videos) were developed to make the workshop content more accessible to a broad audience of students and researchers working across disciplinary boundaries. Key workshop discussion topics included: Exploring and identifying novel organisms; Identifying patterns and conserved biological structures in nature; Exploring and identifying fundamental properties and mechanisms of known biological systems; Supporting current, and creating new, opportunities for interdisciplinary education, training, and outreach; and Applying knowledge from biology to create new devices and sustainable technology.« less

Protein bio-corona: critical issue in immune nanotoxicology.

PubMed

Neagu, Monica; Piperigkou, Zoi; Karamanou, Konstantina; Engin, Ayse Basak; Docea, Anca Oana; Constantin, Carolina; Negrei, Carolina; Nikitovic, Dragana; Tsatsakis, Aristidis

2017-03-01

With the expansion of the nanomedicine field, the knowledge focusing on the behavior of nanoparticles in the biological milieu has rapidly escalated. Upon introduction to a complex biological system, nanomaterials dynamically interact with all the encountered biomolecules and form the protein "bio-corona." The decoration with these surface biomolecules endows nanoparticles with new properties. The present review will address updates of the protein bio-corona characteristics as influenced by nanoparticle's physicochemical properties and by the particularities of the encountered biological milieu. Undeniably, bio-corona generation influences the efficacy of the nanodrug and guides the actions of innate and adaptive immunity. Exploiting the dynamic process of protein bio-corona development in combination with the new engineered horizons of drugs linked to nanoparticles could lead to innovative functional nanotherapies. Therefore, bio-medical nanotechnologies should focus on the interactions of nanoparticles with the immune system for both safety and efficacy reasons.

At the Edge of Translation – Materials to Program Cells for Directed Differentiation

PubMed Central

Arany, Praveen R; Mooney, David J

2010-01-01

The rapid advancement in basic biology knowledge, especially in the stem cell field, has created new opportunities to develop biomaterials capable of orchestrating the behavior of transplanted and host cells. Based on our current understanding of cellular differentiation, a conceptual framework for the use of materials to program cells in situ is presented, namely a domino versus a switchboard model, to highlight the use of single versus multiple cues in a controlled manner to modulate biological processes. Further, specific design principles of material systems to present soluble and insoluble cues that are capable of recruiting, programming and deploying host cells for various applications are presented. The evolution of biomaterials from simple inert substances used to fill defects, to the recent development of sophisticated material systems capable of programming cells in situ is providing a platform to translate our understanding of basic biological mechanisms to clinical care. PMID:20860763

Student Understanding of Water and Water Resources: A Review of the Literature.

ERIC Educational Resources Information Center

Brody, Michael J.

This paper reviews the educational research related to student understanding of water and water resources. The literature is drawn primarily from science and environmental education literature and is divided into student knowledge of: physical and chemical properties, biology, earth systems and water resources. The majority of work has been in the…

How trees influence the hydrological cycle in forest ecosystems

Treesearch

Barbara J. Bond; Frederick C. Meinzer; J. Renee Brooks

2007-01-01

Ultimately, the quest of ecohydrology (or hydroecology) is to apply fundamental knowledge from hydrology, ecology, atmospheric science, and related disciplines to solve real world problems involving biological systems and hydrologic cycles. Achieving this goal requires sharing information across disciplines, and this chapter is structured toward that end. Our aim is to...

Lipopolysaccharide-induced early response genes in bovine peripheral blood mononuclear cells implicate GLG1/E-selectin as a key ligand–receptor interaction

USDA-ARS?s Scientific Manuscript database

This study uses a systems biology approach, integrating global gene expression information and knowledge of the regulatory events in cells to identify transcription networks controlling peripheral blood mononuclear cells’ (PBMCs) immune response to lipopolysaccharide (LPS) and to identify the molecu...

The Tentative Nature of Scientific Knowledge: Why Should We Teach More about Diabetes Mellitus?

ERIC Educational Resources Information Center

Biermann, Carol A.

1993-01-01

Almost 70 years of scientific research leaves many unanswered questions concerning diabetes mellitus. This disease can be viewed as an illustration of the complexity of biological systems. Textbooks stress normal rather than abnormal physiology and rarely share the difficulties encountered in understanding those abnormal conditions (PR)

Synthetic biology era: Improving antibiotic's world.

PubMed

Guzmán-Trampe, Silvia; Ceapa, Corina D; Manzo-Ruiz, Monserrat; Sánchez, Sergio

2017-06-15

The emergence of antibiotic-resistant pathogen microorganisms is problematic in the context of the current spectrum of available medication. The poor specificity and the high toxicity of some available molecules have made imperative the search for new strategies to improve the specificity and to pursue the discovery of novel compounds with increased bioactivity. Using living cells as platforms, synthetic biology has counteracted this problem by offering novel pathways to create synthetic systems with improved and desired functions. Among many other biotechnological approaches, the advances in synthetic biology have made it possible to design and construct novel biological systems in order to look for new drugs with increased bioactivity. Advancements have also been made in the redesigning of RNA and DNA molecules in order to engineer antibiotic clusters for antibiotic overexpression. As for the production of these antibacterial compounds, yeasts and filamentous fungi as well as gene therapy are utilized to enhance protein solubility. Specific delivery is achieved by creating chimeras using plant genes into bacterial hosts. Some of these synthetic systems are currently in clinical trials, proving the proficiency of synthetic biology in terms of both pharmacological activities as well as an increase in the biosafety of treatments. It is possible that we may just be seeing the tip of the iceberg, and synthetic biology applications will overpass expectations beyond our present knowledge. Copyright © 2017. Published by Elsevier Inc.

Multidisciplinary Russian biomedical research in space

NASA Astrophysics Data System (ADS)

Orlov, O. I.; Sychev, V. N.; Samarin, G. I.; Ilyin, E. A.; Belakovskiy, M. S.; Kussmaul, A. R.

2014-08-01

Research activities on a comprehensive multidisciplinary program are vital for enhancement of the system of crew's medical care, environmental health and hygiene in space missions. The primary goal of the program must be identification of patterns, intensity and dynamics of structural and functional shifts in organism induced by an aggregate of spaceflight factors including microgravity, isolation, artificial environment, space radiation, etc. Also, the program must pursue differential assessment of emerging deviations from the standpoint of adequacy to the spaceflight conditions and prospects of returning to Earth and guide the development of principles, methods and techniques necessary to maintain health and working capacity of humans during short- and long-duration missions and on return to Earth. Over 50 years, since 1963, the IBMP researchers apply systemic and innovational approaches to fundamental and exploratory studies in the fields of medical sciences, radiation biology, engineering science, biotechnology, etc. with participation of various biological specimens and human volunteers. Investigations aboard manned spacecrafts and biological satellites as well as in ground-based laboratories further enhancement of the medical care system for crews on orbital and remote space missions; they give insight into the fundamental problems of gravitational physiology and biology, psychophysiology, radiation biology, and contribute thereby to the development of knowledge, methods and technologies, as well as medical and scientific equipment.

The role of stress and beta-adrenergic system in melanoma: current knowledge and possible therapeutic options.

PubMed

Colucci, Roberta; Moretti, Silvia

2016-05-01

The aim of the present review was to discuss recent findings on the role of beta-adrenergic system in melanoma, in order to provide information on the biological responses elicited by its activation and its potential application for melanoma treatment. A literature search was performed, and evidences regarding the involvement of stress and beta-adrenergic system in cancer and melanoma were found and discussed. Our search pointed out that beta-adrenergic system is a key regulator of important biological processes involved in the onset and progression of some solid tumors. In the last decade, functional beta-adrenoceptors have been also identified on melanoma cells, as well as on their microenvironment cells. Similarly to other common cancers too, the activation of such adrenoceptors by catecholamines, usually released under stress conditions, has been found to trigger pro-tumorigenic pathways contributing to cell proliferation and motility, immune system regulation, apoptosis, epithelial-mesenchymal transition, invasion and neoangiogenesis. The biological evidences we found clarify and sustain the clinical evidences reporting the involvement of chronic stress in melanoma onset and progression. In such scenario, it is conceivable that a therapeutic approach targeting beta-adrenergic system could constitute a novel and promising strategy for melanoma treatment.

Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET

PubMed Central

Androsova, Ganna; del Sol, Antonio

2015-01-01

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states. PMID:26058016

Discovering a vaccine against neosporosis using computers: is it feasible?

PubMed

Goodswen, Stephen J; Kennedy, Paul J; Ellis, John T

2014-08-01

A vaccine is urgently needed to prevent cattle neosporosis. This infectious disease is caused by the parasite Neospora caninum, a complex biological system with multifaceted life cycles. An in silico vaccine discovery approach attempts to transform digital abstractions of this system into adequate knowledge to predict candidates. Researchers need current information to implement such an approach, such as understanding evasion mechanisms of the immune system, type of immune response to elicit, availability of data and prediction programs, and statistical models to analyze predictions. Taken together, an in silico approach involves assembly of an intricate jigsaw of interdisciplinary and interdependent knowledge. In this review, we focus on the approach influencing vaccine development against Neospora caninum, which can be generalized to other pathogenic apicomplexans. Copyright © 2014 Elsevier Ltd. All rights reserved.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Casual Games and Casual Learning About Human Biological Systems

NASA Astrophysics Data System (ADS)

Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia

2016-02-01

Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human biological systems. Two hundred and forty-two children were given pretests at a Museum and posttests at home after playing either a treatment or control game. Also, 41 children were interviewed to explore deeper meanings behind the test results. Results show modest improvement in scientific attitudes, ability to identify human biological systems and in the children's ability to describe how those systems work together in real-world scenarios. Interviews reveal that children drew upon their prior school learning as they played the game. Also, on the surface they perceived the game as mainly entertainment but were easily able to discern learning outcomes when prompted. Implications for the design of casual games and how they can be used to enhance transfer of knowledge from the classroom to everyday life are discussed.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

Voting systems for environmental decisions.

PubMed

Burgman, Mark A; Regan, Helen M; Maguire, Lynn A; Colyvan, Mark; Justus, James; Martin, Tara G; Rothley, Kris

2014-04-01

Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group. © 2014 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of the Society for Conservation Biology.

Effect of Integrating a Sportfishing Curriculum into a Camp Program on the Knowledge, Awareness, and Attitudes of Participating Youth.

ERIC Educational Resources Information Center

Koupal, Keith; Krasny, Marianne

2003-01-01

The effect of a 1-week sportfishing and environmental curriculum on participants' (aged 9-14) knowledge of fishing and biology/ecology, awareness of ethical behavior, and attitudes was assessed with 127 completed pre-/post-surveys. The program developed fishing and biology/ecology knowledge, but did not affect ethical behavior awareness or…

The Relationships Between Epistemic Beliefs in Biology and Approaches to Learning Biology Among Biology-Major University Students in Taiwan

NASA Astrophysics Data System (ADS)

Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung

2012-12-01

The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and large, it was found that the students reflected "mixed" motives in biology learning, while those who had more sophisticated epistemic beliefs tended to employ deep strategies. In addition, the results of paired t tests revealed that the female students were more likely to possess beliefs about biological knowledge residing in external authorities, to believe in a right answer, and to utilize rote learning as a learning strategy. Moreover, compared to juniors and seniors, freshmen and sophomores tended to hold less mature views on all factors of epistemic beliefs regarding biology. Another comparison indicated that theoretical biology students (e.g. students majoring in the Department of Biology) tended to have more mature beliefs in learning biology and more advanced strategies for biology learning than those students studying applied biology (e.g. in the Department of Biotechnology). Stepwise regression analysis, in general, indicated that students who valued the role of experiments and justify epistemic assumptions and knowledge claims based on evidence were more oriented towards having mixed motives and utilizing deep strategies to learn biology. In contrast, students who believed in the certainty of biological knowledge were more likely to adopt rote learning strategies and to aim to qualify in biology.

Weaving Traditional Ecological Knowledge into Biological Education: A Call to Action.

ERIC Educational Resources Information Center

Kimmerer, Robin Wall

2002-01-01

Traditional ecological knowledge has value not only for the wealth of biological information it contains but also for the cultural framework of respect, reciprocity, and responsibility in which it is embedded. (Contains 48 references.) (DDR)

Socioemotional, Personality, and Biological Development: Illustrations from a Multilevel Developmental Psychopathology Perspective on Child Maltreatment.

PubMed

Cicchetti, Dante

2016-01-01

Developmental theories can be affirmed, challenged, and augmented by incorporating knowledge about atypical ontogenesis. Investigations of the biological, socioemotional, and personality development in individuals with high-risk conditions and psychopathological disorders can provide an entrée into the study of system organization, disorganization, and reorganization. This article examines child maltreatment to illustrate the benefit that can be derived from the study of individuals subjected to nonnormative caregiving experiences. Relative to an average expectable environment, which consists of a species-specific range of environmental conditions that support adaptive development among genetically normal individuals, maltreating families fail to provide many of the experiences that are required for normal development. Principles gleaned from the field of developmental psychopathology provide a framework for understanding multilevel functioning in normality and pathology. Knowledge of normative developmental processes provides the impetus to design and implement randomized control trial (RCT) interventions that can promote resilient functioning in maltreated children.

A protocol for generating a high-quality genome-scale metabolic reconstruction.

PubMed

Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

A protocol for generating a high-quality genome-scale metabolic reconstruction

PubMed Central

Thiele, Ines; Palsson, Bernhard Ø.

2011-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have developed over the past 10 years. These reconstructions represent structured knowledge-bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates myriad computational biological studies including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics, and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge-bases. Here, we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction as well as common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process. PMID:20057383

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

BrainSnail: A dynamic information display system for the Sciences

PubMed Central

Telefont, Martin; Asaithambi, Asai

2009-01-01

Scientific reference management has become crucial in rapidly expanding fields of biology. Many of the reference management systems currently employed are reference centric and not object/process focused. BrainSnail is a reference management/knowledge representation application that tries to bridge disconnect between subject and reference in the fields of neuropharmacology, neuroanatomy and neurophysiology. BrainSnail has been developed with considering both individual researcher and research group efforts. PMID:19293992

What's the point of the type III secretion system needle?

PubMed Central

Blocker, Ariel J.; Deane, Janet E.; Veenendaal, Andreas K. J.; Roversi, Pietro; Hodgkinson, Julie L.; Johnson, Steven; Lea, Susan M.

2008-01-01

Recent work by several groups has significantly expanded our knowledge of the structure, regulation of assembly, and function of components of the extracellular portion of the type III secretion system (T3SS) of Gram-negative bacteria. This perspective presents a structure-informed analysis of functional data and discusses three nonmutually exclusive models of how a key aspect of T3SS biology, the sensing of host cells, may be performed. PMID:18458349

Combating desertification: building on traditional knowledge systems of the Thar Desert communities.

PubMed

Gaur, Mahesh K; Gaur, Hemlata

2004-12-01

The Thar Desert of western India is known for its rich and ancient culture system and traditions. The communities have long been part of the Thar Desert ecosystem and have evolved specific strategies to live in harmony with its hostile environment. This culture has provided several miracle plants of immense food and medicinal value to modern civilisation. The ancient rural livelihood knowledge system reflects time-tested techno-scientific knowledge with a proven track record of sustainability, especially during natural hazards like drought and famines. In addition, several of the traditional skills of local communities in arts and crafts, music and instruments have made modern man aware of the art and techniques of sustainably utilising local biological resources and preserving their biodiversity along with using waste products of the forests, without harming the desert ecosystem. Traditional cultural and socio-religious values are fast dwindling under the impact of materialistic approach, industrialisation and development. This paper endeavours to illustrate the need to assist and propagate indigenous rural livelihood systems rather than mindlessly replace or abandon them as a result of state bureaucracies.

Achilles and the tortoise: Some caveats to mathematical modeling in biology.

PubMed

Gilbert, Scott F

2018-01-31

Mathematical modeling has recently become a much-lauded enterprise, and many funding agencies seek to prioritize this endeavor. However, there are certain dangers associated with mathematical modeling, and knowledge of these pitfalls should also be part of a biologist's training in this set of techniques. (1) Mathematical models are limited by known science; (2) Mathematical models can tell what can happen, but not what did happen; (3) A model does not have to conform to reality, even if it is logically consistent; (4) Models abstract from reality, and sometimes what they eliminate is critically important; (5) Mathematics can present a Platonic ideal to which biologically organized matter strives, rather than a trial-and-error bumbling through evolutionary processes. This "Unity of Science" approach, which sees biology as the lowest physical science and mathematics as the highest science, is part of a Western belief system, often called the Great Chain of Being (or Scala Natura), that sees knowledge emerge as one passes from biology to chemistry to physics to mathematics, in an ascending progression of reason being purification from matter. This is also an informal model for the emergence of new life. There are now other informal models for integrating development and evolution, but each has its limitations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Creativity, brain, and art: biological and neurological considerations.

PubMed

Zaidel, Dahlia W

2014-01-01

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity's neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The verb "to create" has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson's), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals.

Creativity, brain, and art: biological and neurological considerations

PubMed Central

Zaidel, Dahlia W.

2014-01-01

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity’s neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The verb “to create” has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson’s), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals. PMID:24917807

Exploring Biology Teachers' Pedagogical Content Knowledge in the Teaching of Genetics in Swaziland Science Classrooms

NASA Astrophysics Data System (ADS)

Mthethwa-Kunene, Eunice; Oke Onwu, Gilbert; de Villiers, Rian

2015-05-01

This study explored the pedagogical content knowledge (PCK) and its development of four experienced biology teachers in the context of teaching school genetics. PCK was defined in terms of teacher content knowledge, pedagogical knowledge and knowledge of students' preconceptions and learning difficulties. Data sources of teacher knowledge base included teacher-constructed concept maps, pre- and post-lesson teacher interviews, video-recorded genetics lessons, post-lesson teacher questionnaire and document analysis of teacher's reflective journals and students' work samples. The results showed that the teachers' individual PCK profiles consisted predominantly of declarative and procedural content knowledge in teaching basic genetics concepts. Conditional knowledge, which is a type of meta-knowledge for blending together declarative and procedural knowledge, was also demonstrated by some teachers. Furthermore, the teachers used topic-specific instructional strategies such as context-based teaching, illustrations, peer teaching, and analogies in diverse forms but failed to use physical models and individual or group student experimental activities to assist students' internalization of the concepts. The finding that all four teachers lacked knowledge of students' genetics-related preconceptions was equally significant. Formal university education, school context, journal reflection and professional development programmes were considered as contributing to the teachers' continuing PCK development. Implications of the findings for biology teacher education are briefly discussed.

Structure, Biology, and Therapeutic Application of Toxin-Antitoxin Systems in Pathogenic Bacteria.

PubMed

Lee, Ki-Young; Lee, Bong-Jin

2016-10-22

Bacterial toxin-antitoxin (TA) systems have received increasing attention for their diverse identities, structures, and functional implications in cell cycle arrest and survival against environmental stresses such as nutrient deficiency, antibiotic treatments, and immune system attacks. In this review, we describe the biological functions and the auto-regulatory mechanisms of six different types of TA systems, among which the type II TA system has been most extensively studied. The functions of type II toxins include mRNA/tRNA cleavage, gyrase/ribosome poison, and protein phosphorylation, which can be neutralized by their cognate antitoxins. We mainly explore the similar but divergent structures of type II TA proteins from 12 important pathogenic bacteria, including various aspects of protein-protein interactions. Accumulating knowledge about the structure-function correlation of TA systems from pathogenic bacteria has facilitated a novel strategy to develop antibiotic drugs that target specific pathogens. These molecules could increase the intrinsic activity of the toxin by artificially interfering with the intermolecular network of the TA systems.

Structure, Biology, and Therapeutic Application of Toxin–Antitoxin Systems in Pathogenic Bacteria

PubMed Central

Lee, Ki-Young; Lee, Bong-Jin

2016-01-01

Bacterial toxin–antitoxin (TA) systems have received increasing attention for their diverse identities, structures, and functional implications in cell cycle arrest and survival against environmental stresses such as nutrient deficiency, antibiotic treatments, and immune system attacks. In this review, we describe the biological functions and the auto-regulatory mechanisms of six different types of TA systems, among which the type II TA system has been most extensively studied. The functions of type II toxins include mRNA/tRNA cleavage, gyrase/ribosome poison, and protein phosphorylation, which can be neutralized by their cognate antitoxins. We mainly explore the similar but divergent structures of type II TA proteins from 12 important pathogenic bacteria, including various aspects of protein–protein interactions. Accumulating knowledge about the structure–function correlation of TA systems from pathogenic bacteria has facilitated a novel strategy to develop antibiotic drugs that target specific pathogens. These molecules could increase the intrinsic activity of the toxin by artificially interfering with the intermolecular network of the TA systems. PMID:27782085

Prior knowledge-based approach for associating ...

EPA Pesticide Factsheets

Evaluating the potential human health and/or ecological risks associated with exposures to complex chemical mixtures in the ambient environment is one of the central challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and bio-effects data to evaluate risks associated with chemicals present in the environment. We used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near two wastewater treatment plants. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data was also mapped to the assembly models to statistically evaluate the likelihood of a chemical contributing to the observed biological responses. The prior knowledge approach was able reasonably hypothesize the biological impacts at one site but not the other. Chemicals most likely contributing to the observed biological responses were identified at each location. Despite limitations to the approach, knowledge assembly models have strong potential for associating chemical occurrence with potential biological effects and providing a foundation for hypothesis generation to guide research and/or monitoring efforts relat

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

Global Change: A Biogeochemical Perspective

NASA Technical Reports Server (NTRS)

Mcelroy, M.

1983-01-01

A research program that is designed to enhance our understanding of the Earth as the support system for life is described. The program change, both natural and anthropogenic, that might affect the habitability of the planet on a time scale roughly equal to that of a human life is studied. On this time scale the atmosphere, biosphere, and upper ocean are treated as a single coupled system. The need for understanding the processes affecting the distribution of essential nutrients--carbon, nitrogen, phosphorous, sulfur, and water--within this coupled system is examined. The importance of subtle interactions among chemical, biological, and physical effects is emphasized. The specific objectives are to define the present state of the planetary life-support system; to ellucidate the underlying physical, chemical, and biological controls; and to provide the body of knowledge required to assess changes that might impact the future habitability of the Earth.

Endocannabinoids: Effectors of glucocorticoid signaling.

PubMed

Balsevich, Georgia; Petrie, Gavin N; Hill, Matthew N

2017-10-01

For decades, there has been speculation regarding the interaction of cannabinoids with glucocorticoid systems. Given the functional redundancy between many of the physiological effects of glucocorticoids and cannabinoids, it was originally speculated that the biological mechanisms of cannabinoids were mediated by direct interactions with glucocorticoid systems. With the discovery of the endocannabinoid system, additional research demonstrated that it was actually the opposite; glucocorticoids recruit endocannabinoid signaling, and that the engagement of endocannabinoid signaling mediated many of the neurobiological and physiological effects of glucocorticoids. With the development of advances in pharmacology and genetics, significant advances in this area have been made, and it is now clear that functional interactions between these systems are critical for a wide array of physiological processes. The current review acts a comprehensive summary of the contemporary state of knowledge regarding the biological interactions between glucocorticoids and endocannabinoids, and their potential role in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Structuring and extracting knowledge for the support of hypothesis generation in molecular biology

PubMed Central

Roos, Marco; Marshall, M Scott; Gibson, Andrew P; Schuemie, Martijn; Meij, Edgar; Katrenko, Sophia; van Hage, Willem Robert; Krommydas, Konstantinos; Adriaans, Pieter W

2009-01-01

Background Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation. PMID:19796406

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

PubMed

Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

2016-12-01

The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

Teaching Statistics in Biology: Using Inquiry-based Learning to Strengthen Understanding of Statistical Analysis in Biology Laboratory Courses

PubMed Central

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754

A Model of Biological Attacks on a Realistic Population

NASA Astrophysics Data System (ADS)

Carley, Kathleen M.; Fridsma, Douglas; Casman, Elizabeth; Altman, Neal; Chen, Li-Chiou; Kaminsky, Boris; Nave, Demian; Yahja, Alex

The capability to assess the impacts of large-scale biological attacks and the efficacy of containment policies is critical and requires knowledge-intensive reasoning about social response and disease transmission within a complex social system. There is a close linkage among social networks, transportation networks, disease spread, and early detection. Spatial dimensions related to public gathering places such as hospitals, nursing homes, and restaurants, can play a major role in epidemics [Klovdahl et. al. 2001]. Like natural epidemics, bioterrorist attacks unfold within spatially defined, complex social systems, and the societal and networked response can have profound effects on their outcome. This paper focuses on bioterrorist attacks, but the model has been applied to emergent and familiar diseases as well.

PathText: a text mining integrator for biological pathway visualizations

PubMed Central

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

2010-01-01

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

Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome.

PubMed

Pavlovic, Dragana M; Vértes, Petra E; Bullmore, Edward T; Schafer, William R; Nichols, Thomas E

2014-01-01

Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the "core-in-modules" decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems.

Yeast mitochondria: an overview of mitochondrial biology and the potential of mitochondrial systems biology.

PubMed

Malina, Carl; Larsson, Christer; Nielsen, Jens

2018-08-01

Mitochondria are dynamic organelles of endosymbiotic origin that are essential components of eukaryal cells. They contain their own genetic machinery, have multicopy genomes and like their bacterial ancestors they consist of two membranes. However, the majority of the ancestral genome has been lost or transferred to the nuclear genome of the host, preserving only a core set of genes involved in oxidative phosphorylation. Mitochondria perform numerous biological tasks ranging from bioenergetics to production of protein co-factors, including heme and iron-sulfur clusters. Due to the importance of mitochondria in many cellular processes, mitochondrial dysfunction is implicated in a wide variety of human disorders. Much of our current knowledge on mitochondrial function and dysfunction comes from studies using Saccharomyces cerevisiae. This yeast has good fermenting capacity, rendering tolerance to mutations that inactivate oxidative phosphorylation and complete loss of mitochondrial DNA. Here, we review yeast mitochondrial metabolism and function with focus on S. cerevisiae and its contribution in understanding mitochondrial biology. We further review how systems biology studies, including mathematical modeling, has allowed gaining new insight into mitochondrial function, and argue that this approach may enable us to gain a holistic view on how mitochondrial function interacts with different cellular processes.

Imaging and the new biology: What's wrong with this picture?

NASA Astrophysics Data System (ADS)

Vannier, Michael W.

2004-05-01

The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement. Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely understood type. Imaging creates another form of biological information, providing the ability to study morphology, growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale. The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and other "-ome's." To date, the imaging science community has not set a high priority on the unification of their results with genomics, proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of biological data, impairing our ability to conceive and address many fundamental questions in research and clinical practice. This presentation will explain the challenge of biological knowledge integration in basic research and clinical applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the imaging community, and mainstream of new and future biological science will be identified, so the critical and immediate need for change can be highlighted.

Defining the Relationship of Student Achievement Between STEM Subjects Through Canonical Correlation Analysis of 2011 Trends in International Mathematics and Science Study (TIMSS) Data

NASA Astrophysics Data System (ADS)

O'Neal, Melissa Jean

Canonical correlation analysis was used to analyze data from Trends in International Mathematics and Science Study (TIMSS) 2011 achievement databases encompassing information from fourth/eighth grades. Student achievement in life science/biology was correlated with achievement in mathematics and other sciences across three analytical areas: mathematics and science student performance, achievement in cognitive domains, and achievement in content domains. Strong correlations between student achievement in life science/biology with achievement in mathematics and overall science occurred for both high- and low-performing education systems. Hence, partial emphases on the inter-subject connections did not always lead to a better student learning outcome in STEM education. In addition, student achievement in life science/biology was positively correlated with achievement in mathematics and science cognitive domains; these patterns held true for correlations of life science/biology with mathematics as well as other sciences. The importance of linking student learning experiences between and within STEM domains to support high performance on TIMSS assessments was indicated by correlations of moderate strength (57 TIMSS assessments was indicated by correlations of moderate strength (57 < r < 85) stronger correlations (73 < r < 97) between life science/biology and other science domains. Results demonstrated the foundational nature of STEM knowledge at the fourth grade level, and established the importance of strong interconnections among life science/biology, mathematics, and other sciences. At the eighth grade level, students who built increasing levels of cognitive complexity upon firm foundations were prepared for successful learning throughout their educational careers. The results from this investigation promote a holistic design of school learning opportunities to improve student achievement in life science/biology and other science, technology, engineering, and mathematics (STEM) subjects at the elementary and middle school levels. While the curriculum can vary from combined STEM subjects to separated mathematics or science courses, both professional learning communities (PLC) for teachers and problem-based learning (PBL) for learners can be strengthened through new knowledge construction beyond the traditional boundaries of each subject. It is the knowledge transfer across subjects that breaks barriers of future STEM discoveries to improve STEM education outcomes.

Modular plant culture systems for life support functions

NASA Technical Reports Server (NTRS)

1985-01-01

The current state of knowledge with regard to culture of higher plants in the zero-G environment is assessed; and concepts for the empirical development of small plant growth chambers for the production of salad type vegetables on space shuttle or space station are evaluated. American and Soviet space flight experiences in gravitational biology are summarized.

State-of-the-art exposure chamber for highly controlled and reproducible THz biological effects studies

NASA Astrophysics Data System (ADS)

Cerna, Cesario Z.; Elam, David P.; Echchgadda, Ibtissam; Sloan, Mark A.; Wilmink, Gerald J.

2014-03-01

Terahertz (THz) imaging and sensing technologies are increasingly being used at international airports for security screening purposes and at major medical centers for cancer and burn diagnosis. The emergence of new THz applications has directly resulted in an increased interest regarding the biological effects associated with this frequency range. Knowledge of THz biological effects is also desired for the safe use of THz systems, identification of health hazards, and development of empirically-based safety standards. In this study, we developed a state-of-the-art exposure chamber that allowed for highly controlled and reproducible studies of THz biological effects. This innovative system incorporated an industry grade cell incubator system that permitted a highly controlled exposure environment, where temperatures could be maintained at 37 °C +/- 0.1 °C, carbon dioxide (CO2) levels at 5% +/- 0.1%, and relative humidity (RH) levels at 95% +/- 1%. To maximize the THz power transmitted to the cell culture region inside the humid incubator, a secondary custom micro-chamber was fabricated and incorporated into the system. This micro-chamber shields the THz beam from the incubator environment and could be nitrogen-purged to eliminate water absorption effects. Additionally, a microscope that allowed for real-time visualization of the live cells before, during, and after THz exposure was integrated into the exposure system.

Systems biology coupled with label-free high-throughput detection as a novel approach for diagnosis of chronic obstructive pulmonary disease

PubMed Central

Richens, Joanna L; Urbanowicz, Richard A; Lunt, Elizabeth AM; Metcalf, Rebecca; Corne, Jonathan; Fairclough, Lucy; O'Shea, Paul

2009-01-01

Chronic obstructive pulmonary disease (COPD) is a treatable and preventable disease state, characterised by progressive airflow limitation that is not fully reversible. Although COPD is primarily a disease of the lungs there is now an appreciation that many of the manifestations of disease are outside the lung, leading to the notion that COPD is a systemic disease. Currently, diagnosis of COPD relies on largely descriptive measures to enable classification, such as symptoms and lung function. Here the limitations of existing diagnostic strategies of COPD are discussed and systems biology approaches to diagnosis that build upon current molecular knowledge of the disease are described. These approaches rely on new 'label-free' sensing technologies, such as high-throughput surface plasmon resonance (SPR), that we also describe. PMID:19386108

S3QL: A distributed domain specific language for controlled semantic integration of life sciences data

PubMed Central

2011-01-01

Background The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control. We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. Results Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. Conclusions S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms. PMID:21756325

S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.

PubMed

Deus, Helena F; Correa, Miriã C; Stanislaus, Romesh; Miragaia, Maria; Maass, Wolfgang; de Lencastre, Hermínia; Fox, Ronan; Almeida, Jonas S

2011-07-14

The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control.We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms.

Is the efficacy of biological control against plant diseases likely to be more durable than that of chemical pesticides?

PubMed Central

Bardin, Marc; Ajouz, Sakhr; Comby, Morgane; Lopez-Ferber, Miguel; Graillot, Benoît; Siegwart, Myriam; Nicot, Philippe C.

2015-01-01

The durability of a control method for plant protection is defined as the persistence of its efficacy in space and time. It depends on (i) the selection pressure exerted by it on populations of plant pathogens and (ii) on the capacity of these pathogens to adapt to the control method. Erosion of effectiveness of conventional plant protection methods has been widely studied in the past. For example, apparition of resistance to chemical pesticides in plant pathogens or pests has been extensively documented. The durability of biological control has often been assumed to be higher than that of chemical control. Results concerning pest management in agricultural systems have shown that this assumption may not always be justified. Resistance of various pests to one or several toxins of Bacillus thuringiensis and apparition of resistance of the codling moth Cydia pomonella to the C. pomonella granulovirus have, for example, been described. In contrast with the situation for pests, the durability of biological control of plant diseases has hardly been studied and no scientific reports proving the loss of efficiency of biological control agents against plant pathogens in practice has been published so far. Knowledge concerning the possible erosion of effectiveness of biological control is essential to ensure a durable efficacy of biological control agents on target plant pathogens. This knowledge will result in identifying risk factors that can foster the selection of strains of plant pathogens resistant to biological control agents. It will also result in identifying types of biological control agents with lower risk of efficacy loss, i.e., modes of action of biological control agents that does not favor the selection of resistant isolates in natural populations of plant pathogens. An analysis of the scientific literature was then conducted to assess the potential for plant pathogens to become resistant to biological control agents. PMID:26284088

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms.

PubMed

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning. © 2016 K. Southard et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

The need and potential for building a integrated knowledge-base of the Earth-Human system

NASA Astrophysics Data System (ADS)

Jacobs, Clifford

2011-03-01

The pursuit of scientific understanding is increasingly based on interdisciplinary research. To understand more deeply the planet and its interactions requires a progressively more holistic approach, exploring knowledge coming from all scientific and engineering disciplines including but not limited to, biology, chemistry, computer sciences, geosciences, material sciences, mathematics, physics, cyberinfrastucture, and social sciences. Nowhere is such an approach more critical than in the study of global climate change in which one of the major challenges is the development of next-generation Earth System Models that include coupled and interactive representations of ecosystems, agricultural working lands and forests, urban environments, biogeochemistry, atmospheric chemistry, ocean and atmospheric currents, the water cycle, land ice, and human activities.

A bioinformatics roadmap for the human vaccines project.

PubMed

Scheuermann, Richard H; Sinkovits, Robert S; Schenkelberg, Theodore; Koff, Wayne C

2017-06-01

Biomedical research has become a data intensive science in which high throughput experimentation is producing comprehensive data about biological systems at an ever-increasing pace. The Human Vaccines Project is a new public-private partnership, with the goal of accelerating development of improved vaccines and immunotherapies for global infectious diseases and cancers by decoding the human immune system. To achieve its mission, the Project is developing a Bioinformatics Hub as an open-source, multidisciplinary effort with the overarching goal of providing an enabling infrastructure to support the data processing, analysis and knowledge extraction procedures required to translate high throughput, high complexity human immunology research data into biomedical knowledge, to determine the core principles driving specific and durable protective immune responses.

Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine

PubMed Central

Contreras, Alejandra V.; Cocom-Chan, Benjamin; Hernandez-Montes, Georgina; Portillo-Bobadilla, Tobias; Resendis-Antonio, Osbaldo

2016-01-01

It has been experimentally shown that host-microbial interaction plays a major role in shaping the wellness or disease of the human body. Microorganisms coexisting in human tissues provide a variety of benefits that contribute to proper functional activity in the host through the modulation of fundamental processes such as signal transduction, immunity and metabolism. The unbalance of this microbial profile, or dysbiosis, has been correlated with the genesis and evolution of complex diseases such as cancer. Although this latter disease has been thoroughly studied using different high-throughput (HT) technologies, its heterogeneous nature makes its understanding and proper treatment in patients a remaining challenge in clinical settings. Notably, given the outstanding role of host-microbiome interactions, the ecological interactions with microorganisms have become a new significant aspect in the systems that can contribute to the diagnosis and potential treatment of solid cancers. As a part of expanding precision medicine in the area of cancer research, efforts aimed at effective treatments for various kinds of cancer based on the knowledge of genetics, biology of the disease and host-microbiome interactions might improve the prediction of disease risk and implement potential microbiota-directed therapeutics. In this review, we present the state of the art of sequencing and metabolome technologies, computational methods and schemes in systems biology that have addressed recent breakthroughs of uncovering relationships or associations between microorganisms and cancer. Together, microbiome studies extend the horizon of new personalized treatments against cancer from the perspective of precision medicine through a synergistic strategy integrating clinical knowledge, HT data, bioinformatics, and systems biology. PMID:28018236

A knowledge base of the chemical compounds of intermediary metabolism.

PubMed

Karp, P D

1992-08-01

This paper describes a publicly available knowledge base of the chemical compounds involved in intermediary metabolism. We consider the motivations for constructing a knowledge base of metabolic compounds, the methodology by which it was constructed, and the information that it currently contains. Currently the knowledge base describes 981 compounds, listing for each: synonyms for its name, a systematic name, CAS registry number, chemical formula, molecular weight, chemical structure and two-dimensional display coordinates for the structure. The Compound Knowledge Base (CompoundKB) illustrates several methodological principles that should guide the development of biological knowledge bases. I argue that biological datasets should be made available in multiple representations to increase their accessibility to end users, and I present multiple representations of the CompoundKB (knowledge base, relational data base and ASN. 1 representations). I also analyze the general characteristics of these representations to provide an understanding of their relative advantages and disadvantages. Another principle is that the error rate of biological data bases should be estimated and documented-this analysis is performed for the CompoundKB.

Biophysics at the Boundaries: The Next Problem Sets

NASA Astrophysics Data System (ADS)

Skolnick, Malcolm

2009-03-01

The interface between physics and biology is one of the fastest growing subfields of physics. As knowledge of such topics as cellular processes and complex ecological systems advances, researchers have found that progress in understanding these and other systems requires application of more quantitative approaches. Today, there is a growing demand for quantitative and computational skills in biological research and the commercialization of that research. The fragmented teaching of science in our universities still leaves biology outside the quantitative and mathematical culture that is the foundation of physics. This is particularly inopportune at a time when the needs for quantitative thinking about biological systems are exploding. More physicists should be encouraged to become active in research and development in the growing application fields of biophysics including molecular genetics, biomedical imaging, tissue generation and regeneration, drug development, prosthetics, neural and brain function, kinetics of nonequilibrium open biological systems, metabolic networks, biological transport processes, large-scale biochemical networks and stochastic processes in biochemical systems to name a few. In addition to moving into basic research in these areas, there is increasing opportunity for physicists in industry beginning with entrepreneurial roles in taking research results out of the laboratory and in the industries who perfect and market the inventions and developments that physicists produce. In this talk we will identify and discuss emerging opportunities for physicists in biophysical and biotechnological pursuits ranging from basic research through development of applications and commercialization of results. This will include discussion of the roles of physicists in non-traditional areas apart from academia such as patent law, financial analysis and regulatory science and the problem sets assigned in education and training that will enable future biophysicists to fill these roles.

A consistent S-Adenosylmethionine force field improved by dynamic Hirshfeld-I atomic charges for biomolecular simulation

NASA Astrophysics Data System (ADS)

Saez, David Adrian; Vöhringer-Martinez, Esteban

2015-10-01

S-Adenosylmethionine (AdoMet) is involved in many biological processes as cofactor in enzymes transferring its sulfonium methyl group to various substrates. Additionally, it is used as drug and nutritional supplement to reduce the pain in osteoarthritis and against depression. Due to the biological relevance of AdoMet it has been part of various computational simulation studies and will also be in the future. However, to our knowledge no rigorous force field parameter development for its simulation in biological systems has been reported. Here, we use electronic structure calculations combined with molecular dynamics simulations in explicit solvent to develop force field parameters compatible with the AMBER99 force field. Additionally, we propose new dynamic Hirshfeld-I atomic charges which are derived from the polarized electron density of AdoMet in aqueous solution to describe its electrostatic interactions in biological systems. The validation of the force field parameters and the atomic charges is performed against experimental interproton NOE distances of AdoMet in aqueous solution and crystal structures of AdoMet in the cavity of three representative proteins.

Virtually the Same: A Comparison of STEM Students' Content Knowledge, Course Performance, and Motivation to Learn in Virtual and Face-to-Face Introductory Biology Laboratories. Research and Teaching

ERIC Educational Resources Information Center

Reece, Amber J.; Butler, Malcolm B.

2017-01-01

Biology I is a required course for many science, technology, engineering, and mathematics (STEM) majors and is often their first college-level laboratory experience. The replacement of the traditional face-to-face laboratory experience with virtual laboratories could influence students' content knowledge, motivation to learn biology, and overall…

The effect of cooperative learning on the attitudes toward science and the achievement of students in a non-science majors' general biology laboratory course at an urban community college

NASA Astrophysics Data System (ADS)

Chung-Schickler, Genevieve C.

The purpose of this study was to evaluate the effect of cooperative learning strategies on students' attitudes toward science and achievement in BSC 1005L, a non-science majors' general biology laboratory course at an urban community college. Data were gathered on the participants' attitudes toward science and cognitive biology level pre and post treatment in BSC 1005L. Elements of the Learning Together model developed by Johnson and Johnson and the Student Team-Achievement Divisions model created by Slavin were incorporated into the experimental sections of BSC 1005L. Four sections of BSC 1005L participated in this study. Participants were enrolled in the 1998 spring (January) term. Students met weekly in a two hour laboratory session. The treatment was administered to the experimental group over a ten week period. A quasi-experimental pretest-posttest control group design was used. Students in the cooperative learning group (nsb1 = 27) were administered the Test of Science-Related Attitudes (TOSRA) and the cognitive biology test at the same time as the control group (nsb2 = 19) (at the beginning and end of the term). Statistical analyses confirmed that both groups were equivalent regarding ethnicity, gender, college grade point average and number of absences. Independent sample t-tests performed on pretest mean scores indicated no significant differences in the TOSRA scale two or biology knowledge between the cooperative learning group and the control group. The scores of TOSRA scales: one, three, four, five, six, and seven were significantly lower in the cooperative learning group. Independent sample t-tests of the mean score differences did not show any significant differences in posttest attitudes toward science or biology knowledge between the two groups. Paired t-tests did not indicate any significant differences on the TOSRA or biology knowledge within the cooperative learning group. Paired t-tests did show significant differences within the control group on TOSRA scale two and biology knowledge. ANCOVAs did not indicate any significant differences on the post mean scores of the TOSRA or biology knowledge adjusted by differences in the pretest mean scores. Analysis of the research data did not show any significant correlation between attitudes toward science and biology knowledge.

NASA Human Research Program Space Radiation Program Element

NASA Technical Reports Server (NTRS)

Chappell, Lori; Huff, Janice; Patel, Janapriya; Wang, Minli; Hu, Shaowwen; Kidane, Yared; Myung-Hee, Kim; Li, Yongfeng; Nounu, Hatem; Plante, Ianik;

Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

PubMed

MacLeod, Miles; Nersessian, Nancy J

2015-02-01

In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

Genotoxicity and carcinogenicity of cobalt-, nickel- and copper-based nanoparticles

PubMed Central

MAGAYE, RUTH; ZHAO, JINSHUN; BOWMAN, LINDA; DING, MIN

2012-01-01

The nanotechnology industry has matured and expanded at a rapid pace in the last decade, leading to the research and development of nanomaterials with enormous potential. The largest source of these nanomaterials is the transitional metals. It has been revealed that numerous properties of these nano-sized elements are not present in their bulk states. The nano size of these particles means they are easily transported into biological systems, thus, raising the question of their effects on the susceptible systems. Although advances have been made and insights have been gained on the effect of transitional metals on susceptible biological systems, there still is much ground to be covered, particularly with respect to our knowledge on the genotoxic and carcinogenic effects. Therefore, this review intends to summarize the current knowledge on the genotoxic and carcinogenic potential of cobalt-, nickel- and copper-based nanoparticles indicated in in vitro and in vivo mammalian studies. In the present review, we briefly state the sources, use and exposure routes of these nanoparticles and summarize the current literature findings on their in vivo and in vitro genotoxic and carcinogenic effects. Due to the increasing evidence of their role in carcinogenicity, we have also included studies that have reported epigenetic factors, such as abnormal apoptosis, enhanced oxidative stress and pro-inflammatory effects involving these nanoparticles. PMID:23170105

Understanding pictorial information in biology: students' cognitive activities and visual reading strategies

NASA Astrophysics Data System (ADS)

Brandstetter, Miriam; Sandmann, Angela; Florian, Christine

2017-06-01

In classroom, scientific contents are increasingly communicated through visual forms of representations. Students' learning outcomes rely on their ability to read and understand pictorial information. Understanding pictorial information in biology requires cognitive effort and can be challenging to students. Yet evidence-based knowledge about students' visual reading strategies during the process of understanding pictorial information is pending. Therefore, 42 students at the age of 14-15 were asked to think aloud while trying to understand visual representations of the blood circulatory system and the patellar reflex. A category system was developed differentiating 16 categories of cognitive activities. A Principal Component Analysis revealed two underlying patterns of activities that can be interpreted as visual reading strategies: 1. Inferences predominated by using a problem-solving schema; 2. Inferences predominated by recall of prior content knowledge. Each pattern consists of a specific set of cognitive activities that reflect selection, organisation and integration of pictorial information as well as different levels of expertise. The results give detailed insights into cognitive activities of students who were required to understand the pictorial information of complex organ systems. They provide an evidence-based foundation to derive instructional aids that can promote students pictorial-information-based learning on different levels of expertise.

Invited review: gravitational biology of the neuromotor systems: a perspective to the next era

NASA Technical Reports Server (NTRS)

Edgerton, V. R.; Roy, R. R.

2000-01-01

Earth's gravity has had a significant impact on the designs of the neuromotor systems that have evolved. Early indications are that gravity also plays a key role in the ontogenesis of some of these design features. The purpose of the present review is not to assess and interpret a body of knowledge in the usual sense of a review but to look ahead, given some of the general concepts that have evolved and observations made to date, which can guide our future approach to gravitational biology. We are now approaching an era in gravitational biology during which well-controlled experiments can be conducted for sustained periods in a microgravity environment. Thus it is now possible to study in greater detail the role of gravity in phylogenesis and ontogenesis. Experiments can range from those conducted on the simplest levels of organization of the components that comprise the neuromotor system to those conducted on the whole organism. Generally, the impact of Earth's gravitational environment on living systems becomes more complex as the level of integration of the biological phenomenon of interest increases. Studies of the effects of gravitational vectors on neuromotor systems have and should continue to provide unique insight into these mechanisms that control and maintain neural control systems designed to function in Earth's gravitational environment. A number of examples are given of how a gravitational biology perspective can lead to a clearer understanding of neuromotor disorders. Furthermore, the technologies developed for spaceflight studies have contributed and should continue to contribute to studies of motor dysfunctions, such as spinal cord injury and stroke. Disorders associated with energy support and delivery systems and how these functions are altered by sedentary life styles at 1 G and by space travel in a microgravity environment are also discussed.

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

[The practice and discussion of the physical knowledge stepping into genetics teaching].

PubMed

Luo, Shen; Luo, Peigao

2014-09-01

Genetics, one of the core courses of biological field, play a key role in biology teaching and research. In fact, there exists high similarity between many genetic knowledge and physical knowledge. Due to strong abstract of genetic contents and the weak basis of genetics, some students lack of interests to study genetics. How to apply the strong physical knowledge which students had been learned in the middle school in genetics teaching is worthwhile for genetics teachers. In this paper, we would like to introduce an infiltrative teaching model on applying physical knowledge into genetic contents by establishing the intrinsic logistic relationship between physical knowledge and genetic knowledge. This teaching model could help students more deeply understand genetic knowledge and enhance students' self-studying ability as well as creating ability.

Understanding students' explanations of biological phenomena: Conceptual frameworks or p-prims?

NASA Astrophysics Data System (ADS)

Southerland, Sherry A.; Abrams, Eleanor; Cummins, Catherine L.; Anzelmo, Julie

2001-07-01

This study explores two differing perspectives of the nature of students' biological knowledge structures, conceptual frameworks, and p-prims. Students from four grade levels and from three regions of the United States were asked to explain a variety of biological phenomena. Students' responses to the interview probes were analyzed to describe 1) patterns in the nature of students' explanations across grade levels and interview probes, and 2) the consistency of students' explanations across individual interview probes and across the range of probes. The results were interpreted from both perspectives of knowledge structures. While definitive assertions supporting either perspective could not be made, each hypothesis was explored. Although the more prevalent description of student conceptions within a broader conceptual framework could not be discounted, the p-prim of need as a rationale for change was also found to offer a useful description of knowledge frameworks for this content area. The difficulties endemic to the use of biology for the study of basic knowledge structures are also discussed.

Bio-TDS: bioscience query tool discovery system.

PubMed

Gnimpieba, Etienne Z; VanDiermen, Menno S; Gustafson, Shayla M; Conn, Bill; Lushbough, Carol M

2017-01-04

Bioinformatics and computational biology play a critical role in bioscience and biomedical research. As researchers design their experimental projects, one major challenge is to find the most relevant bioinformatics toolkits that will lead to new knowledge discovery from their data. The Bio-TDS (Bioscience Query Tool Discovery Systems, http://biotds.org/) has been developed to assist researchers in retrieving the most applicable analytic tools by allowing them to formulate their questions as free text. The Bio-TDS is a flexible retrieval system that affords users from multiple bioscience domains (e.g. genomic, proteomic, bio-imaging) the ability to query over 12 000 analytic tool descriptions integrated from well-established, community repositories. One of the primary components of the Bio-TDS is the ontology and natural language processing workflow for annotation, curation, query processing, and evaluation. The Bio-TDS's scientific impact was evaluated using sample questions posed by researchers retrieved from Biostars, a site focusing on BIOLOGICAL DATA ANALYSIS: The Bio-TDS was compared to five similar bioscience analytic tool retrieval systems with the Bio-TDS outperforming the others in terms of relevance and completeness. The Bio-TDS offers researchers the capacity to associate their bioscience question with the most relevant computational toolsets required for the data analysis in their knowledge discovery process. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Lyapunov exponents from CHUA's circuit time series using artificial neural networks

NASA Technical Reports Server (NTRS)

Gonzalez, J. Jesus; Espinosa, Ismael E.; Fuentes, Alberto M.

1995-01-01

In this paper we present the general problem of identifying if a nonlinear dynamic system has a chaotic behavior. If the answer is positive the system will be sensitive to small perturbations in the initial conditions which will imply that there is a chaotic attractor in its state space. A particular problem would be that of identifying a chaotic oscillator. We present an example of three well known different chaotic oscillators where we have knowledge of the equations that govern the dynamical systems and from there we can obtain the corresponding time series. In a similar example we assume that we only know the time series and, finally, in another example we have to take measurements in the Chua's circuit to obtain sample points of the time series. With the knowledge about the time series the phase plane portraits are plotted and from them, by visual inspection, it is concluded whether or not the system is chaotic. This method has the problem of uncertainty and subjectivity and for that reason a different approach is needed. A quantitative approach is the computation of the Lyapunov exponents. We describe several methods for obtaining them and apply a little known method of artificial neural networks to the different examples mentioned above. We end the paper discussing the importance of the Lyapunov exponents in the interpretation of the dynamic behavior of biological neurons and biological neural networks.

STARLIFE-An International Campaign to Study the Role of Galactic Cosmic Radiation in Astrobiological Model Systems.

PubMed

Moeller, Ralf; Raguse, Marina; Leuko, Stefan; Berger, Thomas; Hellweg, Christine Elisabeth; Fujimori, Akira; Okayasu, Ryuichi; Horneck, Gerda

2017-02-01

In-depth knowledge regarding the biological effects of the radiation field in space is required for assessing the radiation risks in space. To obtain this knowledge, a set of different astrobiological model systems has been studied within the STARLIFE radiation campaign during six irradiation campaigns (2013-2015). The STARLIFE group is an international consortium with the aim to investigate the responses of different astrobiological model systems to the different types of ionizing radiation (X-rays, γ rays, heavy ions) representing major parts of the galactic cosmic radiation spectrum. Low- and high-energy charged particle radiation experiments have been conducted at the Heavy Ion Medical Accelerator in Chiba (HIMAC) facility at the National Institute of Radiological Sciences (NIRS) in Chiba, Japan. X-rays or γ rays were used as reference radiation at the German Aerospace Center (DLR, Cologne, Germany) or Beta-Gamma-Service GmbH (BGS, Wiehl, Germany) to derive the biological efficiency of different radiation qualities. All samples were exposed under identical conditions to the same dose and qualities of ionizing radiation (i) allowing a direct comparison between the tested specimens and (ii) providing information on the impact of the space radiation environment on currently used astrobiological model organisms. Key Words: Space radiation environment-Sparsely ionizing radiation-Densely ionizing radiation-Heavy ions-Gamma radiation-Astrobiological model systems. Astrobiology 17, 101-109.

Protecting Traditional Knowledge Related to Biological Resources: Is Scientific Research Going to Become More Bureaucratized?

PubMed Central

Reddy, Prashant; Lakshmikumaran, Malathi

2015-01-01

For the past several decades, there has been a world debate on the need for protecting traditional knowledge. A global treaty appears to be a distant reality. Of more immediate concern are the steps taken by the global community to protect access to biological resources in the name of protecting traditional knowledge. The Indian experience with implementing the Convention on Biological Diversity has created substantial legal uncertainty in collaborative scientific research between Indians and foreigners apart from bureaucratizing the entire process of scientific research, especially with regard to filing of applications for intellectual property rights. The issue therefore is whether the world needs to better balance the needs of the scientific community with the rights of those who have access to traditional knowledge. PMID:26101205

Systems pharmacology, pharmacogenetics, and clinical trial design in network medicine.

PubMed

Antman, Elliott; Weiss, Scott; Loscalzo, Joseph

2012-01-01

The rapidly growing disciplines of systems biology and network science are now poised to meet the fields of clinical medicine and pharmacology. Principles of systems pharmacology can be applied to drug design and, ultimately, testing in human clinical trials. Rather than focusing exclusively on single drug targets, systems pharmacology examines the holistic response of a phenotype-dependent pathway or pathways to drug perturbation. Knowledge of individual pharmacogenetic profiles further modulates the responses to these drug perturbations, moving the field toward more individualized ('personalized') drug development. The speed with which the information required to assess these system responses and their genomic underpinnings is changing and the importance of identifying the optimal drug or drug combinations for maximal benefit and minimal risk require that clinical trial design strategies be adaptable. In this paper, we review the tenets of adaptive clinical trial design as they may apply to an era of expanding knowledge of systems pharmacology and pharmacogenomics, and clinical trail design in network medicine. Copyright © 2012 Wiley Periodicals, Inc.

On the Epistemological Crisis in Genomics

PubMed Central

Dougherty, Edward R

2008-01-01

There is an epistemological crisis in genomics. At issue is what constitutes scientific knowledge in genomic science, or systems biology in general. Does this crisis require a new perspective on knowledge heretofore absent from science or is it merely a matter of interpreting new scientific developments in an existing epistemological framework? This paper discusses the manner in which the experimental method, as developed and understood over recent centuries, leads naturally to a scientific epistemology grounded in an experimental-mathematical duality. It places genomics into this epistemological framework and examines the current situation in genomics. Meaning and the constitution of scientific knowledge are key concerns for genomics, and the nature of the epistemological crisis in genomics depends on how these are understood. PMID:19440447

ISMB 2016 offers outstanding science, networking, and celebration

PubMed Central

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392

ISMB 2016 offers outstanding science, networking, and celebration.

PubMed

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.

From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

PubMed

Chiel, Hillel J; McManus, Jeffrey M; Shaw, Kendrick M

2010-01-01

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

Update of KDBI: Kinetic Data of Bio-molecular Interaction database

PubMed Central

Kumar, Pankaj; Han, B. C.; Shi, Z.; Jia, J.; Wang, Y. P.; Zhang, Y. T.; Liang, L.; Liu, Q. F.; Ji, Z. L.; Chen, Y. Z.

2009-01-01

Knowledge of the kinetics of biomolecular interactions is important for facilitating the study of cellular processes and underlying molecular events, and is essential for quantitative study and simulation of biological systems. Kinetic Data of Bio-molecular Interaction database (KDBI) has been developed to provide information about experimentally determined kinetic data of protein–protein, protein–nucleic acid, protein–ligand, nucleic acid–ligand binding or reaction events described in the literature. To accommodate increasing demand for studying and simulating biological systems, numerous improvements and updates have been made to KDBI, including new ways to access data by pathway and molecule names, data file in System Biology Markup Language format, more efficient search engine, access to published parameter sets of simulation models of 63 pathways, and 2.3-fold increase of data (19 263 entries of 10 532 distinctive biomolecular binding and 11 954 interaction events, involving 2635 proteins/protein complexes, 847 nucleic acids, 1603 small molecules and 45 multi-step processes). KDBI is publically available at http://bidd.nus.edu.sg/group/kdbi/kdbi.asp. PMID:18971255

New Frontiers in Synthetic Biology for Spaceflight

NASA Technical Reports Server (NTRS)

Galazka, Jonathan M.

2017-01-01

Exploration of the solar system is constrained by the cost of moving mass off Earth. Producing materials in situ will reduce the mass that must be delivered from earth. CO2 is abundant on Mars and manned spacecraft. On the ISS, NASA reacts excess CO2 with H2 to generate CH4 and H2O using the Sabatier System. The resulting water is recovered into the ISS, but the methane is vented to space. Thus, there is a capability need for systems that convert methane into valuable materials. Methanotrophic bacteria consume methane but these are poor synthetic biology platforms. Thus, there is a knowledge gap in utilizing methane in a robust and flexible synthetic biology platform. The yeast Pichia pastoris is a refined microbial factory that is used widely by industry because it efficiently secretes products. Pichia could produce a variety of useful products in space. Pichia does not consume methane but robustly consumes methanol, which is one enzymatic step removed from methane. Our goal is to engineer Pichia to consume methane thereby creating a powerful methane-consuming microbial factory.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology.

PubMed

Fondi, Marco; Liò, Pietro

2015-02-01

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists. Copyright © 2015. Published by Elsevier GmbH.

Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient.

PubMed

An, Gary; Faeder, James; Vodovotz, Yoram

2008-01-01

The pathophysiology of the burn patient manifests the full spectrum of the complexity of the inflammatory response. In the acute phase, inflammation may have negative effects via capillary leak, the propagation of inhalation injury, and development of multiple organ failure. Attempts to mediate these processes remain a central subject of burn care research. Conversely, inflammation is a necessary prologue and component in the later stage processes of wound healing. Despite the volume of information concerning the cellular and molecular processes involved in inflammation, there exists a significant gap between the knowledge of mechanistic pathophysiology and the development of effective clinical therapeutic regimens. Translational systems biology (TSB) is the application of dynamic mathematical modeling and certain engineering principles to biological systems to integrate mechanism with phenomenon and, importantly, to revise clinical practice. This study will review the existing applications of TSB in the areas of inflammation and wound healing, relate them to specific areas of interest to the burn community, and present an integrated framework that links TSB with traditional burn research.

Osteoporosis in Rheumatic Diseases: Anti-rheumatic Drugs and the Skeleton.

PubMed

Dubrovsky, Alanna M; Lim, Mie Jin; Lane, Nancy E

2018-05-01

Osteoporosis in rheumatic diseases is a very well-known complication. Systemic inflammation results in both generalized and localized bone loss and erosions. Recently, increased knowledge of inflammatory process in rheumatic diseases has resulted in the development of potent inhibitors of the cytokines, the biologic DMARDs. These treatments reduce systemic inflammation and have some effect on the generalized and localized bone loss. Progression of bone erosion was slowed by TNF, IL-6 and IL-1 inhibitors, a JAK inhibitor, a CTLA4 agonist, and rituximab. Effects on bone mineral density varied between the biological DMARDs. Medications that are approved for the treatment of osteoporosis have been evaluated to prevent bone loss in rheumatic disease patients, including denosumab, cathepsin K, bisphosphonates, anti-sclerostin antibodies and parathyroid hormone (hPTH 1-34), and have some efficacy in both the prevention of systemic bone loss and reducing localized bone erosions. This article reviews the effects of biologic DMARDs on bone mass and erosions in patients with rheumatic diseases and trials of anti-osteoporotic medications in animal models and patients with rheumatic diseases.

High School Intervention for Influenza Biology and Epidemics/Pandemics: Impact on Conceptual Understanding among Adolescents

PubMed Central

Hasni, Abdelkrim

2009-01-01

Understanding real-life issues such as influenza epidemiology may be of particular interest to the development of scientific knowledge and initiation of conceptual changes about viruses and their life cycles for high school students. The goal of this research project was to foster the development of adolescents' conceptual understanding of viruses and influenza biology. Thus, the project included two components: 1) pre- and posttests to determine students' conceptions about influenza biology, epidemics/pandemics, and vaccination; and 2) design an intervention that supports conceptual change to promote improvements in influenza knowledge based on these primary conceptions. Thirty-five female students from a high school biology class participated in a series of instructional activities and pre- and posttest assessments. Results from the pretest indicated that high school students exhibit a limited understanding of concepts related to viruses. Six weeks after an intervention that promoted active learning, results from a posttest showed that conceptions about influenza are more accurately related to the provided scientific knowledge. Although adolescents have nonscientific models to explain influenza biology, we showed that a carefully designed intervention can affect students' knowledge as well as influence the implementation of health education programs in secondary schools. PMID:19255137

Using Multiple Lenses to Examine the Development of Beginning Biology Teachers' Pedagogical Content Knowledge for Teaching Natural Selection Simulations

NASA Astrophysics Data System (ADS)

Sickel, Aaron J.; Friedrichsen, Patricia

2018-02-01

Pedagogical content knowledge (PCK) has become a useful construct to examine science teacher learning. Yet, researchers conceptualize PCK development in different ways. The purpose of this longitudinal study was to use three analytic lenses to understand the development of three beginning biology teachers' PCK for teaching natural selection simulations. We observed three early-career biology teachers as they taught natural selection in their respective school contexts over two consecutive years. Data consisted of six interviews with each participant. Using the PCK model developed by Magnusson et al. (1999), we examined topic-specific PCK development utilizing three different lenses: (1) expansion of knowledge within an individual knowledge base, (2) integration of knowledge across knowledge bases, and (3) knowledge that explicitly addressed core concepts of natural selection. We found commonalities across the participants, yet each lens was also useful to understand the influence of different factors (e.g., orientation, subject matter preparation, and the idiosyncratic nature of teacher knowledge) on PCK development. This multi-angle approach provides implications for considering the quality of beginning science teachers' knowledge and future research on PCK development. We conclude with an argument that explicitly communicating lenses used to understand PCK development will help the research community compare analytic approaches and better understand the nature of science teacher learning.

Microarray missing data imputation based on a set theoretic framework and biological knowledge.

PubMed

Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong

2006-01-01

Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods.

Computer simulations for lab experiences in secondary physics

NASA Astrophysics Data System (ADS)

Murphy, David Shannon

Physical science instruction often involves modeling natural systems, such as electricity that possess particles which are invisible to the unaided eye. The effect of these particles' motion is observable, but the particles are not directly observable to humans. Simulations have been developed in physics, chemistry and biology that, under certain circumstances, have been found to allow students to gain insight into the operation of the systems they model. This study compared the use of a DC circuit simulation, a modified simulation, static graphics, and traditional bulbs and wires to compare gains in DC circuit knowledge as measured by the DIRECT instrument, a multiple choice instrument previously developed to assess DC circuit knowledge. Gender, prior DC circuit knowledge and subsets of DC circuit knowledge of students were also compared. The population (n=166) was comprised of high school freshmen students from an eastern Kentucky public school with a population of 1100 students and followed a quantitative quasi experimental research design. Differences between treatment groups were not statistically significant. Keywords: Simulations, Static Images, Science Education, DC Circuit Instruction, Phet.

The use of traditional Hawaiian knowledge in the contemporary management of marine resources

USGS Publications Warehouse

Poepoe, Kelson K.; Bartram, Paul K.; Friedlander, Alan M.

2003-01-01

It is traditional for Hawaiians to "consult nature" so that fishing is practiced at times and places, and with gear that causes minimum disruption of natural biological and ecological processes. The Ho'olehua Hawaiian Homestead continues this tradition in and around Mo'omomi Bay on the northwest coast of the island of Moloka'i. This community relies heavily on inshore marine resources for subsistence and consequently, has an intimate knowledge of these resources. The shared knowledge, beliefs, and values of the community are culturally channeled to promote proper fishing behavior. This informal system brings more knowledge, experience, and moral commitment to fishery conservation than more centralized government management. Community-based management in the Mo'omomi area involves observational processes and problem-solving strategies for the purpose of conservation. The system is not articulated in the manner of Western science, but relies instead on mental models. These models foster a practical understanding of local inshore resource dynamics by the fishing community and, thus, lend credibility to unwritten standards for fishing conduct. The "code of conduct" is concerned with how people fish rather than how much they catch.

Diversified Control Paths: A Significant Way Disease Genes Perturb the Human Regulatory Network

PubMed Central

Wang, Bingbo; Gao, Lin; Zhang, Qingfang; Li, Aimin; Deng, Yue; Guo, Xingli

2015-01-01

Background The complexity of biological systems motivates us to use the underlying networks to provide deep understanding of disease etiology and the human diseases are viewed as perturbations of dynamic properties of networks. Control theory that deals with dynamic systems has been successfully used to capture systems-level knowledge in large amount of quantitative biological interactions. But from the perspective of system control, the ways by which multiple genetic factors jointly perturb a disease phenotype still remain. Results In this work, we combine tools from control theory and network science to address the diversified control paths in complex networks. Then the ways by which the disease genes perturb biological systems are identified and quantified by the control paths in a human regulatory network. Furthermore, as an application, prioritization of candidate genes is presented by use of control path analysis and gene ontology annotation for definition of similarities. We use leave-one-out cross-validation to evaluate the ability of finding the gene-disease relationship. Results have shown compatible performance with previous sophisticated works, especially in directed systems. Conclusions Our results inspire a deeper understanding of molecular mechanisms that drive pathological processes. Diversified control paths offer a basis for integrated intervention techniques which will ultimately lead to the development of novel therapeutic strategies. PMID:26284649

What is new in systemic lupus erythematosus.

PubMed

Rúa-Figueroa Fernández de Larrinoa, Iñigo

2015-01-01

Systemic lupus erythematosus is a heterogeneous rheumatic systemic disease with extremely varied clinical manifestations and a diverse pathogenesis, as illustrated in this review on the most relevant new knowledge related to the disease. Topics such as anemia, pathogenesis, cardiovascular risk assessment, antiphospholipid syndrome, prediction of damage and recent advances in treatment, including tolerogenic and biological agents, are discussed. Relevant contributions regarding classical therapies such as corticosteroid and antimalarials and their optimal use, as well as the roll of vitamin D, are also referred. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort.

PubMed

Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

2016-11-01

Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR).

Outer membrane proteins of pathogenic spirochetes

PubMed Central

Cullen, Paul A.; Haake, David A.; Adler, Ben

2009-01-01

Pathogenic spirochetes are the causative agents of several important diseases including syphilis, Lyme disease, leptospirosis, swine dysentery, periodontal disease and some forms of relapsing fever. Spirochetal bacteria possess two membranes and the proteins present in the outer membrane are at the site of interaction with host tissue and the immune system. This review describes the current knowledge in the field of spirochetal outer membrane protein (OMP) biology. What is known concerning biogenesis and structure of OMPs, with particular regard to the atypical signal peptide cleavage sites observed amongst the spirochetes, is discussed. We examine the functions that have been determined for several spirochetal OMPs including those that have been demonstrated to function as adhesins, porins or to have roles in complement resistance. A detailed description of the role of spirochetal OMPs in immunity, including those that stimulate protective immunity or that are involved in antigenic variation, is given. A final section is included which covers experimental considerations in spirochetal outer membrane biology. This section covers contentious issues concerning cellular localization of putative OMPs, including determination of surface exposure. A more detailed knowledge of spirochetal OMP biology will hopefully lead to the design of new vaccines and a better understanding of spirochetal pathogenesis. PMID:15449605

Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort

PubMed Central

Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

2016-01-01

Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR). PMID:27759770

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action.

PubMed

Dove, Edward S; Faraj, Samer A; Kolker, Eugene; Ozdemir, Vural

2012-01-01

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous 'scientific cultures', we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising 'actors' and 'narrators'. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arm's length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such 'self-calibrating' and nested innovation ecosystems, we introduce the concept of 'wiki-governance' to enable mutual and iterative learning among innovation actors and first- and second-order narrators. '[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing.' [1] 'Ubuntu: I am because you are.' [2].

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action

PubMed Central

2012-01-01

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous 'scientific cultures', we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising 'actors' and 'narrators'. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arm's length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such 'self-calibrating' and nested innovation ecosystems, we introduce the concept of 'wiki-governance' to enable mutual and iterative learning among innovation actors and first- and second-order narrators. '[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing.' [1] 'Ubuntu: I am because you are.' [2] PMID:23194449

StrateGene: object-oriented programming in molecular biology.

PubMed

Carhart, R E; Cash, H D; Moore, J F

1988-03-01

This paper describes some of the ways that object-oriented programming methodologies have been used to represent and manipulate biological information in a working application. When running on a Xerox 1100 series computer, StrateGene functions as a genetic engineering workstation for the management of information about cloning experiments. It represents biological molecules, enzymes, fragments, and methods as classes, subclasses, and members in a hierarchy of objects. These objects may have various attributes, which themselves can be defined and classified. The attributes and their values can be passed from the classes of objects down to the subclasses and members. The user can modify the objects and their attributes while using them. New knowledge and changes to the system can be incorporated relatively easily. The operations on the biological objects are associated with the objects themselves. This makes it easier to invoke them correctly and allows generic operations to be customized for the particular object.