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Sample records for computing biological functions

  1. Metacognition: computation, biology and function

    PubMed Central

    Fleming, Stephen M.; Dolan, Raymond J.; Frith, Christopher D.

    2012-01-01

    Many complex systems maintain a self-referential check and balance. In animals, such reflective monitoring and control processes have been grouped under the rubric of metacognition. In this introductory article to a Theme Issue on metacognition, we review recent and rapidly progressing developments from neuroscience, cognitive psychology, computer science and philosophy of mind. While each of these areas is represented in detail by individual contributions to the volume, we take this opportunity to draw links between disciplines, and highlight areas where further integration is needed. Specifically, we cover the definition, measurement, neurobiology and possible functions of metacognition, and assess the relationship between metacognition and consciousness. We propose a framework in which level of representation, order of behaviour and access consciousness are orthogonal dimensions of the conceptual landscape. PMID:22492746

  2. Metacognition: computation, biology and function.

    PubMed

    Fleming, Stephen M; Dolan, Raymond J; Frith, Christopher D

    2012-05-19

    Many complex systems maintain a self-referential check and balance. In animals, such reflective monitoring and control processes have been grouped under the rubric of metacognition. In this introductory article to a Theme Issue on metacognition, we review recent and rapidly progressing developments from neuroscience, cognitive psychology, computer science and philosophy of mind. While each of these areas is represented in detail by individual contributions to the volume, we take this opportunity to draw links between disciplines, and highlight areas where further integration is needed. Specifically, we cover the definition, measurement, neurobiology and possible functions of metacognition, and assess the relationship between metacognition and consciousness. We propose a framework in which level of representation, order of behaviour and access consciousness are orthogonal dimensions of the conceptual landscape.

  3. All biology is computational biology

    PubMed Central

    2017-01-01

    Here, I argue that computational thinking and techniques are so central to the quest of understanding life that today all biology is computational biology. Computational biology brings order into our understanding of life, it makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. The next modern synthesis in biology will be driven by mathematical, statistical, and computational methods being absorbed into mainstream biological training, turning biology into a quantitative science. PMID:28278152

  4. All biology is computational biology.

    PubMed

    Markowetz, Florian

    2017-03-01

    Here, I argue that computational thinking and techniques are so central to the quest of understanding life that today all biology is computational biology. Computational biology brings order into our understanding of life, it makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. The next modern synthesis in biology will be driven by mathematical, statistical, and computational methods being absorbed into mainstream biological training, turning biology into a quantitative science.

  5. 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

  6. Computational Systems Biology

    SciTech Connect

    McDermott, Jason E.; Samudrala, Ram; Bumgarner, Roger E.; Montogomery, Kristina; Ireton, Renee

    2009-05-01

    Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (“systems”) involved in a living organism. Based on this definition, the field of computational systems biology has been in existence for some time. However, the recent confluence of high throughput methodology for biological data gathering, genome-scale sequencing and computational processing power has driven a reinvention and expansion of this field. The expansions include not only modeling of small metabolic{Ishii, 2004 #1129; Ekins, 2006 #1601; Lafaye, 2005 #1744} and signaling systems{Stevenson-Paulik, 2006 #1742; Lafaye, 2005 #1744} but also modeling of the relationships between biological components in very large systems, incluyding whole cells and organisms {Ideker, 2001 #1124; Pe'er, 2001 #1172; Pilpel, 2001 #393; Ideker, 2002 #327; Kelley, 2003 #1117; Shannon, 2003 #1116; Ideker, 2004 #1111}{Schadt, 2003 #475; Schadt, 2006 #1661}{McDermott, 2002 #878; McDermott, 2005 #1271}. Generally these models provide a general overview of one or more aspects of these systems and leave the determination of details to experimentalists focused on smaller subsystems. The promise of such approaches is that they will elucidate patterns, relationships and general features that are not evident from examining specific components or subsystems. These predictions are either interesting in and of themselves (for example, the identification of an evolutionary pattern), or are interesting and valuable to researchers working on a particular problem (for example highlight a previously unknown functional pathway). Two events have occurred to bring about the field computational systems biology to the forefront. One is the advent of high throughput methods that have generated large amounts of information about particular systems in the form of genetic studies, gene expression analyses (both protein and

  7. Function and dynamics of macromolecular complexes explored by integrative structural and computational biology.

    PubMed

    Purdy, Michael D; Bennett, Brad C; McIntire, William E; Khan, Ali K; Kasson, Peter M; Yeager, Mark

    2014-08-01

    Three vignettes exemplify the potential of combining EM and X-ray crystallographic data with molecular dynamics (MD) simulation to explore the architecture, dynamics and functional properties of multicomponent, macromolecular complexes. The first two describe how EM and X-ray crystallography were used to solve structures of the ribosome and the Arp2/3-actin complex, which enabled MD simulations that elucidated functional dynamics. The third describes how EM, X-ray crystallography, and microsecond MD simulations of a GPCR:G protein complex were used to explore transmembrane signaling by the β-adrenergic receptor. Recent technical advancements in EM, X-ray crystallography and computational simulation create unprecedented synergies for integrative structural biology to reveal new insights into heretofore intractable biological systems.

  8. Computational Systems Chemical Biology

    PubMed Central

    Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

    2013-01-01

    There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007). The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology / systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology. PMID:20838980

  9. Computational systems chemical biology.

    PubMed

    Oprea, Tudor I; May, Elebeoba E; Leitão, Andrei; Tropsha, Alexander

    2011-01-01

    There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology (SCB) (Nat Chem Biol 3: 447-450, 2007).The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules, and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology/systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology, and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology.

  10. Computational biology for ageing.

    PubMed

    Wieser, Daniela; Papatheodorou, Irene; Ziehm, Matthias; Thornton, Janet M

    2011-01-12

    High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions.

  11. Redox Biology: Computational Approaches to the Investigation of Functional Cysteine Residues

    PubMed Central

    Marino, Stefano M.

    2011-01-01

    Abstract Cysteine (Cys) residues serve many functions, such as catalysis, stabilization of protein structure through disulfides, metal binding, and regulation of protein function. Cys residues are also subject to numerous post-translational modifications. In recent years, various computational tools aiming at classifying and predicting different functional categories of Cys have been developed, particularly for structural and catalytic Cys. On the other hand, given complexity of the subject, bioinformatics approaches have been less successful for the investigation of regulatory Cys sites. In this review, we introduce different functional categories of Cys residues. For each category, an overview of state-of-the-art bioinformatics methods and tools is provided, along with examples of successful applications and potential limitations associated with each approach. Finally, we discuss Cys-based redox switches, which modify the view of distinct functional categories of Cys in proteins. Antioxid. Redox Signal. 15, 135–146. PMID:20812876

  12. Computational optimization and biological evolution.

    PubMed

    Goryanin, Igor

    2010-10-01

    Modelling and optimization principles become a key concept in many biological areas, especially in biochemistry. Definitions of objective function, fitness and co-evolution, although they differ between biology and mathematics, are similar in a general sense. Although successful in fitting models to experimental data, and some biochemical predictions, optimization and evolutionary computations should be developed further to make more accurate real-life predictions, and deal not only with one organism in isolation, but also with communities of symbiotic and competing organisms. One of the future goals will be to explain and predict evolution not only for organisms in shake flasks or fermenters, but for real competitive multispecies environments.

  13. 2D-RNA-coupling numbers: a new computational chemistry approach to link secondary structure topology with biological function.

    PubMed

    González-Díaz, Humberto; Agüero-Chapin, Guillermín; Varona, Javier; Molina, Reinaldo; Delogu, Giovanna; Santana, Lourdes; Uriarte, Eugenio; Podda, Gianni

    2007-04-30

    Methods for prediction of proteins, DNA, or RNA function and mapping it onto sequence often rely on bioinformatics alignment approach instead of chemical structure. Consequently, it is interesting to develop computational chemistry approaches based on molecular descriptors. In this sense, many researchers used sequence-coupling numbers and our group extended them to 2D proteins representations. However, no coupling numbers have been reported for 2D-RNA topology graphs, which are highly branched and contain useful information. Here, we use a computational chemistry scheme: (a) transforming sequences into RNA secondary structures, (b) defining and calculating new 2D-RNA-coupling numbers, (c) seek a structure-function model, and (d) map biological function onto the folded RNA. We studied as example 1-aminocyclopropane-1-carboxylic acid (ACC) oxidases known as ACO, which control fruit ripening having importance for biotechnology industry. First, we calculated tau(k)(2D-RNA) values to a set of 90-folded RNAs, including 28 transcripts of ACO and control sequences. Afterwards, we compared the classification performance of 10 different classifiers implemented in the software WEKA. In particular, the logistic equation ACO = 23.8 . tau(1)(2D-RNA) + 41.4 predicts ACOs with 98.9%, 98.0%, and 97.8% of accuracy in training, leave-one-out and 10-fold cross-validation, respectively. Afterwards, with this equation we predict ACO function to a sequence isolated in this work from Coffea arabica (GenBank accession DQ218452). The tau(1)(2D-RNA) also favorably compare with other descriptors. This equation allows us to map the codification of ACO activity on different mRNA topology features. The present computational-chemistry approach is general and could be extended to connect RNA secondary structure topology to other functions.

  14. GPU computing for systems biology.

    PubMed

    Dematté, Lorenzo; Prandi, Davide

    2010-05-01

    The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate biological systems. However, the computational power required by these simulations often exceeds that available on common desktop computers and thus expensive high performance computing solutions are required. An emerging alternative is represented by general-purpose scientific computing on graphics processing units (GPGPU), which offers the power of a small computer cluster at a cost of approximately $400. Computing with a GPU requires the development of specific algorithms, since the programming paradigm substantially differs from traditional CPU-based computing. In this paper, we review some recent efforts in exploiting the processing power of GPUs for the simulation of biological systems.

  15. Computational Biology and High Performance Computing 2000

    SciTech Connect

    Simon, Horst D.; Zorn, Manfred D.; Spengler, Sylvia J.; Shoichet, Brian K.; Stewart, Craig; Dubchak, Inna L.; Arkin, Adam P.

    2000-10-19

    The pace of extraordinary advances in molecular biology has accelerated in the past decade due in large part to discoveries coming from genome projects on human and model organisms. The advances in the genome project so far, happening well ahead of schedule and under budget, have exceeded any dreams by its protagonists, let alone formal expectations. Biologists expect the next phase of the genome project to be even more startling in terms of dramatic breakthroughs in our understanding of human biology, the biology of health and of disease. Only today can biologists begin to envision the necessary experimental, computational and theoretical steps necessary to exploit genome sequence information for its medical impact, its contribution to biotechnology and economic competitiveness, and its ultimate contribution to environmental quality. High performance computing has become one of the critical enabling technologies, which will help to translate this vision of future advances in biology into reality. Biologists are increasingly becoming aware of the potential of high performance computing. The goal of this tutorial is to introduce the exciting new developments in computational biology and genomics to the high performance computing community.

  16. Computational biology for cardiovascular biomarker discovery.

    PubMed

    Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

    2009-07-01

    Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

  17. Computational Skills for Biology Students

    ERIC Educational Resources Information Center

    Gross, Louis J.

    2008-01-01

    This interview with Distinguished Science Award recipient Louis J. Gross highlights essential computational skills for modern biology, including: (1) teaching concepts listed in the Math & Bio 2010 report; (2) illustrating to students that jobs today require quantitative skills; and (3) resources and materials that focus on computational skills.

  18. Limits of computational biology.

    PubMed

    Bray, Dennis

    2015-01-01

    Are we close to a complete inventory of living processes so that we might expect in the near future to reproduce every essential aspect necessary for life? Or are there mechanisms and processes in cells and organisms that are presently inaccessible to us? Here I argue that a close examination of a particularly well-understood system--that of Escherichia coli chemotaxis--shows we are still a long way from a complete description. There is a level of molecular uncertainty, particularly that responsible for fine-tuning and adaptation to myriad external conditions, which we presently cannot resolve or reproduce on a computer. Moreover, the same uncertainty exists for any process in any organism and is especially pronounced and important in higher animals such as humans. Embryonic development, tissue homeostasis, immune recognition, memory formation, and survival in the real world, all depend on vast numbers of subtle variations in cell chemistry most of which are presently unknown or only poorly characterized. Overcoming these limitations will require us to not only accumulate large quantities of highly detailed data but also develop new computational methods able to recapitulate the massively parallel processing of living cells.

  19. Limits of computational biology

    PubMed Central

    Bray, Dennis

    2015-01-01

    Abstract Are we close to a complete inventory of living processes so that we might expect in the near future to reproduce every essential aspect necessary for life? Or are there mechanisms and processes in cells and organisms that are presently inaccessible to us? Here I argue that a close examination of a particularly well-understood system— that of Escherichia coli chemotaxis— shows we are still a long way from a complete description. There is a level of molecular uncertainty, particularly that responsible for fine-tuning and adaptation to myriad external conditions, which we presently cannot resolve or reproduce on a computer. Moreover, the same uncertainty exists for any process in any organism and is especially pronounced and important in higher animals such as humans. Embryonic development, tissue homeostasis, immune recognition, memory formation, and survival in the real world, all depend on vast numbers of subtle variations in cell chemistry most of which are presently unknown or only poorly characterized. Overcoming these limitations will require us to not only accumulate large quantities of highly detailed data but also develop new computational methods able to recapitulate the massively parallel processing of living cells. PMID:25318467

  20. Biomaterial science meets computational biology.

    PubMed

    Hutmacher, Dietmar W; Little, J Paige; Pettet, Graeme J; Loessner, Daniela

    2015-05-01

    There is a pressing need for a predictive tool capable of revealing a holistic understanding of fundamental elements in the normal and pathological cell physiology of organoids in order to decipher the mechanoresponse of cells. Therefore, the integration of a systems bioengineering approach into a validated mathematical model is necessary to develop a new simulation tool. This tool can only be innovative by combining biomaterials science with computational biology. Systems-level and multi-scale experimental data are incorporated into a single framework, thus representing both single cells and collective cell behaviour. Such a computational platform needs to be validated in order to discover key mechano-biological factors associated with cell-cell and cell-niche interactions.

  1. 2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research.

    PubMed

    Yang, Jack Y; Niemierko, Andrzej; Bajcsy, Ruzena; Xu, Dong; Athey, Brian D; Zhang, Aidong; Ersoy, Okan K; Li, Guo-Zheng; Borodovsky, Mark; Zhang, Joe C; Arabnia, Hamid R; Deng, Youping; Dunker, A Keith; Liu, Yunlong; Ghafoor, Arif

    2010-12-01

    Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT

  2. 2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

    PubMed Central

    2010-01-01

    Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT

  3. The new biology and computational statistical physics

    NASA Astrophysics Data System (ADS)

    Rintoul, Mark D.

    2002-06-01

    While it has historically been an exploratory, descriptive, and empirical science, in the past 100 years, biology has become more discovery- and mechanism-oriented. There are a number of ways in which this new paradigm is driving much of the current biological research toward statistical physics. This is happening at a molecular level due to the very large nature of biological molecules, such as proteins and nucleic acids. It is also occurring at the cellular level where random processes play an important role in cell function. There are even examples that describe the behavior of large numbers of individual organisms within one or more species. Finally, this trend has been accelerated with the advent of high-throughput experimental techniques that are driving biology towards information science. Analysis and discovery of the information gained from such experiments will rely heavily on techniques that have traditionally been applied in statistical physics. This paper will focus on examples of how statistical physics techniques are being applied and hope to be applied to biological problems, with an emphasis on high-performance computing. We will also speculate on what we feel are the necessary computing requirements to solve many of the outstanding problems in computational biology using the techniques that will be discussed.

  4. Deep learning for computational biology.

    PubMed

    Angermueller, Christof; Pärnamaa, Tanel; Parts, Leopold; Stegle, Oliver

    2016-07-29

    Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new technology.

  5. A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

    PubMed Central

    2010-01-01

    Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological

  6. Multiscale Computational Models of Complex Biological Systems

    PubMed Central

    Walpole, Joseph; Papin, Jason A.; Peirce, Shayn M.

    2014-01-01

    Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental platforms, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems while using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to best leverage these multiscale models to gain insight into biological systems using quantitative, biomedical engineering methods to analyze data in non-intuitive ways. These topics are discussed with a focus on the future of the field, the current challenges encountered, and opportunities yet to be realized. PMID:23642247

  7. Functional Aspects of Biological Networks

    NASA Astrophysics Data System (ADS)

    Sneppen, Kim

    2007-03-01

    We discuss biological networks with respect to 1) relative positioning and importance of high degree nodes, 2) function and signaling, 3) logic and dynamics of regulation. Visually the soft modularity of many real world networks can be characterized in terms of number of high and low degrees nodes positioned relative to each other in a landscape analogue with mountains (high-degree nodes) and valleys (low-degree nodes). In these terms biological networks looks like rugged landscapes with separated peaks, hub proteins, which each are roughly as essential as any of the individual proteins on the periphery of the hub. Within each sup-domain of a molecular network one can often identify dynamical feedback mechanisms that falls into combinations of positive and negative feedback circuits. We will illustrate this with examples taken from phage regulation and bacterial uptake and regulation of small molecules. In particular we find that a double negative regulation often are replaced by a single positive link in unrelated organisms with same functional requirements. Overall we argue that network topology primarily reflects functional constraints. References: S. Maslov and K. Sneppen. ``Computational architecture of the yeast regulatory network." Phys. Biol. 2:94 (2005) A. Trusina et al. ``Functional alignment of regulatory networks: A study of temerate phages". Plos Computational Biology 1:7 (2005). J.B. Axelsen et al. ``Degree Landscapes in Scale-Free Networks" physics/0512075 (2005). A. Trusina et al. ``Hierarchy and Anti-Hierarchy in Real and Scale Free networks." PRL 92:178702 (2004) S. Semsey et al. ``Genetic Regulation of Fluxes: Iron Homeostasis of Escherichia coli". (2006) q-bio.MN/0609042

  8. Functions in Biological Kind Classification

    ERIC Educational Resources Information Center

    Lombrozo, Tania; Rehder, Bob

    2012-01-01

    Biological traits that serve functions, such as a zebra's coloration (for camouflage) or a kangaroo's tail (for balance), seem to have a special role in conceptual representations for biological kinds. In five experiments, we investigate whether and why functional features are privileged in biological kind classification. Experiment 1…

  9. Designing integrated computational biology pipelines visually.

    PubMed

    Jamil, Hasan M

    2013-01-01

    The long-term cost of developing and maintaining a computational pipeline that depends upon data integration and sophisticated workflow logic is too high to even contemplate "what if" or ad hoc type queries. In this paper, we introduce a novel application building interface for computational biology research, called VizBuilder, by leveraging a recent query language called BioFlow for life sciences databases. Using VizBuilder, it is now possible to develop ad hoc complex computational biology applications at throw away costs. The underlying query language supports data integration and workflow construction almost transparently and fully automatically, using a best effort approach. Users express their application by drawing it with VizBuilder icons and connecting them in a meaningful way. Completed applications are compiled and translated as BioFlow queries for execution by the data management system LifeDB, for which VizBuilder serves as a front end. We discuss VizBuilder features and functionalities in the context of a real life application after we briefly introduce BioFlow. The architecture and design principles of VizBuilder are also discussed. Finally, we outline future extensions of VizBuilder. To our knowledge, VizBuilder is a unique system that allows visually designing computational biology pipelines involving distributed and heterogeneous resources in an ad hoc manner.

  10. A computational functional genomics based self-limiting self-concentration mechanism of cell specialization as a biological role of jumping genes.

    PubMed

    Lötsch, Jörn; Ultsch, Alfred

    2016-01-01

    Specialization is ubiquitous in biological systems and its manifold mechanisms are active research topics. Although clearly adaptive, the way in which specialization of cells is realized remains incompletely understood as it requires the reshaping of a cell's genome to favor particular biological processes in the competition on a cell's functional capacity. Here, a self-specialization mechanism is identified as a possible biological role of jumping genes, in particular LINE-1 retrotransposition. The mechanism is self-limiting and consistent with its evolutionary preservation despite its likely gene-breaking effects. The scenario we studied was the need for a cell to process a longer exposition to an extraordinary situation, for example continuous exposure to the nociceptive input or the intake of addictive drugs. Both situations may evolve toward chronification. The mechanism involves competition within a gene set in which a subset of genes cooperating in particular biological processes. The subset carries a piece of information, consisting of the LINE-1 sequence, about the destruction of their functional competitor genes which are not involved in that process. During gene transcription, an active copy of LINE-1 is co-transcribed. At a certain low probability, a subsequently transcribed and thus actually exposed gene can be rendered nonfunctional by LINE-1 retrotransposition in a relevant gene part. As retrotransposition needs time it is unlikely that LINE-1 retrotranspose into its own carrier gene. This reshapes the cell genome toward self-specializing of those biological processes that are carried out with a high number of LINE-1 containing genes. Self-termination of the mechanism is achieved by allowing LINE-1 to also occasionally jump into the coding region of itself, thus destroying the information about competitor destruction by successively decreasing the number of LINE-1 until the mechanism ceases. Employing a computational functional genomics approach, we

  11. Computer Analogies: Teaching Molecular Biology and Ecology.

    ERIC Educational Resources Information Center

    Rice, Stanley; McArthur, John

    2002-01-01

    Suggests that computer science analogies can aid the understanding of gene expression, including the storage of genetic information on chromosomes. Presents a matrix of biology and computer science concepts. (DDR)

  12. The relativity of biological function.

    PubMed

    Laubichler, Manfred D; Stadler, Peter F; Prohaska, Sonja J; Nowick, Katja

    2015-12-01

    Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

  13. Computational Biology: A Strategic Initiative LDRD

    SciTech Connect

    Barksy, D; Colvin, M

    2002-02-07

    The goal of this Strategic Initiative LDRD project was to establish at LLNL a new core capability in computational biology, combining laboratory strengths in high performance computing, molecular biology, and computational chemistry and physics. As described in this report, this project has been very successful in achieving this goal. This success is demonstrated by the large number of referred publications, invited talks, and follow-on research grants that have resulted from this project. Additionally, this project has helped build connections to internal and external collaborators and funding agencies that will be critical to the long-term vitality of LLNL programs in computational biology. Most importantly, this project has helped establish on-going research groups in the Biology and Biotechnology Research Program, the Physics and Applied Technology Directorate, and the Computation Directorate. These groups include three laboratory staff members originally hired as post-doctoral researchers for this strategic initiative.

  14. 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.

  15. Computer vision in cell biology.

    PubMed

    Danuser, Gaudenz

    2011-11-23

    Computer vision refers to the theory and implementation of artificial systems that extract information from images to understand their content. Although computers are widely used by cell biologists for visualization and measurement, interpretation of image content, i.e., the selection of events worth observing and the definition of what they mean in terms of cellular mechanisms, is mostly left to human intuition. This Essay attempts to outline roles computer vision may play and should play in image-based studies of cellular life.

  16. Biocellion: accelerating computer simulation of multicellular biological system models

    PubMed Central

    Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

    2014-01-01

    Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

  17. Functional constituents of wild and cultivated Goji (L. barbarum L.) leaves: phytochemical characterization, biological profile, and computational studies.

    PubMed

    Mocan, Andrei; Zengin, Gökhan; Simirgiotis, Mario; Schafberg, Michaela; Mollica, Adriano; Vodnar, Dan C; Crişan, Gianina; Rohn, Sascha

    2017-12-01

    Goji (Lycium barbarum L.) leaves are emphasized as a functional tea or as dietary supplements. The phenolic compound profile, antioxidant, enzyme inhibitory, antimicrobial, and antimutagenic activities of leaf extracts from two selected cultivars in comparison with wild-growing plants have been evaluated. HPLC-DAD/ESI-ToF-MS analysis revealed the presence of phenolic acids and flavonoids with chlorogenic acid and rutin being the dominant compounds in the cultivated plants, whereas rutin and kaempeferol-3-O-rutinoside for wild growing ones. In particular, cv. Erma contained the highest amount of chlorogenic acid and showed a strong tyrosinase-inhibitory effect. Staphylococcus aureus, Listeria monocytogenes, and Penicillium funiculosum were the most sensitive strains when exposed to extracts from cultivated plants. Antimutagenic activity was evaluated by Ames' test. The tested extracts provided high protection against mutagenicity induced by 2-anthramine (2-AA) to Salmonella typhimurium strains TA 98 and TA 100 (max. inhibition (%) 88% and 74.2%, respectively). Overall, Goji leaves are a rich source of bioactive compounds with functional properties that need further risk/benefit evaluation when used in foods or health-promoting formulations.

  18. Analog Computer Laboratory with Biological Examples.

    ERIC Educational Resources Information Center

    Strebel, Donald E.

    1979-01-01

    The use of biological examples in teaching applications of the analog computer is discussed and several examples from mathematical ecology, enzyme kinetics, and tracer dynamics are described. (Author/GA)

  19. Computational Biology in microRNA.

    PubMed

    Li, Yue; Zhang, Zhaolei

    2015-01-01

    MicroRNA (miRNA) is a class of small endogenous noncoding RNA species, which regulate gene expression post-transcriptionally by forming imperfect base-pair at the 3' untranslated regions of the messenger RNAs. Since the 1993 discovery of the first miRNA let-7 in worms, a vast number of studies have been dedicated to functionally characterizing miRNAs with a special emphasis on their roles in cancer. A single miRNA can potentially target ∼ 400 distinct genes, and there are over a 1000 distinct endogenous miRNAs in the human genome. Thus, miRNAs are likely involved in virtually all biological processes and pathways including carcinogenesis. However, functionally characterizing miRNAs hinges on the accurate identification of their mRNA targets, which has been a challenging problem due to imperfect base-pairing and condition-specific miRNA regulatory dynamics. In this review, we will survey the current state-of-the-art computational methods to predict miRNA targets, which are divided into three main categories: (1) sequence-based methods that primarily utilizes the canonical seed-match model, evolutionary conservation, and binding energy; (2) expression-based target prediction methods using the increasingly available miRNA and mRNA expression data measured for the same sample; and (3) network-based method that aims identify miRNA regulatory modules, which reflect their synergism in conferring a global impact to the biological system of interest. We hope that the review will serve as a good reference to the new comers to the ever-growing miRNA research field as well as veterans, who would appreciate the detailed review on the technicalities, strength, and limitations of each representative computational method.

  20. India's Computational Biology Growth and Challenges.

    PubMed

    Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Agoramoorthy, Govindasamy

    2016-09-01

    India's computational science is growing swiftly due to the outburst of internet and information technology services. The bioinformatics sector of India has been transforming rapidly by creating a competitive position in global bioinformatics market. Bioinformatics is widely used across India to address a wide range of biological issues. Recently, computational researchers and biologists are collaborating in projects such as database development, sequence analysis, genomic prospects and algorithm generations. In this paper, we have presented the Indian computational biology scenario highlighting bioinformatics-related educational activities, manpower development, internet boom, service industry, research activities, conferences and trainings undertaken by the corporate and government sectors. Nonetheless, this new field of science faces lots of challenges.

  1. Integrating interactive computational modeling in biology curricula.

    PubMed

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  2. Graphics processing units in bioinformatics, computational biology and systems biology.

    PubMed

    Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

    2016-07-08

    Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools.

  3. Software For Computing Selected Functions

    NASA Technical Reports Server (NTRS)

    Grant, David C.

    1992-01-01

    Technical memorandum presents collection of software packages in Ada implementing mathematical functions used in science and engineering. Provides programmer with function support in Pascal and FORTRAN, plus support for extended-precision arithmetic and complex arithmetic. Valuable for testing new computers, writing computer code, or developing new computer integrated circuits.

  4. Standards and ontologies in computational systems biology.

    PubMed

    Sauro, Herbert M; Bergmann, Frank T

    2008-01-01

    With the growing importance of computational models in systems biology there has been much interest in recent years to develop standard model interchange languages that permit biologists to easily exchange models between different software tools. In the present chapter two chief model exchange standards, SBML (Systems Biology Markup Language) and CellML are described. In addition, other related features including visual layout initiatives, ontologies and best practices for model annotation are discussed. Software tools such as developer libraries and basic editing tools are also introduced, together with a discussion on the future of modelling languages and visualization tools in systems biology.

  5. Applicability of computational systems biology in toxicology.

    PubMed

    Kongsbak, Kristine; Hadrup, Niels; Audouze, Karine; Vinggaard, Anne Marie

    2014-07-01

    Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search. However, computational systems biology offers more advantages than providing a high-throughput literature search; it may form the basis for establishment of hypotheses on potential links between environmental chemicals and human diseases, which would be very difficult to establish experimentally. This is possible due to the existence of comprehensive databases containing information on networks of human protein-protein interactions and protein-disease associations. Experimentally determined targets of the specific chemical of interest can be fed into these networks to obtain additional information that can be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method in the hypothesis-generating phase of toxicological research.

  6. The "Biologically-Inspired Computing" Column

    NASA Technical Reports Server (NTRS)

    Hinchey, Mike

    2007-01-01

    Self-managing systems, whether viewed from the perspective of Autonomic Computing, or from that of another initiative, offers a holistic vision for the development and evolution of biologically-inspired computer-based systems. It aims to bring new levels of automation and dependability to systems, while simultaneously hiding their complexity and reducing costs. A case can certainly be made that all computer-based systems should exhibit autonomic properties [6], and we envisage greater interest in, and uptake of, autonomic principles in future system development.

  7. Micro-Computers in Biology Inquiry.

    ERIC Educational Resources Information Center

    Barnato, Carolyn; Barrett, Kathy

    1981-01-01

    Describes the modification of computer programs (BISON and POLLUT) to accommodate species and areas indigenous to the Pacific Coast area. Suggests that these programs, suitable for PET microcomputers, may foster a long-term, ongoing, inquiry-directed approach in biology. (DS)

  8. A Computer Applications Course for Biology Students.

    ERIC Educational Resources Information Center

    Ralph, Charles L.

    1989-01-01

    Describes a computer applications course developed for undergraduate biology students (primarily sophomores) to teach word processing, database and spreadsheet programs, graphing programs, telecommunications, and file transfer procedures. AppleWorks software is discussed, course content is explained, and the microcomputer laboratory is described.…

  9. The Center for Computational Biology: resources, achievements, and challenges.

    PubMed

    Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

    2012-01-01

    The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

  10. Understanding biological computation: reliable learning and recognition.

    PubMed Central

    Hogg, T; Huberman, B A

    1984-01-01

    We experimentally examine the consequences of the hypothesis that the brain operates reliably, even though individual components may intermittently fail, by computing with dynamical attractors. Specifically, such a mechanism exploits dynamic collective behavior of a system with attractive fixed points in its phase space. In contrast to the usual methods of reliable computation involving a large number of redundant elements, this technique of self-repair only requires collective computation with a few units, and it is amenable to quantitative investigation. Experiments on parallel computing arrays show that this mechanism leads naturally to rapid self-repair, adaptation to the environment, recognition and discrimination of fuzzy inputs, and conditional learning, properties that are commonly associated with biological computation. PMID:6593731

  11. Ranked retrieval of Computational Biology models

    PubMed Central

    2010-01-01

    Background The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Results Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. Conclusions The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models. PMID:20701772

  12. The biological function of consciousness

    PubMed Central

    Earl, Brian

    2014-01-01

    This research is an investigation of whether consciousness—one's ongoing experience—influences one's behavior and, if so, how. Analysis of the components, structure, properties, and temporal sequences of consciousness has established that, (1) contrary to one's intuitive understanding, consciousness does not have an active, executive role in determining behavior; (2) consciousness does have a biological function; and (3) consciousness is solely information in various forms. Consciousness is associated with a flexible response mechanism (FRM) for decision-making, planning, and generally responding in nonautomatic ways. The FRM generates responses by manipulating information and, to function effectively, its data input must be restricted to task-relevant information. The properties of consciousness correspond to the various input requirements of the FRM; and when important information is missing from consciousness, functions of the FRM are adversely affected; both of which indicate that consciousness is the input data to the FRM. Qualitative and quantitative information (shape, size, location, etc.) are incorporated into the input data by a qualia array of colors, sounds, and so on, which makes the input conscious. This view of the biological function of consciousness provides an explanation why we have experiences; why we have emotional and other feelings, and why their loss is associated with poor decision-making; why blindsight patients do not spontaneously initiate responses to events in their blind field; why counter-habitual actions are only possible when the intended action is in mind; and the reason for inattentional blindness. PMID:25140159

  13. Network Coding for Function Computation

    ERIC Educational Resources Information Center

    Appuswamy, Rathinakumar

    2011-01-01

    In this dissertation, the following "network computing problem" is considered. Source nodes in a directed acyclic network generate independent messages and a single receiver node computes a target function f of the messages. The objective is to maximize the average number of times f can be computed per network usage, i.e., the "computing…

  14. Computational biology and bioinformatics in Nigeria.

    PubMed

    Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

    2014-04-01

    Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

  15. The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

    PubMed

    Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

    2012-01-01

    Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

  16. Standards and Ontologies in Computational Systems Biology

    PubMed Central

    Sauro, Herbert M.; Bergmann, Frank

    2009-01-01

    With the growing importance of computational models in systems biology there has been much interest in recent years to develop standard model interchange languages that permit biologists to easily exchange models between different software tools. In this chapter two chief model exchange standards, SBML and CellML are described. In addition, other related features including visual layout initiatives, ontologies and best practices for model annotation are discussed. Software tools such as developer libraries and basic editing tools are also introduced together with a discussion on the future of modeling languages and visualization tools in systems biology. PMID:18793134

  17. Program Computes Thermodynamic Functions

    NASA Technical Reports Server (NTRS)

    Mcbride, Bonnie J.; Gordon, Sanford

    1994-01-01

    PAC91 is latest in PAC (Properties and Coefficients) series. Two principal features are to provide means of (1) generating theoretical thermodynamic functions from molecular constants and (2) least-squares fitting of these functions to empirical equations. PAC91 written in FORTRAN 77 to be machine-independent.

  18. Symbolic functions from neural computation.

    PubMed

    Smolensky, Paul

    2012-07-28

    Is thought computation over ideas? Turing, and many cognitive scientists since, have assumed so, and formulated computational systems in which meaningful concepts are encoded by symbols which are the objects of computation. Cognition has been carved into parts, each a function defined over such symbols. This paper reports on a research program aimed at computing these symbolic functions without computing over the symbols. Symbols are encoded as patterns of numerical activation over multiple abstract neurons, each neuron simultaneously contributing to the encoding of multiple symbols. Computation is carried out over the numerical activation values of such neurons, which individually have no conceptual meaning. This is massively parallel numerical computation operating within a continuous computational medium. The paper presents an axiomatic framework for such a computational account of cognition, including a number of formal results. Within the framework, a class of recursive symbolic functions can be computed. Formal languages defined by symbolic rewrite rules can also be specified, the subsymbolic computations producing symbolic outputs that simultaneously display central properties of both facets of human language: universal symbolic grammatical competence and statistical, imperfect performance.

  19. [Progress in molecular biology study of DNA computer].

    PubMed

    Zhang, Zhi-Zhou; Zhao, Jian; He, Lin

    2003-09-01

    DNA (deoxyribonucleotide acids) computer is an emerging new study area that basically combines molecular biology study of DNA molecules and computational study on how to employ these specific molecules to calculate. In 1994 Adleman described his pioneering research on DNA computing in Science. This is the first experimental report on DNA computer study. In 2001 Benenson et al published a paper in Nature regarding a programmable and autonomous DNA computing device. Because of its Turing-like functions, the device is regarded as another milestone progress for DNA computer study. The main features of DNA computer are massively parallel computing ability and potential enormous data storage capacity. Comparing with conventional electronic computers, DNA molecules provide conceptually a revolution in computing, and more and more implications have been found in various disciplines. DNA computer studies have brought great progress not only in its own computing mechanisms, but also in DNA manipulation technologies especially nano-technology. This article presents the basic principles of DNA computer, its applications, its important relationship with genomic research and our comments on all above issues.

  20. A new online computational biology curriculum.

    PubMed

    Searls, David B

    2014-06-01

    A recent proliferation of Massive Open Online Courses (MOOCs) and other web-based educational resources has greatly increased the potential for effective self-study in many fields. This article introduces a catalog of several hundred free video courses of potential interest to those wishing to expand their knowledge of bioinformatics and computational biology. The courses are organized into eleven subject areas modeled on university departments and are accompanied by commentary and career advice.

  1. Computational Biology: Modeling Chronic Renal Allograft Injury

    PubMed Central

    Stegall, Mark D.; Borrows, Richard

    2015-01-01

    New approaches are needed to develop more effective interventions to prevent long-term rejection of organ allografts. Computational biology provides a powerful tool to assess the large amount of complex data that is generated in longitudinal studies in this area. This manuscript outlines how our two groups are using mathematical modeling to analyze predictors of graft loss using both clinical and experimental data and how we plan to expand this approach to investigate specific mechanisms of chronic renal allograft injury. PMID:26284070

  2. A New Online Computational Biology Curriculum

    PubMed Central

    Searls, David B.

    2014-01-01

    A recent proliferation of Massive Open Online Courses (MOOCs) and other web-based educational resources has greatly increased the potential for effective self-study in many fields. This article introduces a catalog of several hundred free video courses of potential interest to those wishing to expand their knowledge of bioinformatics and computational biology. The courses are organized into eleven subject areas modeled on university departments and are accompanied by commentary and career advice. PMID:24921255

  3. Computational systems biology in cancer brain metastasis.

    PubMed

    Peng, Huiming; Tan, Hua; Zhao, Weiling; Jin, Guangxu; Sharma, Sambad; Xing, Fei; Watabe, Kounosuke; Zhou, Xiaobo

    2016-01-01

    Brain metastases occur in 20-40% of patients with advanced malignancies. A better understanding of the mechanism of this disease will help us to identify novel therapeutic strategies. In this review, we will discuss the systems biology approaches used in this area, including bioinformatics and mathematical modeling. Bioinformatics has been used for identifying the molecular mechanisms driving brain metastasis and mathematical modeling methods for analyzing dynamics of a system and predicting optimal therapeutic strategies. We will illustrate the strategies, procedures, and computational techniques used for studying systems biology in cancer brain metastases. We will give examples on how to use a systems biology approach to analyze a complex disease. Some of the approaches used to identify relevant networks, pathways, and possibly biomarkers in metastasis will be reviewed into details. Finally, certain challenges and possible future directions in this area will also be discussed.

  4. The case for biological quantum computer elements

    NASA Astrophysics Data System (ADS)

    Baer, Wolfgang; Pizzi, Rita

    2009-05-01

    An extension to vonNeumann's analysis of quantum theory suggests self-measurement is a fundamental process of Nature. By mapping the quantum computer to the brain architecture we will argue that the cognitive experience results from a measurement of a quantum memory maintained by biological entities. The insight provided by this mapping suggests quantum effects are not restricted to small atomic and nuclear phenomena but are an integral part of our own cognitive experience and further that the architecture of a quantum computer system parallels that of a conscious brain. We will then review the suggestions for biological quantum elements in basic neural structures and address the de-coherence objection by arguing for a self- measurement event model of Nature. We will argue that to first order approximation the universe is composed of isolated self-measurement events which guaranties coherence. Controlled de-coherence is treated as the input/output interactions between quantum elements of a quantum computer and the quantum memory maintained by biological entities cognizant of the quantum calculation results. Lastly we will present stem-cell based neuron experiments conducted by one of us with the aim of demonstrating the occurrence of quantum effects in living neural networks and discuss future research projects intended to reach this objective.

  5. Computational Models for Neuromuscular Function

    PubMed Central

    Valero-Cuevas, Francisco J.; Hoffmann, Heiko; Kurse, Manish U.; Kutch, Jason J.; Theodorou, Evangelos A.

    2011-01-01

    Computational models of the neuromuscular system hold the potential to allow us to reach a deeper understanding of neuromuscular function and clinical rehabilitation by complementing experimentation. By serving as a means to distill and explore specific hypotheses, computational models emerge from prior experimental data and motivate future experimental work. Here we review computational tools used to understand neuromuscular function including musculoskeletal modeling, machine learning, control theory, and statistical model analysis. We conclude that these tools, when used in combination, have the potential to further our understanding of neuromuscular function by serving as a rigorous means to test scientific hypotheses in ways that complement and leverage experimental data. PMID:21687779

  6. PERSPECTIVE: From computational quantum chemistry to computational biology: experiments and computations are (full) partners

    NASA Astrophysics Data System (ADS)

    Ma, Buyong; Nussinov, Ruth

    2004-12-01

    Computations are being integrated into biological research at an increasingly fast pace. This has not only changed the way in which biological information is managed; it has also changed the way in which experiments are planned in order to obtain information from nature. Can experiments and computations be full partners? Computational chemistry has expanded over the years, proceeding from computations of a hydrogen molecule toward the challenging goal of systems biology, which attempts to handle the entire living cell. Applying theories from ab initio quantum mechanics to simplified models, the virtual worlds explored by computations provide replicas of real-world phenomena. At the same time, the virtual worlds can affect our perception of the real world. Computational biology targets a world of complex organization, for which a unified theory is unlikely to exist. A computational biology model, even if it has a clear physical or chemical basis, may not reduce to physics and chemistry. At the molecular level, computational biology and experimental biology have already been partners, mutually benefiting from each other. For the perception to become reality, computation and experiment should be united as full partners in biological research.

  7. Mathematical and Computational Modeling in Complex Biological Systems

    PubMed Central

    Li, Wenyang; Zhu, Xiaoliang

    2017-01-01

    The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

  8. Automatic computation of transfer functions

    DOEpatents

    Atcitty, Stanley; Watson, Luke Dale

    2015-04-14

    Technologies pertaining to the automatic computation of transfer functions for a physical system are described herein. The physical system is one of an electrical system, a mechanical system, an electromechanical system, an electrochemical system, or an electromagnetic system. A netlist in the form of a matrix comprises data that is indicative of elements in the physical system, values for the elements in the physical system, and structure of the physical system. Transfer functions for the physical system are computed based upon the netlist.

  9. Computational Tools to Assess Turbine Biological Performance

    SciTech Connect

    Richmond, Marshall C.; Serkowski, John A.; Rakowski, Cynthia L.; Strickler, Brad; Weisbeck, Molly; Dotson, Curtis L.

    2014-07-24

    Public Utility District No. 2 of Grant County (GCPUD) operates the Priest Rapids Dam (PRD), a hydroelectric facility on the Columbia River in Washington State. The dam contains 10 Kaplan-type turbine units that are now more than 50 years old. Plans are underway to refit these aging turbines with new runners. The Columbia River at PRD is a migratory pathway for several species of juvenile and adult salmonids, so passage of fish through the dam is a major consideration when upgrading the turbines. In this paper, a method for turbine biological performance assessment (BioPA) is demonstrated. Using this method, a suite of biological performance indicators is computed based on simulated data from a CFD model of a proposed turbine design. Each performance indicator is a measure of the probability of exposure to a certain dose of an injury mechanism. Using known relationships between the dose of an injury mechanism and frequency of injury (dose–response) from laboratory or field studies, the likelihood of fish injury for a turbine design can be computed from the performance indicator. By comparing the values of the indicators from proposed designs, the engineer can identify the more-promising alternatives. We present an application of the BioPA method for baseline risk assessment calculations for the existing Kaplan turbines at PRD that will be used as the minimum biological performance that a proposed new design must achieve.

  10. Functional Programming in Computer Science

    SciTech Connect

    Anderson, Loren James; Davis, Marion Kei

    2016-01-19

    We explore functional programming through a 16-week internship at Los Alamos National Laboratory. Functional programming is a branch of computer science that has exploded in popularity over the past decade due to its high-level syntax, ease of parallelization, and abundant applications. First, we summarize functional programming by listing the advantages of functional programming languages over the usual imperative languages, and we introduce the concept of parsing. Second, we discuss the importance of lambda calculus in the theory of functional programming. Lambda calculus was invented by Alonzo Church in the 1930s to formalize the concept of effective computability, and every functional language is essentially some implementation of lambda calculus. Finally, we display the lasting products of the internship: additions to a compiler and runtime system for the pure functional language STG, including both a set of tests that indicate the validity of updates to the compiler and a compiler pass that checks for illegal instances of duplicate names.

  11. Developing an online programme in computational biology.

    PubMed

    Vincent, Heather M; Page, Christopher

    2013-11-01

    Much has been written about the need for continuing education and training to enable life scientists and computer scientists to manage and exploit the different types of biological data now becoming available. Here we describe the development of an online programme that combines short training courses, so that those who require an educational programme can progress to complete a formal qualification. Although this flexible approach fits the needs of course participants, it does not fit easily within the organizational structures of a campus-based university.

  12. Multiobjective optimization in bioinformatics and computational biology.

    PubMed

    Handl, Julia; Kell, Douglas B; Knowles, Joshua

    2007-01-01

    This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.

  13. Principles for modeling and functional simulation of biological microstructures

    NASA Astrophysics Data System (ADS)

    Kriete, Andres

    1997-04-01

    This paper discusses some aspects of computer based modeling of biological microstructures. The workflow tom model and simulate a biological structure is described as a feedback- loop. Beside the system definition by structural and dynamical properties, the simulation is discussed as a mathematical representation coupled with a computer visualization. As an example, the investigation of the functional behavior of lung structures is described with special emphasis to the modeling of respiratory units.

  14. A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

    SciTech Connect

    James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew

    2013-10-01

    The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

  15. Systems Biology in Immunology – A Computational Modeling Perspective

    PubMed Central

    Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra; Fraser, Iain D. C.

    2011-01-01

    Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and conduct simulations of immune function, We provide descriptions of the key data gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease. PMID:21219182

  16. Computer Experiments for Function Approximations

    SciTech Connect

    Chang, A; Izmailov, I; Rizzo, S; Wynter, S; Alexandrov, O; Tong, C

    2007-10-15

    This research project falls in the domain of response surface methodology, which seeks cost-effective ways to accurately fit an approximate function to experimental data. Modeling and computer simulation are essential tools in modern science and engineering. A computer simulation can be viewed as a function that receives input from a given parameter space and produces an output. Running the simulation repeatedly amounts to an equivalent number of function evaluations, and for complex models, such function evaluations can be very time-consuming. It is then of paramount importance to intelligently choose a relatively small set of sample points in the parameter space at which to evaluate the given function, and then use this information to construct a surrogate function that is close to the original function and takes little time to evaluate. This study was divided into two parts. The first part consisted of comparing four sampling methods and two function approximation methods in terms of efficiency and accuracy for simple test functions. The sampling methods used were Monte Carlo, Quasi-Random LP{sub {tau}}, Maximin Latin Hypercubes, and Orthogonal-Array-Based Latin Hypercubes. The function approximation methods utilized were Multivariate Adaptive Regression Splines (MARS) and Support Vector Machines (SVM). The second part of the study concerned adaptive sampling methods with a focus on creating useful sets of sample points specifically for monotonic functions, functions with a single minimum and functions with a bounded first derivative.

  17. Computational Biology Support: RECOMB Conference Series (Conference Support)

    SciTech Connect

    Michael Waterman

    2006-06-15

    This funding was support for student and postdoctoral attendance at the Annual Recomb Conference from 2001 to 2005. The RECOMB Conference series was founded in 1997 to provide a scientific forum for theoretical advances in computational biology and their applications in molecular biology and medicine. The conference series aims at attracting research contributions in all areas of computational molecular biology. Typical, but not exclusive, the topics of interest are: Genomics, Molecular sequence analysis, Recognition of genes and regulatory elements, Molecular evolution, Protein structure, Structural genomics, Gene Expression, Gene Networks, Drug Design, Combinatorial libraries, Computational proteomics, and Structural and functional genomics. The origins of the conference came from the mathematical and computational side of the field, and there remains to be a certain focus on computational advances. However, the effective use of computational techniques to biological innovation is also an important aspect of the conference. The conference had a growing number of attendees, topping 300 in recent years and often exceeding 500. The conference program includes between 30 and 40 contributed papers, that are selected by a international program committee with around 30 experts during a rigorous review process rivaling the editorial procedure for top-rate scientific journals. In previous years papers selection has been made from up to 130--200 submissions from well over a dozen countries. 10-page extended abstracts of the contributed papers are collected in a volume published by ACM Press and Springer, and are available at the conference. Full versions of a selection of the papers are published annually in a special issue of the Journal of Computational Biology devoted to the RECOMB Conference. A further point in the program is a lively poster session. From 120-300 posters have been presented each year at RECOMB 2000. One of the highlights of each RECOMB conference is a

  18. Computational design of digital and memory biological devices

    PubMed Central

    Rodrigo, Guillermo

    2008-01-01

    The use of combinatorial optimization techniques with computational design allows the development of automated methods to design biological systems. Automatic design integrates design principles in an unsupervised algorithm to sample a larger region of the biological network space, at the topology and parameter levels. The design of novel synthetic transcriptional networks with targeted behaviors will be key to understand the design principles underlying biological networks. In this work, we evolve transcriptional networks towards a targeted dynamics, by using a library of promoters and coding sequences, to design a complex biological memory device. The designed sequential transcription network implements a JK-Latch, which is fully predictable and richer than other memory devices. Furthermore, we present designs of transcriptional devices behaving as logic gates, and we show how to create digital behavior from analog promoters. Our procedure allows us to propose a scenario for the evolution of multi-functional genetic networks. In addition, we discuss the decomposability of regulatory networks in terms of genetic modules to develop a given cellular function. Summary. We show how to use an automated procedure to design logic and sequential transcription circuits. This methodology will allow advancing the rational design of biological devices to more complex systems, and we propose the first design of a biological JK-latch memory device. Electronic supplementary material The online version of this article (doi:10.1007/s11693-008-9017-0) contains supplementary material, which is available to authorized users. PMID:19003443

  19. Natural computing and biological evolution: a new paradigm.

    PubMed

    Giuditta, Antonio

    2008-01-01

    After a brief outline of the available hypotheses on the mechanism of biological evolution, attention is called on the global nature of the variations leading to the generation of new species. Integrated changes may hardly be attributed to beneficial random mutations of single traits even if assisted by a phylogenetic elimination of poorly adapted individuals. Rather, integrated variations are likely to reflect the outcome of cybernetic algorithms (natural computing) operating on organism's resources and impending environmental changes. As all organisms are endowed with computing capacities that modulate and integrate ontogenetic development and maintenance of biological functions, structures, and behaviors, these capacities are assumed to have moulded the evolutionary variations of organisms, and their transfer to the progeny.

  20. Reinforcement learning: Computational theory and biological mechanisms.

    PubMed

    Doya, Kenji

    2007-05-01

    Reinforcement learning is a computational framework for an active agent to learn behaviors on the basis of a scalar reward signal. The agent can be an animal, a human, or an artificial system such as a robot or a computer program. The reward can be food, water, money, or whatever measure of the performance of the agent. The theory of reinforcement learning, which was developed in an artificial intelligence community with intuitions from animal learning theory, is now giving a coherent account on the function of the basal ganglia. It now serves as the "common language" in which biologists, engineers, and social scientists can exchange their problems and findings. This article reviews the basic theoretical framework of reinforcement learning and discusses its recent and future contributions toward the understanding of animal behaviors and human decision making.

  1. FUNCTION GENERATOR FOR ANALOGUE COMPUTERS

    DOEpatents

    Skramstad, H.K.; Wright, J.H.; Taback, L.

    1961-12-12

    An improved analogue computer is designed which can be used to determine the final ground position of radioactive fallout particles in an atomic cloud. The computer determines the fallout pattern on the basis of known wind velocity and direction at various altitudes, and intensity of radioactivity in the mushroom cloud as a function of particle size and initial height in the cloud. The output is then displayed on a cathode-ray tube so that the average or total luminance of the tube screen at any point represents the intensity of radioactive fallout at the geographical location represented by that point. (AEC)

  2. Applications of large-scale density functional theory in biology

    NASA Astrophysics Data System (ADS)

    Cole, Daniel J.; Hine, Nicholas D. M.

    2016-10-01

    Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

  3. First Steps in Computational Systems Biology: A Practical Session in Metabolic Modeling and Simulation

    ERIC Educational Resources Information Center

    Reyes-Palomares, Armando; Sanchez-Jimenez, Francisca; Medina, Miguel Angel

    2009-01-01

    A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever…

  4. Integrating Functional, Developmental and Evolutionary Biology into Biology Curricula

    ERIC Educational Resources Information Center

    Haave, Neil

    2012-01-01

    A complete understanding of life involves how organisms are able to function in their environment and how they arise. Understanding how organisms arise involves both their evolution and development. Thus to completely comprehend living things, biology must study their function, development and evolution. Previous proposals for standardized…

  5. Coarse-graining methods for computational biology.

    PubMed

    Saunders, Marissa G; Voth, Gregory A

    2013-01-01

    Connecting the molecular world to biology requires understanding how molecular-scale dynamics propagate upward in scale to define the function of biological structures. To address this challenge, multiscale approaches, including coarse-graining methods, become necessary. We discuss here the theoretical underpinnings and history of coarse-graining and summarize the state of the field, organizing key methodologies based on an emerging paradigm for multiscale theory and modeling of biomolecular systems. This framework involves an integrated, iterative approach to couple information from different scales. The primary steps, which coincide with key areas of method development, include developing first-pass coarse-grained models guided by experimental results, performing numerous large-scale coarse-grained simulations, identifying important interactions that drive emergent behaviors, and finally reconnecting to the molecular scale by performing all-atom molecular dynamics simulations guided by the coarse-grained results. The coarse-grained modeling can then be extended and refined, with the entire loop repeated iteratively if necessary.

  6. Computational complexity of Boolean functions

    NASA Astrophysics Data System (ADS)

    Korshunov, Aleksei D.

    2012-02-01

    Boolean functions are among the fundamental objects of discrete mathematics, especially in those of its subdisciplines which fall under mathematical logic and mathematical cybernetics. The language of Boolean functions is convenient for describing the operation of many discrete systems such as contact networks, Boolean circuits, branching programs, and some others. An important parameter of discrete systems of this kind is their complexity. This characteristic has been actively investigated starting from Shannon's works. There is a large body of scientific literature presenting many fundamental results. The purpose of this survey is to give an account of the main results over the last sixty years related to the complexity of computation (realization) of Boolean functions by contact networks, Boolean circuits, and Boolean circuits without branching. Bibliography: 165 titles.

  7. A complex systems approach to computational molecular biology

    SciTech Connect

    Lapedes, A. |

    1993-09-01

    We report on the containing research program at Santa Fe Institute that applies complex systems methodology to computational molecular biology. Two aspects are stressed here are the use of co-evolving adaptive neutral networks for determining predictable protein structure classifications, and the use of information theory to elucidate protein structure and function. A ``snapshot`` of the current state of research in these two topics is presented, representing the present state of two major research thrusts in the program of Genetic Data and Sequence Analysis at the Santa Fe Institute.

  8. 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.

  9. A first attempt to bring computational biology into advanced high school biology classrooms.

    PubMed

    Gallagher, Suzanne Renick; Coon, William; Donley, Kristin; Scott, Abby; Goldberg, Debra S

    2011-10-01

    Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of growing concern to the computational biology community and biology teachers who would like to acquaint their students with updated approaches in the discipline. We present a first attempt to correct this absence by introducing a computational biology element to teach genetic evolution into advanced biology classes in two local high schools. Our primary goal was to show students how computation is used in biology and why a basic understanding of computation is necessary for research in many fields of biology. This curriculum is intended to be taught by a computational biologist who has worked with a high school advanced biology teacher to adapt the unit for his/her classroom, but a motivated high school teacher comfortable with mathematics and computing may be able to teach this alone. In this paper, we present our curriculum, which takes into consideration the constraints of the required curriculum, and discuss our experiences teaching it. We describe the successes and challenges we encountered while bringing this unit to high school students, discuss how we addressed these challenges, and make suggestions for future versions of this curriculum.We believe that our curriculum can be a valuable seed for further development of computational activities aimed at high school biology students. Further, our experiences may be of value to others teaching computational biology at this level. Our curriculum can be obtained at http://ecsite.cs.colorado.edu/?page_id=149#biology or by contacting the authors.

  10. Computer-Based Semantic Network in Molecular Biology: A Demonstration.

    ERIC Educational Resources Information Center

    Callman, Joshua L.; And Others

    This paper analyzes the hardware and software features that would be desirable in a computer-based semantic network system for representing biology knowledge. It then describes in detail a prototype network of molecular biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…

  11. Functional Translational Readthrough: A Systems Biology Perspective

    PubMed Central

    Schueren, Fabian

    2016-01-01

    Translational readthrough (TR) has come into renewed focus because systems biology approaches have identified the first human genes undergoing functional translational readthrough (FTR). FTR creates functional extensions to proteins by continuing translation of the mRNA downstream of the stop codon. Here we review recent developments in TR research with a focus on the identification of FTR in humans and the systems biology methods that have spurred these discoveries. PMID:27490485

  12. Computational cell biology at the home of the helix.

    PubMed

    Ward, Jonathan J; Nédélec, Francois J

    2010-06-01

    The Computational Cell Biology Conference, held jointly by the Cold Spring Harbor Laboratory and the Wellcome Trust, was convened in the grand surroundings of Hinxton Hall near Cambridge, UK. The high quality of the research presented at the meeting confirmed that the field of computational cell biology is maturing rapidly, which mirrors the progression of cell biology from being mostly descriptive to a more quantitative discipline.

  13. Function-Based Algorithms for Biological Sequences

    ERIC Educational Resources Information Center

    Mohanty, Pragyan Sheela P.

    2015-01-01

    Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…

  14. ADVANCED COMPUTATIONAL METHODS IN DOSE MODELING: APPLICATION OF COMPUTATIONAL BIOPHYSICAL TRANSPORT, COMPUTATIONAL CHEMISTRY, AND COMPUTATIONAL BIOLOGY

    EPA Science Inventory

    Computational toxicology (CompTox) leverages the significant gains in computing power and computational techniques (e.g., numerical approaches, structure-activity relationships, bioinformatics) realized over the last few years, thereby reducing costs and increasing efficiency i...

  15. The biological microprocessor, or how to build a computer with biological parts

    PubMed Central

    Moe-Behrens, Gerd HG

    2013-01-01

    Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system. PMID:24688733

  16. [Comparison study between biological vision and computer vision].

    PubMed

    Liu, W; Yuan, X G; Yang, C X; Liu, Z Q; Wang, R

    2001-08-01

    The development and bearing of biology vision in structure and mechanism were discussed, especially on the aspects including anatomical structure of biological vision, tentative classification of reception field, parallel processing of visual information, feedback and conformity effect of visual cortical, and so on. The new advance in the field was introduced through the study of the morphology of biological vision. Besides, comparison between biological vision and computer vision was made, and their similarities and differences were pointed out.

  17. Data-intensive computing laying foundation for biological breakthroughs

    SciTech Connect

    Hachigian, David J.

    2007-06-18

    Finding a different way is the goal of the Data-Intensive Computing for Complex Biological Systems (Biopilot) project—a joint research effort between the Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory funded by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. The two national laboratories, both of whom are world leaders in computing and computational sciences, are teaming to support areas of biological research in urgent need of data-intensive computing capabilities.

  18. Modeling Functional Motions of Biological Systems by Customized Natural Moves.

    PubMed

    Demharter, Samuel; Knapp, Bernhard; Deane, Charlotte M; Minary, Peter

    2016-08-23

    Simulating the functional motions of biomolecular systems requires large computational resources. We introduce a computationally inexpensive protocol for the systematic testing of hypotheses regarding the dynamic behavior of proteins and nucleic acids. The protocol is based on natural move Monte Carlo, a highly efficient conformational sampling method with built-in customization capabilities that allows researchers to design and perform a large number of simulations to investigate functional motions in biological systems. We demonstrate the use of this protocol on both a protein and a DNA case study. Firstly, we investigate the plasticity of a class II major histocompatibility complex in the absence of a bound peptide. Secondly, we study the effects of the epigenetic mark 5-hydroxymethyl on cytosine on the structure of the Dickerson-Drew dodecamer. We show how our customized natural moves protocol can be used to investigate causal relationships of functional motions in biological systems.

  19. Session on computation in biological pathways

    SciTech Connect

    Karp, P.D.; Riley, M.

    1996-12-31

    The papers in this session focus on the development of pathway databases and computational tools for pathway analysis. The discussion involves existing databases of sequenced genomes, as well as techniques for studying regulatory pathways.

  20. Computing Functions by Approximating the Input

    ERIC Educational Resources Information Center

    Goldberg, Mayer

    2012-01-01

    In computing real-valued functions, it is ordinarily assumed that the input to the function is known, and it is the output that we need to approximate. In this work, we take the opposite approach: we show how to compute the values of some transcendental functions by approximating the input to these functions, and obtaining exact answers for their…

  1. UC Merced Center for Computational Biology Final Report

    SciTech Connect

    Colvin, Michael; Watanabe, Masakatsu

    2010-11-30

    Final report for the UC Merced Center for Computational Biology. The Center for Computational Biology (CCB) was established to support multidisciplinary scientific research and academic programs in computational biology at the new University of California campus in Merced. In 2003, the growing gap between biology research and education was documented in a report from the National Academy of Sciences, Bio2010 Transforming Undergraduate Education for Future Research Biologists. We believed that a new type of biological sciences undergraduate and graduate programs that emphasized biological concepts and considered biology as an information science would have a dramatic impact in enabling the transformation of biology. UC Merced as newest UC campus and the first new U.S. research university of the 21st century was ideally suited to adopt an alternate strategy - to create a new Biological Sciences majors and graduate group that incorporated the strong computational and mathematical vision articulated in the Bio2010 report. CCB aimed to leverage this strong commitment at UC Merced to develop a new educational program based on the principle of biology as a quantitative, model-driven science. Also we expected that the center would be enable the dissemination of computational biology course materials to other university and feeder institutions, and foster research projects that exemplify a mathematical and computations-based approach to the life sciences. As this report describes, the CCB has been successful in achieving these goals, and multidisciplinary computational biology is now an integral part of UC Merced undergraduate, graduate and research programs in the life sciences. The CCB began in fall 2004 with the aid of an award from U.S. Department of Energy (DOE), under its Genomes to Life program of support for the development of research and educational infrastructure in the modern biological sciences. This report to DOE describes the research and academic programs

  2. Modelling, abstraction, and computation in systems biology: A view from computer science.

    PubMed

    Melham, Tom

    2013-04-01

    Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology.

  3. Computational Modeling, Formal Analysis, and Tools for Systems Biology

    PubMed Central

    Bartocci, Ezio; Lió, Pietro

    2016-01-01

    As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science. PMID:26795950

  4. Excellence in Computational Biology and Informatics — EDRN Public Portal

    Cancer.gov

    9th Early Detection Research Network (EDRN) Scientific Workshop. Excellence in Computational Biology and Informatics: Sponsored by the EDRN Data Sharing Subcommittee Moderator: Daniel Crichton, M.S., NASA Jet Propulsion Laboratory

  5. Data-intensive computing laying foundation for biological breakthroughs

    SciTech Connect

    Straatsma, TP

    2007-06-18

    Biological breakthroughs critical to solving society’s most challenging problems require new and innovative tools and a “different way” to analyze the enormous amounts of data being generated. This article for the Breakthroughs magazine focuses on the Data-Intensive Computing for Complex Biological Systems (Biopilot) project—a joint research effort between the Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory funded by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. The two national laboratories, both of whom are world leaders in computing and computational sciences, are teaming to support areas of biological research in urgent need of data-intensive computing capabilities.

  6. Computer Modelling of Biological Molecules: Free Resources on the Internet.

    ERIC Educational Resources Information Center

    Millar, Neil

    1996-01-01

    Describes a three-dimensional computer modeling system for biological molecules which is suitable for sixth-form teaching. Consists of the modeling program "RasMol" together with structure files of proteins, DNA, and small biological molecules. Describes how the whole system can be downloaded from various sites on the Internet.…

  7. First steps in computational systems biology: A practical session in metabolic modeling and simulation.

    PubMed

    Reyes-Palomares, Armando; Sánchez-Jiménez, Francisca; Medina, Miguel Ángel

    2009-05-01

    A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever faster numerical simulations of mathematical models. Mathematical modeling plays an essential role in new systems biology approaches. As a complex, integrated system, metabolism is a suitable topic of study for systems biology approaches. However, up until recently, this topic has not been properly covered in biochemistry courses. This communication reports the development and implementation of a practical lesson plan on metabolic modeling and simulation.

  8. Using a Computer Animation to Teach High School Molecular Biology

    ERIC Educational Resources Information Center

    Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth

    2008-01-01

    We present an active way to use a computer animation in secondary molecular genetics class. For this purpose we developed an activity booklet that helps students to work interactively with a computer animation which deals with abstract concepts and processes in molecular biology. The achievements of the experimental group were compared with those…

  9. Computer display and manipulation of biological molecules

    NASA Technical Reports Server (NTRS)

    Coeckelenbergh, Y.; Macelroy, R. D.; Hart, J.; Rein, R.

    1978-01-01

    This paper describes a computer model that was designed to investigate the conformation of molecules, macromolecules and subsequent complexes. Utilizing an advanced 3-D dynamic computer display system, the model is sufficiently versatile to accommodate a large variety of molecular input and to generate data for multiple purposes such as visual representation of conformational changes, and calculation of conformation and interaction energy. Molecules can be built on the basis of several levels of information. These include the specification of atomic coordinates and connectivities and the grouping of building blocks and duplicated substructures using symmetry rules found in crystals and polymers such as proteins and nucleic acids. Called AIMS (Ames Interactive Molecular modeling System), the model is now being used to study pre-biotic molecular evolution toward life.

  10. The computational linguistics of biological sequences

    SciTech Connect

    Searls, D.

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Protein sequences are analogous in many respects, particularly their folding behavior. Proteins have a much richer variety of interactions, but in theory the same linguistic principles could come to bear in describing dependencies between distant residues that arise by virtue of three-dimensional structure. This tutorial will concentrate on nucleic acid sequences.

  11. [Biological functions of tin and disease].

    PubMed

    Arakawa, Yasuaki; Tomiyama, Kenichi

    2016-07-01

    Tin generates a wide variety of biological functions due to its chemical character. In this article, the modes of the biological functions of tin(especially organotin compounds) are reviewed, with special emphasis on the connection with the immune system, brain nervous system and endocrine system, on the basis of our data. To sum up this article, the biological functions of organotin compounds appear to be due to the following several processes: (1) their incorporation into the cells in vesicle form through fusion or in a similar manner to their incorporation in cationic form; (2) transport to and accumulation in the regions of the Golgi apparatus and endoplasmic reticulum (ER), but not to or in the plasma membrane or nucleus because of their hydrophobicity; (3) inhibition of intracellular phospholipid transport between organelles due to impairment of the structures and functions of the Golgi apparatus and ER; (4) inhibition of the membrane-mediated signal transduction system leading to DNA synthesis via phospholipid turnover and Ca2+ mobilization, as in cell proliferation systems; (5) disturbance of the trace element balance and the localization of certain elements; (6) disorders of membrane-mediated Ca2+ homeostasis via various channel functions including Zn modulation on the plasma and organelle membranes, and protein phosphorylation, as in the signal transduction systems of memory and olfaction; (7) necrosis or apoptosis in vivo or toxic cell death in vitro.

  12. Secure encapsulation and publication of biological services in the cloud computing environment.

    PubMed

    Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

    2013-01-01

    Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

  13. Dynamics of biomolecules, ligand binding & biological functions

    NASA Astrophysics Data System (ADS)

    Yi, Myunggi

    Proteins are flexible and dynamic. One static structure alone does not often completely explain biological functions of the protein, and some proteins do not even have high resolution structures. In order to provide better understanding to the biological functions of nicotinic acetylcholine receptor, Diphtheria toxin repressor and M2 proton channel, the dynamics of these proteins are investigated using molecular modeling and molecular dynamics (MD) simulations. With absence of high resolution structure of alpha7 receptor, the homology models of apo and cobra toxin bound forms have been built. From the MD simulations of these model structures, we observed one subunit of apo simulation moved away from other four subunits. With local movement of flexible loop regions, the whole subunit tilted clockwise. These conformational changes occurred spontaneously, and were strongly correlated with the conformational change when the channel is activated by agonists. Unlike other computational studies, we directly compared our model of open conformation with the experimental data. However, the subunits of toxin bound form were stable, and conformational change is restricted by the bound cobra toxin. These results provide activation and inhibition mechanisms of alpha7 receptors and a possible explanation for intermediate conductance of the channel. Intramolecular complex of SH3-like domain with a proline-rich (Pr) peptide segment in Diphtheria toxin repressor (DtxR) is stabilized in inactive state. Upon activation of DtxR by transition metal binding, this intramolecular complex should be dissociated. The dynamics of this intramolecular complex is investigated using MD simulations and NMR spectroscopy. We observed spontaneous opening and closing motions of the Pr segment binding pockets in both Pr-SH3 and SH3 simulations. The MD simulation results and NMR relaxation data suggest that the Pr segment exhibits a binding ↔ unbinding equilibrium. Despite a wealth of experimental

  14. Novel opportunities for computational biology and sociology in drug discovery.

    PubMed

    Yao, Lixia; Evans, James A; Rzhetsky, Andrey

    2009-09-01

    Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.

  15. Novel opportunities for computational biology and sociology in drug discovery.

    PubMed

    Yao, Lixia; Evans, James A; Rzhetsky, Andrey

    2010-04-01

    Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development,explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery.These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use.Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies.

  16. Novel opportunities for computational biology and sociology in drug discovery☆

    PubMed Central

    Yao, Lixia; Evans, James A.; Rzhetsky, Andrey

    2013-01-01

    Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy–industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies. PMID:20349528

  17. Novel opportunities for computational biology and sociology in drug discovery

    PubMed Central

    Yao, Lixia

    2009-01-01

    Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801

  18. Phylogenetics and Computational Biology of Multigene Families

    NASA Astrophysics Data System (ADS)

    Liò, Pietro; Brilli, Matteo; Fani, Renato

    This chapter introduces the study of the major evolutionary forces operating in large gene families. The reconstruction of duplication history and phylogenetic analysis provide an interpretative framework of the evolution of multigene families. We present here two case studies, the first coming from Eukaryotes (chemokine receptors) and the second from Prokaryotes (TIM barrel proteins), showing how functional and structural constraints have shaped gene duplication events.

  19. Stochastic Effects in Computational Biology of Space Radiation Cancer Risk

    NASA Technical Reports Server (NTRS)

    Cucinotta, Francis A.; Pluth, Janis; Harper, Jane; O'Neill, Peter

    2007-01-01

    Estimating risk from space radiation poses important questions on the radiobiology of protons and heavy ions. We are considering systems biology models to study radiation induced repair foci (RIRF) at low doses, in which less than one-track on average transverses the cell, and the subsequent DNA damage processing and signal transduction events. Computational approaches for describing protein regulatory networks coupled to DNA and oxidative damage sites include systems of differential equations, stochastic equations, and Monte-Carlo simulations. We review recent developments in the mathematical description of protein regulatory networks and possible approaches to radiation effects simulation. These include robustness, which states that regulatory networks maintain their functions against external and internal perturbations due to compensating properties of redundancy and molecular feedback controls, and modularity, which leads to general theorems for considering molecules that interact through a regulatory mechanism without exchange of matter leading to a block diagonal reduction of the connecting pathways. Identifying rate-limiting steps, robustness, and modularity in pathways perturbed by radiation damage are shown to be valid techniques for reducing large molecular systems to realistic computer simulations. Other techniques studied are the use of steady-state analysis, and the introduction of composite molecules or rate-constants to represent small collections of reactants. Applications of these techniques to describe spatial and temporal distributions of RIRF and cell populations following low dose irradiation are described.

  20. Signal-to-Noise Ratio Measures Efficacy of Biological Computing Devices and Circuits

    PubMed Central

    Beal, Jacob

    2015-01-01

    Engineering biological cells to perform computations has a broad range of important potential applications, including precision medical therapies, biosynthesis process control, and environmental sensing. Implementing predictable and effective computation, however, has been extremely difficult to date, due to a combination of poor composability of available parts and of insufficient characterization of parts and their interactions with the complex environment in which they operate. In this paper, the author argues that this situation can be improved by quantitative signal-to-noise analysis of the relationship between computational abstractions and the variation and uncertainty endemic in biological organisms. This analysis takes the form of a ΔSNRdB function for each computational device, which can be computed from measurements of a device’s input/output curve and expression noise. These functions can then be combined to predict how well a circuit will implement an intended computation, as well as evaluating the general suitability of biological devices for engineering computational circuits. Applying signal-to-noise analysis to current repressor libraries shows that no library is currently sufficient for general circuit engineering, but also indicates key targets to remedy this situation and vastly improve the range of computations that can be used effectively in the implementation of biological applications. PMID:26177070

  1. Computing functions by approximating the input

    NASA Astrophysics Data System (ADS)

    Goldberg, Mayer

    2012-12-01

    In computing real-valued functions, it is ordinarily assumed that the input to the function is known, and it is the output that we need to approximate. In this work, we take the opposite approach: we show how to compute the values of some transcendental functions by approximating the input to these functions, and obtaining exact answers for their output. Our approach assumes only the most rudimentary knowledge of algebra and trigonometry, and makes no use of calculus.

  2. Functionalizing Electrospun Fibers with Biologically Relevant Macromolecules

    PubMed Central

    Casper, Cheryl L.; Yamaguchi, Nori; Kiick, Kristi L.; Rabolt, John F.

    2008-01-01

    The development of functionalized polymers that can elicit specific biological responses is of great interest in the biomedical community, as well as the development of methods to fabricate these biologically functionalized polymers. For example, the generation of fibrous matrices with biological properties and fiber diameters commensurate with those of the natural extracellular matrix (ECM) may permit the development of novel materials for use in wound healing or tissue engineering. The goal of this work is, therefore, to create a biologically active functionalized electrospun matrix to permit immobilization and long-term delivery of growth factors. In this work, poly(ethylene glycol) functionalized with low molecular weight heparin (PEG-LMWH) was fabricated into fibers for possible use in drug delivery, tissue engineering, or wound repair applications. Electrospinning was chosen to process the LMWH into fiber form due to the small fiber diameters and high degree of porosity that can be obtained relatively quickly and using small amounts of starting material. Both free LMWH and PEG-LMWH were investigated for their ability to be incorporated into electrospun fibers. Each of the samples were mixed with a carrier polymer consisting of either a 10 wt % poly(ethylene oxide) (PEO) or 45 wt % poly(lactide-co-glycolide) (PLGA). Field emission scanning electron microscopy (FESEM), energy-dispersive X-ray analysis (EDX), UV–vis spectroscopy, and multiphoton microscopy were used to characterize the electrospun matrices. The incorporation of heparin into the electrospun PEO and PLGA fibers did not affect the surface morphology or fiber diameters. The fibers produced had diameters ranging from approximately 100 to 400 nm. Toluidine blue assays of heparin suggest that it can be incorporated into an electrospun matrix at concentrations ranging from 3.5 to 85 μg per milligram of electrospun fibers. Multiphoton microscopy confirmed that incorporation of PEG-LMWH into the matrix

  3. Towards molecular computers that operate in a biological environment

    NASA Astrophysics Data System (ADS)

    Kahan, Maya; Gil, Binyamin; Adar, Rivka; Shapiro, Ehud

    2008-07-01

    important consequences when performed in a proper context. We envision that molecular computers that operate in a biological environment can be the basis of “smart drugs”, which are potent drugs that activate only if certain environmental conditions hold. These conditions could include abnormalities in the molecular composition of the biological environment that are indicative of a particular disease. Here we review the research direction that set this vision and attempts to realize it.

  4. [Computational radiofrequency electromagnetic field dosimetry in evaluation of biological effects].

    PubMed

    Perov, S Iu; Kudryashov, Iu B; Rubtsova, N B

    2012-01-01

    Given growing computational resources, radiofrequency electromagnetic field dosimetry is becoming more vital in the study of biological effects of non-ionizing electromagnetic radiation. The study analyzes numerical methods which are used in theoretical dosimetry to assess the exposure level and specific absorption rate distribution. The advances of theoretical dosimetry are shown. Advantages and disadvantages of different methods are analyzed in respect to electromagnetic field biological effects. The finite-difference time-domain method was implemented in detail; also evaluated were possible uncertainties of complex biological structure simulation for bioelectromagnetic investigations.

  5. Marine Carotenoids: Biological Functions and Commercial Applications

    PubMed Central

    Vílchez, Carlos; Forján, Eduardo; Cuaresma, María; Bédmar, Francisco; Garbayo, Inés; Vega, José M.

    2011-01-01

    Carotenoids are the most common pigments in nature and are synthesized by all photosynthetic organisms and fungi. Carotenoids are considered key molecules for life. Light capture, photosynthesis photoprotection, excess light dissipation and quenching of singlet oxygen are among key biological functions of carotenoids relevant for life on earth. Biological properties of carotenoids allow for a wide range of commercial applications. Indeed, recent interest in the carotenoids has been mainly for their nutraceutical properties. A large number of scientific studies have confirmed the benefits of carotenoids to health and their use for this purpose is growing rapidly. In addition, carotenoids have traditionally been used in food and animal feed for their color properties. Carotenoids are also known to improve consumer perception of quality; an example is the addition of carotenoids to fish feed to impart color to farmed salmon. PMID:21556162

  6. Aegerolysins: Structure, function, and putative biological role

    PubMed Central

    Berne, Sabina; Lah, Ljerka; Sepčić, Kristina

    2009-01-01

    Aegerolysins, discovered in fungi, bacteria and plants, are highly similar proteins with interesting biological properties. Certain aegerolysins possess antitumoral, antiproliferative, and antibacterial activities. Further possible medicinal applications include their use in the prevention of atherosclerosis, or as vaccines. Additional biotechnological value of fungal aegerolysins lies in their involvement in development, which could improve cultivation of commercially important edible mushrooms. Besides, new insights on microheterogeneity of raft-like membrane domains could be gained by using aegerolysins as specific markers in cell and molecular biology. Although the exact function of aegerolysins in their producing organisms remains to be explained, they are biochemically well characterized all-β structured proteins sharing the following common features: low isoelectric points, similar molecular weights (15–17 kDa), and stability in a wide pH range. PMID:19309687

  7. Marine carotenoids: biological functions and commercial applications.

    PubMed

    Vílchez, Carlos; Forján, Eduardo; Cuaresma, María; Bédmar, Francisco; Garbayo, Inés; Vega, José M

    2011-03-03

    Carotenoids are the most common pigments in nature and are synthesized by all photosynthetic organisms and fungi. Carotenoids are considered key molecules for life. Light capture, photosynthesis photoprotection, excess light dissipation and quenching of singlet oxygen are among key biological functions of carotenoids relevant for life on earth. Biological properties of carotenoids allow for a wide range of commercial applications. Indeed, recent interest in the carotenoids has been mainly for their nutraceutical properties. A large number of scientific studies have confirmed the benefits of carotenoids to health and their use for this purpose is growing rapidly. In addition, carotenoids have traditionally been used in food and animal feed for their color properties. Carotenoids are also known to improve consumer perception of quality; an example is the addition of carotenoids to fish feed to impart color to farmed salmon.

  8. Catalyzing Inquiry at the Interface of Computing and Biology

    SciTech Connect

    John Wooley; Herbert S. Lin

    2005-10-30

    This study is the first comprehensive NRC study that suggests a high-level intellectual structure for Federal agencies for supporting work at the biology/computing interface. The report seeks to establish the intellectual legitimacy of a fundamentally cross-disciplinary collaboration between biologists and computer scientists. That is, while some universities are increasingly favorable to research at the intersection, life science researchers at other universities are strongly impeded in their efforts to collaborate. This report addresses these impediments and describes proven strategies for overcoming them. An important feature of the report is the use of well-documented examples that describe clearly to individuals not trained in computer science the value and usage of computing across the biological sciences, from genes and proteins to networks and pathways, from organelles to cells, and from individual organisms to populations and ecosystems. It is hoped that these examples will be useful to students in the life sciences to motivate (continued) study in computer science that will enable them to be more facile users of computing in their future biological studies.

  9. [Structure and biologic function of IFNgamma].

    PubMed

    Nammous, Abdul Halim; Pietruczuk, Małgorzata; Zubacki, Dymitr; Dobrzycki, Ignacy

    2005-01-01

    IFNgamma is a pro-inflammatory, pleiotropic cytokine mainly produced by the CD4+, CD8+ lymphocytes and NK cells, that play an important role in macrophage activation, antigen presentation enhance and induce innate, and acquired immune responses. IFNgamma by interaction with they cell-surface receptors (IFNgammaR) activates cellular effects including stimulation of antiviral and antimicrobial mechanisms, inhibition of cellular proliferation, regulates cells apoptosis and leukocyte trafficing to sites of inflammation. The purpose of this article is to present the current understending of structure and biological function of IFNgamma in the light of current opinions regarding this matter.

  10. Biology Students Building Computer Simulations Using StarLogo TNG

    ERIC Educational Resources Information Center

    Smith, V. Anne; Duncan, Ishbel

    2011-01-01

    Confidence is an important issue for biology students in handling computational concepts. This paper describes a practical in which honours-level bioscience students simulate complex animal behaviour using StarLogo TNG, a freely-available graphical programming environment. The practical consists of two sessions, the first of which guides students…

  11. Filling the gap between biology and computer science.

    PubMed

    Aguilar-Ruiz, Jesús S; Moore, Jason H; Ritchie, Marylyn D

    2008-07-17

    This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biological data. We outline the aims and scope of the journal, introduce the publishing model and describe the open peer review policy, which fosters interaction within the research community.

  12. Evaluating Computer Lab Modules for Large Biology Courses.

    ERIC Educational Resources Information Center

    Eichinger, David C.; And Others

    This paper describes the first phase of a study to investigate students' evaluations of computer laboratory modules in a university-level, non-majors biology course. The National Science Foundation-funded project has two primary goals: (1) to develop programmable, multifunctional Bio LabStations for data collection and analysis, lab extensions,…

  13. Transcription factor binding energy vs. biological function

    NASA Astrophysics Data System (ADS)

    Djordjevic, M.; Grotewold, E.

    2007-03-01

    Transcription factors (TFs) are proteins that bind to DNA and regulate expression of genes. Identification of transcription factor binding sites within the regulatory segments of genomic DNA is an important step towards understanding of gene regulatory networks. Recent theoretical advances that we developed [1,2], allow us to infer TF-DNA interaction parameters from in-vitro selection experiments [3]. We use more than 6000 binding sequences [3], assembled under controlled conditions, to obtain protein-DNA interaction parameters for a mammalian TF with up to now unprecedented accuracy. Can one accurately identify biologically functional TF binding sites (i.e. the binding sites that regulate gene expression), even with the best possible protein-DNA interaction parameters? To address this issue we i) compare our prediction of protein binding with gene expression data, ii) use evolutionary comparison between related mammalian genomes. Our results strongly suggest that in a genome there exists a large number of randomly occurring high energy binding sites that are not biologically functional. [1] M Djordjevic, submitted to Biomol. Eng. [2] M. Djordjevic and A. M. Sengupta, Phys. Biol. 3: 13, 2006. [3] E. Roulet et al., Nature Biotech. 20: 831, 2002.

  14. Computational intelligence techniques for biological data mining: An overview

    NASA Astrophysics Data System (ADS)

    Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

    2014-10-01

    Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

  15. 10 years for the Journal of Bioinformatics and Computational Biology (2003-2013) -- a retrospective.

    PubMed

    Eisenhaber, Frank; Sherman, Westley Arthur

    2014-06-01

    The Journal of Bioinformatics and Computational Biology (JBCB) started publishing scientific articles in 2003. It has established itself as home for solid research articles in the field (~ 60 per year) that are surprisingly well cited. JBCB has an important function as alternative publishing channel in addition to other, bigger journals.

  16. Supporting Representational Competence in High School Biology with Computer-Based Biomolecular Visualizations

    ERIC Educational Resources Information Center

    Wilder, Anna; Brinkerhoff, Jonathan

    2007-01-01

    This study assessed the effectiveness of computer-based biomolecular visualization activities on the development of high school biology students' representational competence as a means of understanding and visualizing protein structure/function relationships. Also assessed were students' attitudes toward these activities. Sixty-nine students…

  17. On computation of Hough functions

    NASA Astrophysics Data System (ADS)

    Wang, Houjun; Boyd, John P.; Akmaev, Rashid A.

    2016-04-01

    Hough functions are the eigenfunctions of the Laplace tidal equation governing fluid motion on a rotating sphere with a resting basic state. Several numerical methods have been used in the past. In this paper, we compare two of those methods: normalized associated Legendre polynomial expansion and Chebyshev collocation. Both methods are not widely used, but both have some advantages over the commonly used unnormalized associated Legendre polynomial expansion method. Comparable results are obtained using both methods. For the first method we note some details on numerical implementation. The Chebyshev collocation method was first used for the Laplace tidal problem by Boyd (1976) and is relatively easy to use. A compact MATLAB code is provided for this method. We also illustrate the importance and effect of including a parity factor in Chebyshev polynomial expansions for modes with odd zonal wave numbers.

  18. Genomic Functionalization: The Next Revolution In Biology

    SciTech Connect

    Anderson, Peter; Schoeniger, Joseph S.; Imbro, Paula M.

    2014-07-01

    We have implemented a ligand-alignment algorithm into our developed computational pipeline for identifying specificity-determining features (SDFs) in protein-ligand complexes. Given a set of protein-ligand complex structures, the algorithm aligns the complexes by ligand rather than by the C -RMSD or standard approach, providing a single reference frame for extracting SDFs. We anticipate that this ligand-alignment capability will be highly useful for protein function prediction. We already have a database containing > 20 K ligand-protein complex crystal structures taken from the Protein Data Bank. By aligning these proteins to single reference frames using ligand alignment, we can submit the complexes to our pipeline for SDF extraction. The SDFs derived from this training procedure can be used as thumbprints that are hallmarks of individual enzyme classes. These SDF thumbprints may then serve as guides to the prediction of function of new unknown proteins.

  19. Computational Proteomics: High-throughput Analysis for Systems Biology

    SciTech Connect

    Cannon, William R.; Webb-Robertson, Bobbie-Jo M.

    2007-01-03

    High-throughput (HTP) proteomics is a rapidly developing field that offers the global profiling of proteins from a biological system. The HTP technological advances are fueling a revolution in biology, enabling analyses at the scales of entire systems (e.g., whole cells, tumors, or environmental communities). However, simply identifying the proteins in a cell is insufficient for understanding the underlying complexity and operating mechanisms of the overall system. Systems level investigations are relying more and more on computational analyses, especially in the field of proteomics generating large-scale global data.

  20. Perspectives on an education in computational biology and medicine.

    PubMed

    Rubinstein, Jill C

    2012-09-01

    The mainstream application of massively parallel, high-throughput assays in biomedical research has created a demand for scientists educated in Computational Biology and Bioinformatics (CBB). In response, formalized graduate programs have rapidly evolved over the past decade. Concurrently, there is increasing need for clinicians trained to oversee the responsible translation of CBB research into clinical tools. Physician-scientists with dedicated CBB training can facilitate such translation, positioning themselves at the intersection between computational biomedical research and medicine. This perspective explores key elements of the educational path to such a position, specifically addressing: 1) evolving perceptions of the role of the computational biologist and the impact on training and career opportunities; 2) challenges in and strategies for obtaining the core skill set required of a biomedical researcher in a computational world; and 3) how the combination of CBB with medical training provides a logical foundation for a career in academic medicine and/or biomedical research.

  1. Computational design of receptor and sensor proteins with novel functions

    NASA Astrophysics Data System (ADS)

    Looger, Loren L.; Dwyer, Mary A.; Smith, James J.; Hellinga, Homme W.

    2003-05-01

    The formation of complexes between proteins and ligands is fundamental to biological processes at the molecular level. Manipulation of molecular recognition between ligands and proteins is therefore important for basic biological studies and has many biotechnological applications, including the construction of enzymes, biosensors, genetic circuits, signal transduction pathways and chiral separations. The systematic manipulation of binding sites remains a major challenge. Computational design offers enormous generality for engineering protein structure and function. Here we present a structure-based computational method that can drastically redesign protein ligand-binding specificities. This method was used to construct soluble receptors that bind trinitrotoluene, L-lactate or serotonin with high selectivity and affinity. These engineered receptors can function as biosensors for their new ligands; we also incorporated them into synthetic bacterial signal transduction pathways, regulating gene expression in response to extracellular trinitrotoluene or L-lactate. The use of various ligands and proteins shows that a high degree of control over biomolecular recognition has been established computationally. The biological and biosensing activities of the designed receptors illustrate potential applications of computational design.

  2. Computational Neuroscience: Modeling the Systems Biology of Synaptic Plasticity

    PubMed Central

    Kotaleski, Jeanette Hellgren; Blackwell, Kim T.

    2016-01-01

    Preface Synaptic plasticity is a mechanism proposed to underlie learning and memory. The complexity of the interactions between ion channels, enzymes, and genes involved in synaptic plasticity impedes a deep understanding of this phenomenon. Computer modeling is an approach to investigate the information processing that is performed by signaling pathways underlying synaptic plasticity. In the past few years, new software developments that blend computational neuroscience techniques with systems biology techniques have allowed large-scale, quantitative modeling of synaptic plasticity in neurons. We highlight significant advancements produced by these modeling efforts and introduce promising approaches that utilize advancements in live cell imaging. PMID:20300102

  3. Computational intelligence approaches for pattern discovery in biological systems.

    PubMed

    Fogel, Gary B

    2008-07-01

    Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.

  4. A biological solution to a fundamental distributed computing problem.

    PubMed

    Afek, Yehuda; Alon, Noga; Barad, Omer; Hornstein, Eran; Barkai, Naama; Bar-Joseph, Ziv

    2011-01-14

    Computational and biological systems are often distributed so that processors (cells) jointly solve a task, without any of them receiving all inputs or observing all outputs. Maximal independent set (MIS) selection is a fundamental distributed computing procedure that seeks to elect a set of local leaders in a network. A variant of this problem is solved during the development of the fly's nervous system, when sensory organ precursor (SOP) cells are chosen. By studying SOP selection, we derived a fast algorithm for MIS selection that combines two attractive features. First, processors do not need to know their degree; second, it has an optimal message complexity while only using one-bit messages. Our findings suggest that simple and efficient algorithms can be developed on the basis of biologically derived insights.

  5. Exploiting graphics processing units for computational biology and bioinformatics.

    PubMed

    Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H

    2010-09-01

    Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.

  6. Bioconductor: open software development for computational biology and bioinformatics

    PubMed Central

    Gentleman, Robert C; Carey, Vincent J; Bates, Douglas M; Bolstad, Ben; Dettling, Marcel; Dudoit, Sandrine; Ellis, Byron; Gautier, Laurent; Ge, Yongchao; Gentry, Jeff; Hornik, Kurt; Hothorn, Torsten; Huber, Wolfgang; Iacus, Stefano; Irizarry, Rafael; Leisch, Friedrich; Li, Cheng; Maechler, Martin; Rossini, Anthony J; Sawitzki, Gunther; Smith, Colin; Smyth, Gordon; Tierney, Luke; Yang, Jean YH; Zhang, Jianhua

    2004-01-01

    The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples. PMID:15461798

  7. Topological properties of robust biological and computational networks.

    PubMed

    Navlakha, Saket; He, Xin; Faloutsos, Christos; Bar-Joseph, Ziv

    2014-07-06

    Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields.

  8. Topological properties of robust biological and computational networks

    PubMed Central

    Navlakha, Saket; He, Xin; Faloutsos, Christos; Bar-Joseph, Ziv

    2014-01-01

    Network robustness is an important principle in biology and engineering. Previous studies of global networks have identified both redundancy and sparseness as topological properties used by robust networks. By focusing on molecular subnetworks, or modules, we show that module topology is tightly linked to the level of environmental variability (noise) the module expects to encounter. Modules internal to the cell that are less exposed to environmental noise are more connected and less robust than external modules. A similar design principle is used by several other biological networks. We propose a simple change to the evolutionary gene duplication model which gives rise to the rich range of module topologies observed within real networks. We apply these observations to evaluate and design communication networks that are specifically optimized for noisy or malicious environments. Combined, joint analysis of biological and computational networks leads to novel algorithms and insights benefiting both fields. PMID:24789562

  9. Methods of information geometry in computational system biology (consistency between chemical and biological evolution).

    PubMed

    Astakhov, Vadim

    2009-01-01

    Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

  10. Towards a lightweight generic computational grid framework for biological research

    PubMed Central

    Halling-Brown, Mark D; Moss, David S; Shepherd, Adrian J

    2008-01-01

    Background An increasing number of scientific research projects require access to large-scale computational resources. This is particularly true in the biological field, whether to facilitate the analysis of large high-throughput data sets, or to perform large numbers of complex simulations – a characteristic of the emerging field of systems biology. Results In this paper we present a lightweight generic framework for combining disparate computational resources at multiple sites (ranging from local computers and clusters to established national Grid services). A detailed guide describing how to set up the framework is available from the following URL: . Conclusion This approach is particularly (but not exclusively) appropriate for large-scale biology projects with multiple collaborators working at different national or international sites. The framework is relatively easy to set up, hides the complexity of Grid middleware from the user, and provides access to resources through a single, uniform interface. It has been developed as part of the European ImmunoGrid project. PMID:18831735

  11. Computational immuno-biology for organ transplantation and regenerative medicine.

    PubMed

    Vásquez-Montoya, Gustavo A; Danobeitia, Juan S; Fernández, Luis A; Hernández-Ortiz, Juan P

    2016-10-01

    Organ transplantation and regenerative medicine are adopted platforms that provide replacement tissues and organs from natural or engineered sources. Acceptance, tolerance and rejection depend greatly on the proper control of the immune response against graft antigens, motivating the development of immunological and genetical therapies that prevent organ failure. They rely on a complete, or partial, understanding of the immune system. Ultimately, they are innovative technologies that ensure permanent graft tolerance and indefinite graft survival through the modulation of the immune system. Computational immunology has arisen as a tool towards a mechanistic understanding of the biological and physicochemical processes surrounding an immune response. It comprehends theoretical and computational frameworks that simulate immuno-biological systems. The challenge is centered on the multi-scale character of the immune system that spans from atomistic scales, during peptide-epitope and protein interactions, to macroscopic scales, for lymph transport and organ-organ reactions. In this paper, we discuss, from an engineering perspective, the biological processes that are involved during the immune response of organ transplantation. Previous computational efforts, including their characteristics and visible limitations, are described. Finally, future perspectives and challenges are listed to motivate further developments.

  12. Frameworks for programming biological function through RNA parts and devices

    PubMed Central

    Win, Maung Nyan; Liang, Joe C.; Smolke, Christina D.

    2009-01-01

    One of the long-term goals of synthetic biology is to reliably engineer biological systems that perform human-defined functions. Currently, researchers face several scientific and technical challenges in designing and building biological systems, one of which is associated with our limited ability to access, transmit, and control molecular information through the design of functional biomolecules exhibiting novel properties. The fields of RNA biology and nucleic acid engineering, along with the tremendous interdisciplinary growth of synthetic biology, are fueling advances in the emerging field of RNA programming in living systems. Researchers are designing functional RNA molecules that exhibit increasingly complex functions and integrating these molecules into cellular circuits to program higher-level biological functions. The continued integration and growth of RNA design and synthetic biology presents exciting potential to transform how we interact with and program biology. PMID:19318211

  13. Computational approaches for rational design of proteins with novel functionalities

    PubMed Central

    Tiwari, Manish Kumar; Singh, Ranjitha; Singh, Raushan Kumar; Kim, In-Won; Lee, Jung-Kul

    2012-01-01

    Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes. PMID:24688643

  14. Computational design of proteins with novel structure and functions

    NASA Astrophysics Data System (ADS)

    Wei, Yang; Lu-Hua, Lai

    2016-01-01

    Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence-structure-function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein-protein interactions. Challenges and future prospects of this field are also discussed. Project supported by the National Basic Research Program of China (Grant No. 2015CB910300), the National High Technology Research and Development Program of China (Grant No. 2012AA020308), and the National Natural Science Foundation of China (Grant No. 11021463).

  15. Mathematical and Computational Challenges in Population Biology and Ecosystems Science

    NASA Technical Reports Server (NTRS)

    Levin, Simon A.; Grenfell, Bryan; Hastings, Alan; Perelson, Alan S.

    1997-01-01

    Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystems science. The subject has a rich history intertwined with the development of statistics and dynamical systems theory, but recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and presented new challenges. Key challenges involve ways to deal with the collective dynamics of heterogeneous ensembles of individuals, and to scale from small spatial regions to large ones. The central issues-understanding how detail at one scale makes its signature felt at other scales, and how to relate phenomena across scales-cut across scientific disciplines and go to the heart of algorithmic development of approaches to high-speed computation. Examples are given from ecology, genetics, epidemiology, and immunology.

  16. Approximate Bayesian computation with functional statistics.

    PubMed

    Soubeyrand, Samuel; Carpentier, Florence; Guiton, François; Klein, Etienne K

    2013-03-26

    Functional statistics are commonly used to characterize spatial patterns in general and spatial genetic structures in population genetics in particular. Such functional statistics also enable the estimation of parameters of spatially explicit (and genetic) models. Recently, Approximate Bayesian Computation (ABC) has been proposed to estimate model parameters from functional statistics. However, applying ABC with functional statistics may be cumbersome because of the high dimension of the set of statistics and the dependences among them. To tackle this difficulty, we propose an ABC procedure which relies on an optimized weighted distance between observed and simulated functional statistics. We applied this procedure to a simple step model, a spatial point process characterized by its pair correlation function and a pollen dispersal model characterized by genetic differentiation as a function of distance. These applications showed how the optimized weighted distance improved estimation accuracy. In the discussion, we consider the application of the proposed ABC procedure to functional statistics characterizing non-spatial processes.

  17. A framework to establish credibility of computational models in biology.

    PubMed

    Patterson, Eann A; Whelan, Maurice P

    2016-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance.

  18. Cardiac lineage selection: integrating biological complexity into computational models.

    PubMed

    Foley, Ann

    2009-01-01

    The emergence of techniques to study developmental processes using systems biology approaches offers exciting possibilities for the developmental biologist. In particular cardiac lineage selection may be particularly amenable to these types of studies since the heart is the first fully functional organ to form in vertebrates. However there are many technical obstacles that need to be overcome for these studies to proceed. Here we present a brief overview of cardiomyocyte lineage deterimination and discuss how different aspects of this process either benefit from or present unique challenges for the development of systems biology approaches.

  19. Community-Wide Evaluation of Computational Function Prediction.

    PubMed

    Friedberg, Iddo; Radivojac, Predrag

    2017-01-01

    A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, to gain insights into the activity of these molecules and guide experiments, we must rely on computational means to functionally annotate the majority of sequence data. To understand how well these algorithms perform, we have established a challenge involving a broad scientific community in which we evaluate different annotation methods according to their ability to predict the associations between previously unannotated protein sequences and Gene Ontology terms. Here we discuss the rationale, benefits, and issues associated with evaluating computational methods in an ongoing community-wide challenge.

  20. Computational Systems Biology in Cancer: Modeling Methods and Applications

    PubMed Central

    Materi, Wayne; Wishart, David S.

    2007-01-01

    In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

  1. Computer Games Functioning as Motivation Stimulants

    ERIC Educational Resources Information Center

    Lin, Grace Hui Chin; Tsai, Tony Kung Wan; Chien, Paul Shih Chieh

    2011-01-01

    Numerous scholars have recommended computer games can function as influential motivation stimulants of English learning, showing benefits as learning tools (Clarke and Dede, 2007; Dede, 2009; Klopfer and Squire, 2009; Liu and Chu, 2010; Mitchell, Dede & Dunleavy, 2009). This study aimed to further test and verify the above suggestion,…

  2. Computational biology in the cloud: methods and new insights from computing at scale.

    PubMed

    Kasson, Peter M

    2013-01-01

    The past few years have seen both explosions in the size of biological data sets and the proliferation of new, highly flexible on-demand computing capabilities. The sheer amount of information available from genomic and metagenomic sequencing, high-throughput proteomics, experimental and simulation datasets on molecular structure and dynamics affords an opportunity for greatly expanded insight, but it creates new challenges of scale for computation, storage, and interpretation of petascale data. Cloud computing resources have the potential to help solve these problems by offering a utility model of computing and storage: near-unlimited capacity, the ability to burst usage, and cheap and flexible payment models. Effective use of cloud computing on large biological datasets requires dealing with non-trivial problems of scale and robustness, since performance-limiting factors can change substantially when a dataset grows by a factor of 10,000 or more. New computing paradigms are thus often needed. The use of cloud platforms also creates new opportunities to share data, reduce duplication, and to provide easy reproducibility by making the datasets and computational methods easily available.

  3. The Structure and Function of Biological Networks

    ERIC Educational Resources Information Center

    Wu, Daniel Duanqing

    2010-01-01

    Biology has been revolutionized in recent years by an explosion in the availability of data. Transforming this new wealth of data into meaningful biological insights and clinical breakthroughs requires a complete overhaul both in the questions being asked and the methodologies used to answer them. A major challenge in organizing and understanding…

  4. The ERATO Systems Biology Workbench: enabling interaction and exchange between software tools for computational biology.

    PubMed

    Hucka, M; Finney, A; Sauro, H M; Bolouri, H; Doyle, J; Kitano, H

    2002-01-01

    Researchers in computational biology today make use of a large number of different software packages for modeling, analysis, and data manipulation and visualization. In this paper, we describe the ERATO Systems Biology Workbench (SBW), a software framework that allows these heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' data and algorithmic capabilities. Our goal is to create a simple, open-source software infrastructure which is effective, easy to implement and easy to understand. SBW uses a broker-based architecture and enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe the SBW architecture and the current set of modules, as well as alternative implementation technologies.

  5. Computational adaptive optics for live three-dimensional biological imaging

    PubMed Central

    Kam, Z.; Hanser, B.; Gustafsson, M. G. L.; Agard, D. A.; Sedat, J. W.

    2001-01-01

    Light microscopy of thick biological samples, such as tissues, is often limited by aberrations caused by refractive index variations within the sample itself. This problem is particularly severe for live imaging, a field of great current excitement due to the development of inherently fluorescent proteins. We describe a method of removing such aberrations computationally by mapping the refractive index of the sample using differential interference contrast microscopy, modeling the aberrations by ray tracing through this index map, and using space-variant deconvolution to remove aberrations. This approach will open possibilities to study weakly labeled molecules in difficult-to-image live specimens. PMID:11274396

  6. Advances and Computational Tools towards Predictable Design in Biological Engineering

    PubMed Central

    2014-01-01

    The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated. PMID:25161694

  7. Biological networks 101: computational modeling for molecular biologists.

    PubMed

    Scholma, Jetse; Schivo, Stefano; Urquidi Camacho, Ricardo A; van de Pol, Jaco; Karperien, Marcel; Post, Janine N

    2014-01-01

    Computational modeling of biological networks permits the comprehensive analysis of cells and tissues to define molecular phenotypes and novel hypotheses. Although a large number of software tools have been developed, the versatility of these tools is limited by mathematical complexities that prevent their broad adoption and effective use by molecular biologists. This study clarifies the basic aspects of molecular modeling, how to convert data into useful input, as well as the number of time points and molecular parameters that should be considered for molecular regulatory models with both explanatory and predictive potential. We illustrate the necessary experimental preconditions for converting data into a computational model of network dynamics. This model requires neither a thorough background in mathematics nor precise data on intracellular concentrations, binding affinities or reaction kinetics. Finally, we show how an interactive model of crosstalk between signal transduction pathways in primary human articular chondrocytes allows insight into processes that regulate gene expression.

  8. Parameter Estimation and Model Selection in Computational Biology

    PubMed Central

    Lillacci, Gabriele; Khammash, Mustafa

    2010-01-01

    A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants) are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection. PMID:20221262

  9. Computations and algorithms in physical and biological problems

    NASA Astrophysics Data System (ADS)

    Qin, Yu

    This dissertation presents the applications of state-of-the-art computation techniques and data analysis algorithms in three physical and biological problems: assembling DNA pieces, optimizing self-assembly yield, and identifying correlations from large multivariate datasets. In the first topic, in-depth analysis of using Sequencing by Hybridization (SBH) to reconstruct target DNA sequences shows that a modified reconstruction algorithm can overcome the theoretical boundary without the need for different types of biochemical assays and is robust to error. In the second topic, consistent with theoretical predictions, simulations using Graphics Processing Unit (GPU) demonstrate how controlling the short-ranged interactions between particles and controlling the concentrations optimize the self-assembly yield of a desired structure, and nonequilibrium behavior when optimizing concentrations is also unveiled by leveraging the computation capacity of GPUs. In the last topic, a methodology to incorporate existing categorization information into the search process to efficiently reconstruct the optimal true correlation matrix for multivariate datasets is introduced. Simulations on both synthetic and real financial datasets show that the algorithm is able to detect signals below the Random Matrix Theory (RMT) threshold. These three problems are representatives of using massive computation techniques and data analysis algorithms to tackle optimization problems, and outperform theoretical boundary when incorporating prior information into the computation.

  10. Twenty years of protein interaction studies for biological function deciphering.

    PubMed

    Legrain, Pierre; Rain, Jean-Christophe

    2014-07-31

    Intensive methodological developments and technology innovation have been devoted to protein-protein interaction studies over 20years. Genetic indirect assays and sophisticated large scale biochemical analyses have jointly contributed to the elucidation of protein-protein interactions, still with a lot of drawbacks despite heavy investment in human resources and technologies. With the most recent developments in mass spectrometry and computational tools for studying protein content of complex samples, the initial goal of deciphering molecular bases of biological functions is now within reach. Here, we described the various steps of this process and gave examples of key milestones in this scientific story line. This article is part of a Special Issue entitled: 20years of Proteomics in memory of Viatliano Pallini. Guest Editors: Luca Bini, Juan J. Calvete, Natacha Turck, Denis Hochstrasser and Jean-Charles Sanchez.

  11. Mapping an expanding territory: computer simulations in evolutionary biology.

    PubMed

    Huneman, Philippe

    2014-08-01

    The pervasive use of computer simulations in the sciences brings novel epistemological issues discussed in the philosophy of science literature since about a decade. Evolutionary biology strongly relies on such simulations, and in relation to it there exists a research program (Artificial Life) that mainly studies simulations themselves. This paper addresses the specificity of computer simulations in evolutionary biology, in the context (described in Sect. 1) of a set of questions about their scope as explanations, the nature of validation processes and the relation between simulations and true experiments or mathematical models. After making distinctions, especially between a weak use where simulations test hypotheses about the world, and a strong use where they allow one to explore sets of evolutionary dynamics not necessarily extant in our world, I argue in Sect. 2 that (weak) simulations are likely to represent in virtue of the fact that they instantiate specific features of causal processes that may be isomorphic to features of some causal processes in the world, though the latter are always intertwined with a myriad of different processes and hence unlikely to be directly manipulated and studied. I therefore argue that these simulations are merely able to provide candidate explanations for real patterns. Section 3 ends up by placing strong and weak simulations in Levins' triangle, that conceives of simulations as devices trying to fulfil one or two among three incompatible epistemic values (precision, realism, genericity).

  12. Biology Teacher and Expert Opinions about Computer Assisted Biology Instruction Materials: A Software Entitled Nucleic Acids and Protein Synthesis

    ERIC Educational Resources Information Center

    Hasenekoglu, Ismet; Timucin, Melih

    2007-01-01

    The aim of this study is to collect and evaluate opinions of CAI experts and biology teachers about a high school level Computer Assisted Biology Instruction Material presenting computer-made modelling and simulations. It is a case study. A material covering "Nucleic Acids and Protein Synthesis" topic was developed as the…

  13. The emerging discipline of Computational Functional Anatomy

    PubMed Central

    Miller, Michael I.; Qiu, Anqi

    2010-01-01

    Computational Functional Anatomy (CFA) is the study of functional and physiological response variables in anatomical coordinates. For this we focus on two things: (i) the construction of bijections (via diffeomorphisms) between the coordinatized manifolds of human anatomy, and (ii) the transfer (group action and parallel transport) of functional information into anatomical atlases via these bijections. We review advances in the unification of the bijective comparison of anatomical submanifolds via point-sets including points, curves and surface triangulations as well as dense imagery. We examine the transfer via these bijections of functional response variables into anatomical coordinates via group action on scalars and matrices in DTI as well as parallel transport of metric information across multiple templates which preserves the inner product. PMID:19103297

  14. Analysis of Ventricular Function by Computed Tomography

    PubMed Central

    Rizvi, Asim; Deaño, Roderick C.; Bachman, Daniel P.; Xiong, Guanglei; Min, James K.; Truong, Quynh A.

    2014-01-01

    The assessment of ventricular function, cardiac chamber dimensions and ventricular mass is fundamental for clinical diagnosis, risk assessment, therapeutic decisions, and prognosis in patients with cardiac disease. Although cardiac computed tomography (CT) is a noninvasive imaging technique often used for the assessment of coronary artery disease, it can also be utilized to obtain important data about left and right ventricular function and morphology. In this review, we will discuss the clinical indications for the use of cardiac CT for ventricular analysis, review the evidence on the assessment of ventricular function compared to existing imaging modalities such cardiac MRI and echocardiography, provide a typical cardiac CT protocol for image acquisition and post-processing for ventricular analysis, and provide step-by-step instructions to acquire multiplanar cardiac views for ventricular assessment from the standard axial, coronal, and sagittal planes. Furthermore, both qualitative and quantitative assessments of ventricular function as well as sample reporting are detailed. PMID:25576407

  15. New Computer Simulations of Macular Neural Functioning

    NASA Technical Reports Server (NTRS)

    Ross, Muriel D.; Doshay, D.; Linton, S.; Parnas, B.; Montgomery, K.; Chimento, T.

    1994-01-01

    We use high performance graphics workstations and supercomputers to study the functional significance of the three-dimensional (3-D) organization of gravity sensors. These sensors have a prototypic architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scaled-up, 3-D versions run on a Cray Y-MP supercomputer. A semi-automated method of reconstruction of neural tissue from serial sections studied in a transmission electron microscope has been developed to eliminate tedious conventional photography. The reconstructions use a mesh as a step in generating a neural surface for visualization. Two meshes are required to model calyx surfaces. The meshes are connected and the resulting prisms represent the cytoplasm and the bounding membranes. A finite volume analysis method is employed to simulate voltage changes along the calyx in response to synapse activation on the calyx or on calyceal processes. The finite volume method insures that charge is conserved at the calyx-process junction. These and other models indicate that efferent processes act as voltage followers, and that the morphology of some afferent processes affects their functioning. In a final application, morphological information is symbolically represented in three dimensions in a computer. The possible functioning of the connectivities is tested using mathematical interpretations of physiological parameters taken from the literature. Symbolic, 3-D simulations are in progress to probe the functional significance of the connectivities. This research is expected to advance computer-based studies of macular functioning and of synaptic plasticity.

  16. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

    PubMed

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

  17. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

    PubMed Central

    Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

  18. Computational approaches towards understanding human long non-coding RNA biology.

    PubMed

    Jalali, Saakshi; Kapoor, Shruti; Sivadas, Ambily; Bhartiya, Deeksha; Scaria, Vinod

    2015-07-15

    Long non-coding RNAs (lncRNAs) form the largest class of non-protein coding genes in the human genome. While a small subset of well-characterized lncRNAs has demonstrated their significant role in diverse biological functions like chromatin modifications, post-transcriptional regulation, imprinting etc., the functional significance of a vast majority of them still remains an enigma. Increasing evidence of the implications of lncRNAs in various diseases including cancer and major developmental processes has further enhanced the need to gain mechanistic insights into the lncRNA functions. Here, we present a comprehensive review of the various computational approaches and tools available for the identification and annotation of long non-coding RNAs. We also discuss a conceptual roadmap to systematically explore the functional properties of the lncRNAs using computational approaches.

  19. Community-driven computational biology with Debian Linux

    PubMed Central

    2010-01-01

    Background The Open Source movement and its technologies are popular in the bioinformatics community because they provide freely available tools and resources for research. In order to feed the steady demand for updates on software and associated data, a service infrastructure is required for sharing and providing these tools to heterogeneous computing environments. Results The Debian Med initiative provides ready and coherent software packages for medical informatics and bioinformatics. These packages can be used together in Taverna workflows via the UseCase plugin to manage execution on local or remote machines. If such packages are available in cloud computing environments, the underlying hardware and the analysis pipelines can be shared along with the software. Conclusions Debian Med closes the gap between developers and users. It provides a simple method for offering new releases of software and data resources, thus provisioning a local infrastructure for computational biology. For geographically distributed teams it can ensure they are working on the same versions of tools, in the same conditions. This contributes to the world-wide networking of researchers. PMID:21210984

  20. Computer network defense through radial wave functions

    NASA Astrophysics Data System (ADS)

    Malloy, Ian J.

    The purpose of this research is to synthesize basic and fundamental findings in quantum computing, as applied to the attack and defense of conventional computer networks. The concept focuses on uses of radio waves as a shield for, and attack against traditional computers. A logic bomb is analogous to a landmine in a computer network, and if one was to implement it as non-trivial mitigation, it will aid computer network defense. As has been seen in kinetic warfare, the use of landmines has been devastating to geopolitical regions in that they are severely difficult for a civilian to avoid triggering given the unknown position of a landmine. Thus, the importance of understanding a logic bomb is relevant and has corollaries to quantum mechanics as well. The research synthesizes quantum logic phase shifts in certain respects using the Dynamic Data Exchange protocol in software written for this work, as well as a C-NOT gate applied to a virtual quantum circuit environment by implementing a Quantum Fourier Transform. The research focus applies the principles of coherence and entanglement from quantum physics, the concept of expert systems in artificial intelligence, principles of prime number based cryptography with trapdoor functions, and modeling radio wave propagation against an event from unknown parameters. This comes as a program relying on the artificial intelligence concept of an expert system in conjunction with trigger events for a trapdoor function relying on infinite recursion, as well as system mechanics for elliptic curve cryptography along orbital angular momenta. Here trapdoor both denotes the form of cipher, as well as the implied relationship to logic bombs.

  1. Understanding regulatory networks requires more than computing a multitude of graph statistics. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin et al.

    NASA Astrophysics Data System (ADS)

    Tkačik, Gašper

    2016-07-01

    The article by O. Martin and colleagues provides a much needed systematic review of a body of work that relates the topological structure of genetic regulatory networks to evolutionary selection for function. This connection is very important. Using the current wealth of genomic data, statistical features of regulatory networks (e.g., degree distributions, motif composition, etc.) can be quantified rather easily; it is, however, often unclear how to interpret the results. On a graph theoretic level the statistical significance of the results can be evaluated by comparing observed graphs to ;randomized; ones (bravely ignoring the issue of how precisely to randomize!) and comparing the frequency of appearance of a particular network structure relative to a randomized null expectation. While this is a convenient operational test for statistical significance, its biological meaning is questionable. In contrast, an in-silico genotype-to-phenotype model makes explicit the assumptions about the network function, and thus clearly defines the expected network structures that can be compared to the case of no selection for function and, ultimately, to data.

  2. Complex network problems in physics, computer science and biology

    NASA Astrophysics Data System (ADS)

    Cojocaru, Radu Ionut

    There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe

  3. Functionalized apertures for the detection of chemical and biological materials

    DOEpatents

    Letant, Sonia E.; van Buuren, Anthony W.; Terminello, Louis J.; Thelen, Michael P.; Hope-Weeks, Louisa J.; Hart, Bradley R.

    2010-12-14

    Disclosed are nanometer to micron scale functionalized apertures constructed on a substrate made of glass, carbon, semiconductors or polymeric materials that allow for the real time detection of biological materials or chemical moieties. Many apertures can exist on one substrate allowing for the simultaneous detection of numerous chemical and biological molecules. One embodiment features a macrocyclic ring attached to cross-linkers, wherein the macrocyclic ring has a biological or chemical probe extending through the aperture. Another embodiment achieves functionalization by attaching chemical or biological anchors directly to the walls of the apertures via cross-linkers.

  4. Patient radiation biological risk in computed tomography angiography procedure.

    PubMed

    Alkhorayef, M; Babikir, E; Alrushoud, A; Al-Mohammed, H; Sulieman, A

    2017-02-01

    Computed tomography angiography (CTA) has become the most valuable imaging modality for the diagnosis of blood vessel diseases; however, patients are exposed to high radiation doses and the probability of cancer and other biological effects is increased. The objectives of this study were to measure the patient radiation dose during a CTA procedure and to estimate the radiation dose and biological effects. The study was conducted in two radiology departments equipped with 64-slice CT machines (Aquilion) calibrated according to international protocols. A total of 152 patients underwent brain, lower limb, chest, abdomen, and pelvis examinations. The effective radiation dose was estimated using ImPACT scan software. Cancer and biological risks were estimated using the International Commission on Radiological Protection (ICRP) conversion factors. The mean patient dose value per procedure (dose length product [DLP], mGy·cm) for all examinations was 437.8 ± 166, 568.8 ± 194, 516.0 ± 228, 581.8 ± 175, and 1082.9 ± 290 for the lower limbs, pelvis, abdomen, chest, and cerebral, respectively. The lens of the eye, uterus, and ovaries received high radiation doses compared to thyroid and testis. The overall patient risk per CTA procedure ranged between 15 and 36 cancer risks per 1 million procedures. Patient risk from CTA procedures is high during neck and abdomen procedures. Special concern should be provided to the lens of the eye and thyroid during brain CTA procedures. Patient dose reduction is an important consideration; thus, staff should optimize the radiation dose during CTA procedures.

  5. Computational biology: plus c'est la même chose, plus ça change.

    PubMed

    Huttenhower, Curtis

    2011-08-23

    A report on the joint 19th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB)/10th Annual European Conference on Computational Biology (ECCB) meetings and the 7th International Society for Computational Biology Student Council Symposium, Vienna, Austria, 15-19 July 2011.

  6. Energy and time determine scaling in biological and computer designs.

    PubMed

    Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

    2016-08-19

    Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

  7. Computational functions in biochemical reaction networks.

    PubMed Central

    Arkin, A; Ross, J

    1994-01-01

    In prior work we demonstrated the implementation of logic gates, sequential computers (universal Turing machines), and parallel computers by means of the kinetics of chemical reaction mechanisms. In the present article we develop this subject further by first investigating the computational properties of several enzymatic (single and multiple) reaction mechanisms: we show their steady states are analogous to either Boolean or fuzzy logic gates. Nearly perfect digital function is obtained only in the regime in which the enzymes are saturated with their substrates. With these enzymatic gates, we construct combinational chemical networks that execute a given truth-table. The dynamic range of a network's output is strongly affected by "input/output matching" conditions among the internal gate elements. We find a simple mechanism, similar to the interconversion of fructose-6-phosphate between its two bisphosphate forms (fructose-1,6-bisphosphate and fructose-2,6-bisphosphate), that functions analogously to an AND gate. When the simple model is supplanted with one in which the enzyme rate laws are derived from experimental data, the steady state of the mechanism functions as an asymmetric fuzzy aggregation operator with properties akin to a fuzzy AND gate. The qualitative behavior of the mechanism does not change when situated within a large model of glycolysis/gluconeogenesis and the TCA cycle. The mechanism, in this case, switches the pathway's mode from glycolysis to gluconeogenesis in response to chemical signals of low blood glucose (cAMP) and abundant fuel for the TCA cycle (acetyl coenzyme A). Images FIGURE 3 FIGURE 4 FIGURE 5 FIGURE 7 FIGURE 10 FIGURE 12 FIGURE 13 FIGURE 14 FIGURE 15 FIGURE 16 PMID:7948674

  8. Algorithms for Computing the Lag Function.

    DTIC Science & Technology

    1981-03-27

    and S. J. Giner Subject: Algorithms for Computing the Lag Function References: See p . 27 Abstract: This memorandum provides a scheme for the numerical...highly oscillatory, and with singularities at the end points. j -3- 27 March 1981 GHP:SJG:Ihz TABLE OF CONTENTS P age Abstract...0 -9 16 -9 1) 1 11 1 1 -8 3 -1 -t I -8 8 -1 -1 1i 1 2 -6 2 1 1 2 -6 2 1 1 1 3 -3 -1 1 3 -3 -1 1i 1 4 1 1 4 1 -10- 27 March 1981 (1- P : SJG: 1hz The

  9. Functionalized Nanodiamonds for Biological and Medical Applications.

    PubMed

    Lai, Lin; Barnard, Amanda S

    2015-02-01

    Nanodiamond is a promising material for biological and medical applications, owning to its relatively inexpensive and large-scale synthesis, unique structure, and superior optical properties. However, most biomedical applications, such as drug delivery and bio-imaging, are dependent upon the precise control of the surfaces, and can be significantly affected by the type, distribution and stability of chemical funtionalisations of the nanodiamond surface. In this paper, recent studies on nanodiamonds and their biomedical applications by conjugating with different chemicals are reviewed, while highlighting the critical importance of surface chemical states for various applications.

  10. Enzymatic Halogenases and Haloperoxidases: Computational Studies on Mechanism and Function.

    PubMed

    Timmins, Amy; de Visser, Sam P

    2015-01-01

    Despite the fact that halogenated compounds are rare in biology, a number of organisms have developed processes to utilize halogens and in recent years, a string of enzymes have been identified that selectively insert halogen atoms into, for instance, a CH aliphatic bond. Thus, a number of natural products, including antibiotics, contain halogenated functional groups. This unusual process has great relevance to the chemical industry for stereoselective and regiospecific synthesis of haloalkanes. Currently, however, industry utilizes few applications of biological haloperoxidases and halogenases, but efforts are being worked on to understand their catalytic mechanism, so that their catalytic function can be upscaled. In this review, we summarize experimental and computational studies on the catalytic mechanism of a range of haloperoxidases and halogenases with structurally very different catalytic features and cofactors. This chapter gives an overview of heme-dependent haloperoxidases, nonheme vanadium-dependent haloperoxidases, and flavin adenine dinucleotide-dependent haloperoxidases. In addition, we discuss the S-adenosyl-l-methionine fluoridase and nonheme iron/α-ketoglutarate-dependent halogenases. In particular, computational efforts have been applied extensively for several of these haloperoxidases and halogenases and have given insight into the essential structural features that enable these enzymes to perform the unusual halogen atom transfer to substrates.

  11. Effects of cellular homeostatic intrinsic plasticity on dynamical and computational properties of biological recurrent neural networks.

    PubMed

    Naudé, Jérémie; Cessac, Bruno; Berry, Hugues; Delord, Bruno

    2013-09-18

    Homeostatic intrinsic plasticity (HIP) is a ubiquitous cellular mechanism regulating neuronal activity, cardinal for the proper functioning of nervous systems. In invertebrates, HIP is critical for orchestrating stereotyped activity patterns. The functional impact of HIP remains more obscure in vertebrate networks, where higher order cognitive processes rely on complex neural dynamics. The hypothesis has emerged that HIP might control the complexity of activity dynamics in recurrent networks, with important computational consequences. However, conflicting results about the causal relationships between cellular HIP, network dynamics, and computational performance have arisen from machine-learning studies. Here, we assess how cellular HIP effects translate into collective dynamics and computational properties in biological recurrent networks. We develop a realistic multiscale model including a generic HIP rule regulating the neuronal threshold with actual molecular signaling pathways kinetics, Dale's principle, sparse connectivity, synaptic balance, and Hebbian synaptic plasticity (SP). Dynamic mean-field analysis and simulations unravel that HIP sets a working point at which inputs are transduced by large derivative ranges of the transfer function. This cellular mechanism ensures increased network dynamics complexity, robust balance with SP at the edge of chaos, and improved input separability. Although critically dependent upon balanced excitatory and inhibitory drives, these effects display striking robustness to changes in network architecture, learning rates, and input features. Thus, the mechanism we unveil might represent a ubiquitous cellular basis for complex dynamics in neural networks. Understanding this robustness is an important challenge to unraveling principles underlying self-organization around criticality in biological recurrent neural networks.

  12. Chemical Biology for Understanding Matrix Metalloproteinase Function

    PubMed Central

    Knapinska, Anna; Fields, Gregg B.

    2013-01-01

    The matrix metalloproteinase (MMP) family has long been associated with normal physiological processes such as embryonic implantation, tissue remodeling, organ development, and wound healing, as well as multiple aspects of cancer initiation and progression, osteoarthritis, inflammatory and vascular diseases, and neurodegenerative diseases. The development of chemically designed MMP probes has advanced our understanding of the roles of MMPs in disease in addition to shedding considerable light on the mechanisms of MMP action. The first generation of protease-activated agents has demonstrated proof of principle as well as providing impetus for in vivo applications. One common problem has been a lack of agent stability at nontargeted tissues and organs due to activation by multiple proteases. The present review considers how chemical biology has impacted the progress made in understanding the roles of MMPs in disease and the basic mechanisms of MMP action. PMID:22933318

  13. Printable Bioelectronics To Investigate Functional Biological Interfaces.

    PubMed

    Manoli, Kyriaki; Magliulo, Maria; Mulla, Mohammad Yusuf; Singh, Mandeep; Sabbatini, Luigia; Palazzo, Gerardo; Torsi, Luisa

    2015-10-19

    Thin-film transistors can be used as high-performance bioelectronic devices to accomplish tasks such as sensing or controlling the release of biological species as well as transducing the electrical activity of cells or even organs, such as the brain. Organic, graphene, or zinc oxide are used as convenient printable semiconducting layers and can lead to high-performance low-cost bioelectronic sensing devices that are potentially very useful for point-of-care applications. Among others, electrolyte-gated transistors are of interest as they can be operated as capacitance-modulated devices, because of the high capacitance of their charge double layers. Specifically, it is the capacitance of the biolayer, being lowest in a series of capacitors, which controls the output current of the device. Such an occurrence allows for extremely high sensitivity towards very weak interactions. All the aspects governing these processes are reviewed here.

  14. Gels as functional nanomaterials for biology and medicine.

    PubMed

    Xu, Bing

    2009-08-04

    This perspective focuses on the potential uses of gels as materials in biological and medical applications. It describes how molecular self-assembly can confer well-defined secondary structures (e.g., nanofibers, nanotubes, and nanospheres) in a liquid that initiates functions within biological systems. Some prospects for future development and the challenges for achieving them are discussed.

  15. COMPUTATIONAL METHODS FOR STUDYING THE INTERACTION BETWEEN POLYCYCLIC AROMATIC HYDROCARBONS AND BIOLOGICAL MACROMOLECULES

    EPA Science Inventory

    Computational Methods for Studying the Interaction between Polycyclic Aromatic Hydrocarbons and Biological Macromolecules .

    The mechanisms for the processes that result in significant biological activity of PAHs depend on the interaction of these molecules or their metabol...

  16. Computational approaches for inferring the functions of intrinsically disordered proteins

    PubMed Central

    Varadi, Mihaly; Vranken, Wim; Guharoy, Mainak; Tompa, Peter

    2015-01-01

    Intrinsically disordered proteins (IDPs) are ubiquitously involved in cellular processes and often implicated in human pathological conditions. The critical biological roles of these proteins, despite not adopting a well-defined fold, encouraged structural biologists to revisit their views on the protein structure-function paradigm. Unfortunately, investigating the characteristics and describing the structural behavior of IDPs is far from trivial, and inferring the function(s) of a disordered protein region remains a major challenge. Computational methods have proven particularly relevant for studying IDPs: on the sequence level their dependence on distinct characteristics determined by the local amino acid context makes sequence-based prediction algorithms viable and reliable tools for large scale analyses, while on the structure level the in silico integration of fundamentally different experimental data types is essential to describe the behavior of a flexible protein chain. Here, we offer an overview of the latest developments and computational techniques that aim to uncover how protein function is connected to intrinsic disorder. PMID:26301226

  17. Theoretical discussion for quantum computation in biological systems

    NASA Astrophysics Data System (ADS)

    Baer, Wolfgang

    2010-04-01

    Analysis of the brain as a physical system, that has the capacity of generating a display of every day observed experiences and contains some knowledge of the physical reality which stimulates those experiences, suggests the brain executes a self-measurement process described by quantum theory. Assuming physical reality is a universe of interacting self-measurement loops, we present a model of space as a field of cells executing such self-measurement activities. Empty space is the observable associated with the measurement of this field when the mass and charge density defining the material aspect of the cells satisfy the least action principle. Content is the observable associated with the measurement of the quantum wave function ψ interpreted as mass-charge displacements. The illusion of space and its content incorporated into cognitive biological systems is evidence of self-measurement activity that can be associated with quantum operations.

  18. Autofluorescence: Biological functions and technical applications.

    PubMed

    García-Plazaola, José Ignacio; Fernández-Marín, Beatriz; Duke, Stephen O; Hernández, Antonio; López-Arbeloa, Fernando; Becerril, José María

    2015-07-01

    Chlorophylls are the most remarkable examples of fluorophores, and their fluorescence has been intensively studied as a non-invasive tool for assessment of photosynthesis. Many other fluorophores occur in plants, such as alkaloids, phenolic compounds and porphyrins. Fluorescence could be more than just a physicochemical curiosity in the plant kingdom, as several functional roles in biocommunication occur or have been proposed. Besides, fluorescence emitted by secondary metabolites can convert damaging blue and UV into wavelengths potentially useful for photosynthesis. Detection of the fluorescence of some secondary phytochemicals may be a cue for some pollinators and/or seed dispersal organisms. Independently of their functions, plant fluorophores provide researchers with a tool that allows the visualization of some metabolites in plants and cells, complementing and overcoming some of the limitations of the use of fluorescent proteins and dyes to probe plant physiology and biochemistry. Some fluorophores are influenced by environmental interactions, allowing fluorescence to be also used as a specific stress indicator.

  19. Chemical synthesis and biological function of lipidated proteins.

    PubMed

    Yang, Aimin; Zhao, Lei; Wu, Yao-Wen

    2015-01-01

    Lipidated proteins play a key role in many essential biological processes in eukaryotic cells, including signal transduction, membrane trafficking, immune response and pathology. The investigation of the function of lipidated proteins requires access to a reasonable amount of homogenous lipid-modified proteins with defined structures and functional groups. Chemical approaches have provided useful tools to perform such studies. In this review we summarize synthetic methods of lipidated peptides and developments in the chemoselective ligation for the production of lipidated proteins. We introduce the biology of lipidated proteins and highlight the application of synthetic lipidated proteins to tackle important biological questions.

  20. Computing dispersion interactions in density functional theory

    NASA Astrophysics Data System (ADS)

    Cooper, V. R.; Kong, L.; Langreth, D. C.

    2010-02-01

    In this article techniques for including dispersion interactions within density functional theory are examined. In particular comparisons are made between four popular methods: dispersion corrected DFT, pseudopotential correction schemes, symmetry adapted perturbation theory, and a non-local density functional - the so called Rutgers-Chalmers van der Waals density functional (vdW-DF). The S22 benchmark data set is used to evaluate the relative accuracy of these methods and factors such as scalability and transferability are also discussed. We demonstrate that vdW-DF presents an excellent compromise between computational speed and accuracy and lends most easily to full scale application in solid materials. This claim is supported through a brief discussion of a recent large scale application to H2 in a prototype metal organic framework material (MOF), Zn2BDC2TED. The vdW-DF shows overwhelming promise for first-principles studies of physisorbed molecules in porous extended systems; thereby having broad applicability for studies as diverse as molecular adsorption and storage, battery technology, catalysis and gas separations.

  1. Computational Biology Methods for Characterization of Pluripotent Cells.

    PubMed

    Araúzo-Bravo, Marcos J

    2016-01-01

    Pluripotent cells are a powerful tool for regenerative medicine and drug discovery. Several techniques have been developed to induce pluripotency, or to extract pluripotent cells from different tissues and biological fluids. However, the characterization of pluripotency requires tedious, expensive, time-consuming, and not always reliable wet-lab experiments; thus, an easy, standard quality-control protocol of pluripotency assessment remains to be established. Here to help comes the use of high-throughput techniques, and in particular, the employment of gene expression microarrays, which has become a complementary technique for cellular characterization. Research has shown that the transcriptomics comparison with an Embryonic Stem Cell (ESC) of reference is a good approach to assess the pluripotency. Under the premise that the best protocol is a computer software source code, here I propose and explain line by line a software protocol coded in R-Bioconductor for pluripotency assessment based on the comparison of transcriptomics data of pluripotent cells with an ESC of reference. I provide advice for experimental design, warning about possible pitfalls, and guides for results interpretation.

  2. Reduction of dynamical biochemical reactions networks in computational biology

    PubMed Central

    Radulescu, O.; Gorban, A. N.; Zinovyev, A.; Noel, V.

    2012-01-01

    Biochemical networks are used in computational biology, to model mechanistic details of systems involved in cell signaling, metabolism, and regulation of gene expression. Parametric and structural uncertainty, as well as combinatorial explosion are strong obstacles against analyzing the dynamics of large models of this type. Multiscaleness, an important property of these networks, can be used to get past some of these obstacles. Networks with many well separated time scales, can be reduced to simpler models, in a way that depends only on the orders of magnitude and not on the exact values of the kinetic parameters. The main idea used for such robust simplifications of networks is the concept of dominance among model elements, allowing hierarchical organization of these elements according to their effects on the network dynamics. This concept finds a natural formulation in tropical geometry. We revisit, in the light of these new ideas, the main approaches to model reduction of reaction networks, such as quasi-steady state (QSS) and quasi-equilibrium approximations (QE), and provide practical recipes for model reduction of linear and non-linear networks. We also discuss the application of model reduction to the problem of parameter identification, via backward pruning machine learning techniques. PMID:22833754

  3. Computational based functional analysis of Bacillus phytases.

    PubMed

    Verma, Anukriti; Singh, Vinay Kumar; Gaur, Smriti

    2016-02-01

    Phytase is an enzyme which catalyzes the total hydrolysis of phytate to less phosphorylated myo-inositol derivatives and inorganic phosphate and digests the undigestable phytate part present in seeds and grains and therefore provides digestible phosphorus, calcium and other mineral nutrients. Phytases are frequently added to the feed of monogastric animals so that bioavailability of phytic acid-bound phosphate increases, ultimately enhancing the nutritional value of diets. The Bacillus phytase is very suitable to be used in animal feed because of its optimum pH with excellent thermal stability. Present study is aimed to perform an in silico comparative characterization and functional analysis of phytases from Bacillus amyloliquefaciens to explore physico-chemical properties using various bio-computational tools. All proteins are acidic and thermostable and can be used as suitable candidates in the feed industry.

  4. Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition

    NASA Astrophysics Data System (ADS)

    Fitch, W. Tecumseh

    2014-09-01

    Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a

  5. Toward a computational framework for cognitive biology: unifying approaches from cognitive neuroscience and comparative cognition.

    PubMed

    Fitch, W Tecumseh

    2014-09-01

    Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a

  6. Labeling and functionalizing amphipols for biological applications.

    PubMed

    Le Bon, Christel; Popot, Jean-Luc; Giusti, Fabrice

    2014-10-01

    Amphipols (APols) are short amphipathic polymers developed as an alternative to detergents for handling membrane proteins (MPs) in aqueous solution. MPs are, as a rule, much more stable following trapping with APols than they are in detergent solutions. The best-characterized APol to date, called A8-35, is a mixture of short-chain sodium polyacrylates randomly derivatized with octylamine and isopropylamine. Its solution properties have been studied in detail, and it has been used extensively for biochemical and biophysical studies of MPs. One of the attractive characteristics of APols is that it is relatively easy to label them, isotopically or otherwise, without affecting their physical-chemical properties. Furthermore, several variously modified APols can be mixed, achieving multiple functionalization of MP/APol complexes in the easiest possible manner. Labeled or tagged APols are being used to study the solution properties of APols, their miscibility, their biodistribution upon injection into living organisms, their association with MPs and the composition, structure and dynamics of MP/APol complexes, examining the exchange of surfactants at the surface of MPs, labeling MPs to follow their distribution in fractionation experiments or to immobilize them, increasing the contrast between APols and solvent or MPs in biophysical experiments, improving NMR spectra, etc. Labeling or functionalization of APols can take various courses, each of which has its specific constraints and advantages regarding both synthesis and purification. The present review offers an overview of the various derivatives of A8-35 and its congeners that have been developed in our laboratory and discusses the pros and cons of various synthetic routes.

  7. Labeling and Functionalizing Amphipols for Biological Applications

    PubMed Central

    Bon, Christel Le; Popot, Jean-Luc; Giusti, Fabrice

    2014-01-01

    Amphipols (APols) are short amphipathic polymers developed as an alternative to detergents for handling membrane proteins (MPs) in aqueous solution. MPs are, as a rule, much more stable following trapping with APols than they are in detergent solutions. The best-characterized APol to date, called A8-35, is a mixture of short-chain sodium polyacrylates randomly derivatized with octylamine and isopropylamine. Its solution properties have been studied in detail, and it has been used extensively for biochemical and biophysical studies of MPs. One of the attractive characteristics of APols is that it is relatively easy to label them, isotopically or otherwise, without affecting their physical-chemical properties. Furthermore, several variously modified APols can be mixed, achieving multiple functionalization of MP/APol complexes in the easiest possible manner. Labeled or tagged APols are being used to study the solution properties of APols, their miscibility, their biodistribution upon injection into living organisms, their association with MPs and the composition, structure and dynamics of MP/APol complexes, examining the exchange of surfactants at the surface of MPs, labeling MPs to follow their distribution in fractionation experiments or to immobilize them, increasing the contrast between APols and solvent or MPs in biophysical experiments, improving NMR spectra, etc. Labeling or functionalization of APols can take various courses, each of which has its specific constraints and advantages regarding both synthesis and purification. The present review offers an overview of the various derivatives of A8-35 and its congeners that have been developed in our laboratory and discusses the pros and cons of various synthetic routes. PMID:24696186

  8. Complete RNA inverse folding: computational design of functional hammerhead ribozymes

    PubMed Central

    Dotu, Ivan; Garcia-Martin, Juan Antonio; Slinger, Betty L.; Mechery, Vinodh; Meyer, Michelle M.; Clote, Peter

    2014-01-01

    Nanotechnology and synthetic biology currently constitute one of the most innovative, interdisciplinary fields of research, poised to radically transform society in the 21st century. This paper concerns the synthetic design of ribonucleic acid molecules, using our recent algorithm, RNAiFold, which can determine all RNA sequences whose minimum free energy secondary structure is a user-specified target structure. Using RNAiFold, we design ten cis-cleaving hammerhead ribozymes, all of which are shown to be functional by a cleavage assay. We additionally use RNAiFold to design a functional cis-cleaving hammerhead as a modular unit of a synthetic larger RNA. Analysis of kinetics on this small set of hammerheads suggests that cleavage rate of computationally designed ribozymes may be correlated with positional entropy, ensemble defect, structural flexibility/rigidity and related measures. Artificial ribozymes have been designed in the past either manually or by SELEX (Systematic Evolution of Ligands by Exponential Enrichment); however, this appears to be the first purely computational design and experimental validation of novel functional ribozymes. RNAiFold is available at http://bioinformatics.bc.edu/clotelab/RNAiFold/. PMID:25209235

  9. [Biological experiments in microgravity: equilibrium function].

    PubMed

    Gorgiladze, G I; Shipov, A A; Horn, E

    2012-01-01

    The review deals with the investigations of structural and functional modifications in the equilibrium organ (EO) in invertebrates (coelenterates, shells, crustaceans and insects) and vertebrates (fishes, amphibians, rats, primates) on different ontogenetic stages in the condition of microgravity and during readaptation to the Earth's gravity. Results of the investigations detail the adaptive strategy of terrestrial organism in the environment lacking the gravitational components that leads to the discrepancy of an inner model of the body-environment schema constructed by the central nervous system at 1 g and the novel reality. It is manifested by ataxic behavior and increased graviceptors' afferentation against efferent system inactivation. The new condition is defined as a sensibilization phase ensued by the eluding phase: behavior obeys the innate motion strategy, whereas graviceptors' afferentation decreases due to activation of the efferent system. Readaptation to 1 G takes several to 50 days and proceeds as a sequence of slow in motion behavior, ataxia and vestibular sensitization. Reactivity of the gravitosensory system to microgravity was found to be age-dependent. Gain in the EO inertial mass in microgravity and reduction with return to 1 g indicates gravity relevance to EO genesis.

  10. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

    PubMed Central

    Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  11. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

    PubMed

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  12. Modeling photon propagation in biological tissues using a generalized Delta-Eddington phase function.

    PubMed

    Cong, W; Shen, H; Cong, A; Wang, Y; Wang, G

    2007-11-01

    Photon propagation in biological tissue is commonly described by the radiative transfer equation, while the phase function in the equation represents the scattering characteristics of the medium and has significant influence on the precision of solution and the efficiency of computation. In this work, we present a generalized Delta-Eddington phase function to simplify the radiative transfer equation to an integral equation with respect to photon fluence rate. Comparing to the popular diffusion approximation model, the solution of the integral equation is highly accurate to model photon propagation in the biological tissue over a broad range of optical parameters. This methodology is validated by Monte Carlo simulation.

  13. Evidence for a Role of Executive Functions in Learning Biology

    ERIC Educational Resources Information Center

    Rhodes, Sinéad M.; Booth, Josephine N.; Campbell, Lorna Elise; Blythe, Richard A.; Wheate, Nial J.; Delibegovic, Mirela

    2014-01-01

    Research examining cognition and science learning has focused on working memory, but evidence implicates a broader set of executive functions. The current study examined executive functions and learning of biology in young adolescents. Fifty-six participants, aged 12-13?years, completed tasks of working memory (Spatial Working Memory), inhibition…

  14. Functional toxicology: a new approach to detect biologically active xenobiotics.

    PubMed Central

    McLachlan, J A

    1993-01-01

    The pervasiveness of chemicals in the environment with estrogenic activity and other biological functions recommends the development of new approaches to monitor and study them. Chemicals can be screened for activity in vitro using a panel of human or animal cells that have been transfected with a specific receptor and reporter gene; for example, the estrogen receptor. By using a variety of different receptors, the screening of xenobiotics for biological functions can be broad. Chemicals could then be classified by their function in vitro which, in some cases, may be a useful guide for toxicological studies. Images Figure 1. PMID:8119246

  15. Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

    SciTech Connect

    Davidson, George S.; Brown, William Michael

    2007-09-01

    Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

  16. Towards a behavioral-matching based compilation of synthetic biology functions.

    PubMed

    Basso-Blandin, Adrien; Delaplace, Franck

    2015-09-01

    The field of synthetic biology is looking forward engineering framework for safely designing reliable de-novo biological functions. In this undertaking, Computer-Aided-Design (CAD) environments should play a central role for facilitating the design. Although, CAD environment is widely used to engineer artificial systems the application in synthetic biology is still in its infancy. In this article we address the problem of the design of a high level language which at the core of CAD environment. More specifically the Gubs (Genomic Unified Behavioural Specification) language is a specification language used to describe the observations of the expected behaviour. The compiler appropriately selects components such that the observation of the synthetic biological function resulting to their assembly complies to the programmed behaviour.

  17. Evolutionary cell biology: functional insight from "endless forms most beautiful".

    PubMed

    Richardson, Elisabeth; Zerr, Kelly; Tsaousis, Anastasios; Dorrell, Richard G; Dacks, Joel B

    2015-12-15

    In animal and fungal model organisms, the complexities of cell biology have been analyzed in exquisite detail and much is known about how these organisms function at the cellular level. However, the model organisms cell biologists generally use include only a tiny fraction of the true diversity of eukaryotic cellular forms. The divergent cellular processes observed in these more distant lineages are still largely unknown in the general scientific community. Despite the relative obscurity of these organisms, comparative studies of them across eukaryotic diversity have had profound implications for our understanding of fundamental cell biology in all species and have revealed the evolution and origins of previously observed cellular processes. In this Perspective, we will discuss the complexity of cell biology found across the eukaryotic tree, and three specific examples of where studies of divergent cell biology have altered our understanding of key functional aspects of mitochondria, plastids, and membrane trafficking.

  18. Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014.

    PubMed

    Francescatto, Margherita; Hermans, Susanne M A; Babaei, Sepideh; Vicedo, Esmeralda; Borrel, Alexandre; Meysman, Pieter

    2015-01-01

    In this meeting report, we give an overview of the talks, presentations and posters presented at the third European Symposium of the International Society for Computational Biology (ISCB) Student Council. The event was organized as a satellite meeting of the 13th European Conference for Computational Biology (ECCB) and took place in Strasbourg, France on September 6th, 2014.

  19. Individualizing Instruction in Large Undergraduate Biology Laboratories. II. Computers and Investigation

    ERIC Educational Resources Information Center

    Norberg, Ann Marie

    1975-01-01

    Describes the following uses of computers in college biology laboratories: (1) to organize and analyze research data and (2) to simulate biological systems. Also being developed are computer simulations to systematically prepare students for independent investigations. (See also SE 515 092.) (LS)

  20. Mimicking biological functionality with polymers for biomedical applications

    NASA Astrophysics Data System (ADS)

    Green, Jordan J.; Elisseeff, Jennifer H.

    2016-12-01

    The vast opportunities for biomaterials design and functionality enabled by mimicking nature continue to stretch the limits of imagination. As both biological understanding and engineering capabilities develop, more sophisticated biomedical materials can be synthesized that have multifaceted chemical, biological and physical characteristics designed to achieve specific therapeutic goals. Mimicry is being used in the design of polymers for biomedical applications that are required locally in tissues, systemically throughout the body, and at the interface with tissues.

  1. A computer program for linear nonparametric and parametric identification of biological data.

    PubMed

    Werness, S A; Anderson, D J

    1984-01-01

    A computer program package for parametric ad nonparametric linear system identification of both static and dynamic biological data, written for an LSI-11 minicomputer with 28 K of memory, is described. The program has 11 possible commands including an instructional help command. A user can perform nonparametric spectral analysis and estimation of autocorrelation and partial autocorrelation functions of univariate data and estimate nonparametrically the transfer function and possibly an associated noise series of bivariate data. In addition, the commands provide the user the means to derive a parametric autoregressive moving average model for univariate data, to derive a parametric transfer function and noise model for bivariate data, and to perform several model evaluation tests such as pole-zero cancellation, examination of residual whiteness and uncorrelatedness with the input. The program, consisting of a main program and driver subroutine as well as six overlay segments, may be run interactively or automatically.

  2. High performance hybrid functional Petri net simulations of biological pathway models on CUDA.

    PubMed

    Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru

    2011-01-01

    Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.

  3. Can Simple Biophysical Principles Yield Complicated Biological Functions?

    NASA Astrophysics Data System (ADS)

    Liphardt, Jan

    2011-03-01

    About once a year, a new regulatory paradigm is discovered in cell biology. As of last count, eukaryotic cells have more than 40 distinct ways of regulating protein concentration and function. Regulatory possibilities include site-specific phosphorylation, epigenetics, alternative splicing, mRNA (re)localization, and modulation of nucleo-cytoplasmic transport. This raises a simple question. Do all the remarkable things cells do, require an intricately choreographed supporting cast of hundreds of molecular machines and associated signaling networks? Alternatively, are there a few simple biophysical principles that can generate apparently very complicated cellular behaviors and functions? I'll discuss two problems, spatial organization of the bacterial chemotaxis system and nucleo-cytoplasmic transport, where the latter might be true. In both cases, the ability to precisely quantify biological organization and function, at the single-molecule level, helped to find signatures of basic biological organizing principles.

  4. BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature.

    PubMed

    Sen Sarma, Moushumi; Arcoleo, David; Khetani, Radhika S; Chee, Brant; Ling, Xu; He, Xin; Jiang, Jing; Mei, Qiaozhu; Zhai, ChengXiang; Schatz, Bruce

    2011-07-01

    With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php.

  5. Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

    PubMed

    Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

    2010-02-01

    The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

  6. Metabolism and biological functions of human milk oligosaccharides.

    PubMed

    Bertino, E; Peila, C; Giuliani, F; Martano, C; Cresi, F; Di Nicola, P; Occhi, L; Sabatino, G; Fabris, C

    2012-01-01

    It is well known that breastfeeding is beneficial both for its nutritional properties and for the presence of biologically active compounds. Among these, human milk oligosaccharides (HMOs), representing the third largest fraction of human milk, have been assigned important biological functions, such as prebiotic and immunomodulatory and antimicrobial effects. HMOs are synthesized in the mammary gland by glycosyltransferase enzymes and can be divided in core-oligosaccharides, sialo-oligosaccharides, fucosyl-oligosaccharides and sialo-fucosyl-oligosaccharides on the basis of their chemical structure. Glycosyltransferases enzymes are partially regulated by genetic mechanisms; according to the expression of secretory and Lewis' genes, it is possible to classify human milk in 4 different secretory groups. We hereby present a review of the current knowledge concerning HMOs, their metabolism and main biological functions.

  7. Methods for improving simulations of biological systems: systemic computation and fractal proteins

    PubMed Central

    Bentley, Peter J.

    2009-01-01

    Modelling and simulation are becoming essential for new fields such as synthetic biology. Perhaps the most important aspect of modelling is to follow a clear design methodology that will help to highlight unwanted deficiencies. The use of tools designed to aid the modelling process can be of benefit in many situations. In this paper, the modelling approach called systemic computation (SC) is introduced. SC is an interaction-based language, which enables individual-based expression and modelling of biological systems, and the interactions between them. SC permits a precise description of a hypothetical mechanism to be written using an intuitive graph-based or a calculus-based notation. The same description can then be directly run as a simulation, merging the hypothetical mechanism and the simulation into the same entity. However, even when using well-designed modelling tools to produce good models, the best model is not always the most accurate one. Frequently, computational constraints or lack of data make it infeasible to model an aspect of biology. Simplification may provide one way forward, but with inevitable consequences of decreased accuracy. Instead of attempting to replace an element with a simpler approximation, it is sometimes possible to substitute the element with a different but functionally similar component. In the second part of this paper, this modelling approach is described and its advantages are summarized using an exemplar: the fractal protein model. Finally, the paper ends with a discussion of good biological modelling practice by presenting lessons learned from the use of SC and the fractal protein model. PMID:19324681

  8. Multilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.

    PubMed

    Davidsen, Peter K; Turan, Nil; Egginton, Stuart; Falciani, Francesco

    2016-02-01

    The overall aim of physiological research is to understand how living systems function in an integrative manner. Consequently, the discipline of physiology has since its infancy attempted to link multiple levels of biological organization. Increasingly this has involved mathematical and computational approaches, typically to model a small number of components spanning several levels of biological organization. With the advent of "omics" technologies, which can characterize the molecular state of a cell or tissue (intended as the level of expression and/or activity of its molecular components), the number of molecular components we can quantify has increased exponentially. Paradoxically, the unprecedented amount of experimental data has made it more difficult to derive conceptual models underlying essential mechanisms regulating mammalian physiology. We present an overview of state-of-the-art methods currently used to identifying biological networks underlying genomewide responses. These are based on a data-driven approach that relies on advanced computational methods designed to "learn" biology from observational data. In this review, we illustrate an application of these computational methodologies using a case study integrating an in vivo model representing the transcriptional state of hypoxic skeletal muscle with a clinical study representing muscle wasting in chronic obstructive pulmonary disease patients. The broader application of these approaches to modeling multiple levels of biological data in the context of modern physiology is discussed.

  9. Chemical master equation closure for computer-aided synthetic biology.

    PubMed

    Smadbeck, Patrick; Kaznessis, Yiannis N

    2015-01-01

    With inexpensive DNA synthesis technologies, we can now construct biological systems by quickly piecing together DNA sequences. Synthetic biology is the promising discipline that focuses on the construction of these new biological systems. Synthetic biology is an engineering discipline, and as such, it can benefit from mathematical modeling. This chapter focuses on mathematical models of biological systems. These models take the form of chemical reaction networks. The importance of stochasticity is discussed and methods to simulate stochastic reaction networks are reviewed. A closure scheme solution is also presented for the master equation of chemical reaction networks. The master equation is a complete model of randomly evolving molecular populations. Because of its ambitious character, the master equation remained unsolved for all but the simplest of molecular interaction networks for over 70 years. With the first complete solution of chemical master equations, a wide range of experimental observations of biomolecular interactions may be mathematically conceptualized. We anticipate that models based on the closure scheme described herein may assist in rationally designing synthetic biological systems.

  10. Chemical Master Equation Closure for Computer-Aided Synthetic Biology

    PubMed Central

    Smadbeck, Patrick; Kaznessis, Yiannis N.

    2016-01-01

    SUMMARY With inexpensive DNA synthesis technologies, we can now construct biological systems by quickly piecing together DNA sequences. Synthetic biology is the promising discipline that focuses on the construction of these new biological systems. Synthetic biology is an engineering discipline, and as such, it can benefit from mathematical modeling. This chapter focuses on mathematical models of biological systems. These models take the form of chemical reaction networks. The importance of stochasticity is discussed and methods to simulate stochastic reaction networks are reviewed. A closure scheme solution is also presented for the master equation of chemical reaction networks. The master equation is a complete model of randomly evolving molecular populations. Because of its ambitious character, the master equation remained unsolved for all but the simplest of molecular interaction networks for over seventy years. With the first complete solution of chemical master equations, a wide range of experimental observations of biomolecular interactions may be mathematically conceptualized. We anticipate that models based on the closure scheme described herein may assist in rationally designing synthetic biological systems. PMID:25487098

  11. Computational approaches to stochastic systems in physics and biology

    NASA Astrophysics Data System (ADS)

    Jeraldo Maldonado, Patricio Rodrigo

    calculation of the corresponding scaling laws. In Part II, I investigate the evolutionary dynamics of communities of microbes living in the gastrointestinal tracts of vertebrates, and ask to what degree their evolution is niche-driven, where organisms fitter to their environment become dominant, or if it is neutral, where the organisms evolve stochastically and are otherwise functionally equivalent within their communities. To that end, a series of computational tools were developed to pre-process, curate and reduce the data sets. In Chapter 4, I analyze the raw data for this research, namely short reads of 16S ribosomal RNA, and quantify how much of phylogenetic information is lost by using these short reads instead of full-length reads, and show that for lengths spanning 300 to 400 base pairs, we can recover some meaningful phylogenetic information. In Chapter 5, I introduce a pipeline for pre-processing, alignment and curation of libraries of short reads of rRNA. We show that this pipeline significantly reduces the artifacts usually associated with these sequences, resulting in better clustering of the sequences, and better phylogenetic trees representing their organismal relationships. In Chapter 6 I use the data processed with the above tools to analyze communities of microbes living in gastrointestinal tracts of vertebrates, and we ask to what extent the evolutionary dynamics of these communities is dominated by niche-based evolution, or if the communities behave neutrally, where evolution is random and all organisms are functionally equivalent. We conclude that there is evidence for strong niche-based dynamics, though we cannot fully discard some degree of neutral evolution. Finally, in Chapter 7 I propose a method to quantify the balance present in phylogenetic trees to compare a large-scale molecular phylogeny to full organismal taxonomies. I show that there is considerable structure in all of them, but direct comparison of both types of trees is difficult at the

  12. Accomplishment Summary 1968-1969. Biological Computer Laboratory.

    ERIC Educational Resources Information Center

    Von Foerster, Heinz; And Others

    This report summarizes theoretical, applied, and experimental studies in the areas of computational principles in complex intelligent systems, cybernetics, multivalued logic, and the mechanization of cognitive processes. This work is summarized under the following topic headings: properties of complex dynamic systems; computers and the language…

  13. Using computational biophysics to understand protein evolution and function

    NASA Astrophysics Data System (ADS)

    Ytreberg, F. Marty

    2010-10-01

    Understanding how proteins evolve and function is vital for human health (e.g., developing better drugs, predicting the outbreak of disease, etc.). In spite of its importance, little is known about the underlying molecular mechanisms behind these biological processes. Computational biophysics has emerged as a useful tool in this area due to its unique ability to obtain a detailed, atomistic view of proteins and how they interact. I will give two examples from our studies where computational biophysics has provided valuable insight: (i) Protein evolution in viruses. Our results suggest that the amino acid changes that occur during high temperature evolution of a virus decrease the binding free energy of the capsid, i.e., these changes increase capsid stability. (ii) Determining realistic structural ensembles for intrinsically disordered proteins. Most methods for determining protein structure rely on the protein folding into a single conformation, and thus are not suitable for disordered proteins. I will describe a new approach that combines experiment and simulation to generate structures for disordered proteins.

  14. Optimizing high performance computing workflow for protein functional annotation.

    PubMed

    Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

    2014-09-10

    Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

  15. A Tutorial on Analog Computation: Computing Functions over the Reals

    NASA Astrophysics Data System (ADS)

    Campagnolo, Manuel Lameiras

    The best known programmable analog computing device is the differential analyser. The concept for the device dates back to Lord Kelvin and his brother James Thomson in 1876, and was constructed in 1932 at MIT under the supervision of Vannevar Bush. The MIT differential analyser used wheel-and-disk mechanical integrators and was able to solve sixth-order differential equations. During the 1930’s, more powerful differential analysers were built. In 1941 Claude Shannon showed that given a sufficient numbers of integrators the machines could, in theory, precisely generate the solutions of all differentially algebraic equations. Shannon’s mathematical model of the differential analyser is known as the GPAC.

  16. ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

    PubMed Central

    2011-01-01

    Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on

  17. Computational biology for target discovery and characterization: a feasibility study in protein-protein interaction detection

    SciTech Connect

    Zhou, C; Zemla, A

    2009-02-25

    In this work we developed new code for detecting putative multi-domain protein-protein interactions for a small network of bacterial pathogen proteins, and determined how structure-driven domain-fusion (DF) methods should be scaled up for whole-proteome analysis. Protein-protein interactions are of great interest in structural biology and are important for understanding the biology of pathogens. The ability to predict protein-protein interactions provides a means for development of anti-microbials that may interfer with key processes in pathogenicity. The function of a protein-protein complex can be elucidated through knowledge of its structure. The overall goal of this project was to determine the feasibility of extending current LLNL capabilities to produce a high-throughput systems bio-informatics capability for identification and characterization of putative interacting protein partners within known or suspected small protein networks. We extended an existing LLNL methodology for identification of putative protein-protein interacting partners (Chakicherla et al (in review)) by writing a new code to identify multi-domain-fusion linkages (3 or more per complex). We applied these codes to the proteins in the Yersinia pestis quorum sensing network, known as the lsr operon, which comprises a virulence mechanism in this pathogen. We determined that efficient application of our computational algorithms in high-throughput for detection of putative protein-protein complexes genome wide would require pre-computation of PDB domains and construction of a domain-domain association database.

  18. Venom Proteins from Parasitoid Wasps and Their Biological Functions

    PubMed Central

    Moreau, Sébastien J. M.; Asgari, Sassan

    2015-01-01

    Parasitoid wasps are valuable biological control agents that suppress their host populations. Factors introduced by the female wasp at parasitization play significant roles in facilitating successful development of the parasitoid larva either inside (endoparasitoid) or outside (ectoparasitoid) the host. Wasp venoms consist of a complex cocktail of proteinacious and non-proteinacious components that may offer agrichemicals as well as pharmaceutical components to improve pest management or health related disorders. Undesirably, the constituents of only a small number of wasp venoms are known. In this article, we review the latest research on venom from parasitoid wasps with an emphasis on their biological function, applications and new approaches used in venom studies. PMID:26131769

  19. Venom Proteins from Parasitoid Wasps and Their Biological Functions.

    PubMed

    Moreau, Sébastien J M; Asgari, Sassan

    2015-06-26

    Parasitoid wasps are valuable biological control agents that suppress their host populations. Factors introduced by the female wasp at parasitization play significant roles in facilitating successful development of the parasitoid larva either inside (endoparasitoid) or outside (ectoparasitoid) the host. Wasp venoms consist of a complex cocktail of proteinacious and non-proteinacious components that may offer agrichemicals as well as pharmaceutical components to improve pest management or health related disorders. Undesirably, the constituents of only a small number of wasp venoms are known. In this article, we review the latest research on venom from parasitoid wasps with an emphasis on their biological function, applications and new approaches used in venom studies.

  20. Computational Interpretations of Analysis via Products of Selection Functions

    NASA Astrophysics Data System (ADS)

    Escardó, Martín; Oliva, Paulo

    We show that the computational interpretation of full comprehension via two well-known functional interpretations (dialectica and modified realizability) corresponds to two closely related infinite products of selection functions.

  1. Computer method for identification of boiler transfer functions

    NASA Technical Reports Server (NTRS)

    Miles, J. H.

    1972-01-01

    Iterative computer aided procedure was developed which provides for identification of boiler transfer functions using frequency response data. Method uses frequency response data to obtain satisfactory transfer function for both high and low vapor exit quality data.

  2. Neuroscience in the era of functional genomics and systems biology.

    PubMed

    Geschwind, Daniel H; Konopka, Genevieve

    2009-10-15

    Advances in genetics and genomics have fuelled a revolution in discovery-based, or hypothesis-generating, research that provides a powerful complement to the more directly hypothesis-driven molecular, cellular and systems neuroscience. Genetic and functional genomic studies have already yielded important insights into neuronal diversity and function, as well as disease. One of the most exciting and challenging frontiers in neuroscience involves harnessing the power of large-scale genetic, genomic and phenotypic data sets, and the development of tools for data integration and mining. Methods for network analysis and systems biology offer the promise of integrating these multiple levels of data, connecting molecular pathways to nervous system function.

  3. Computer program for Bessel and Hankel functions

    NASA Technical Reports Server (NTRS)

    Kreider, Kevin L.; Saule, Arthur V.; Rice, Edward J.; Clark, Bruce J.

    1991-01-01

    A set of FORTRAN subroutines for calculating Bessel and Hankel functions is presented. The routines calculate Bessel and Hankel functions of the first and second kinds, as well as their derivatives, for wide ranges of integer order and real or complex argument in single or double precision. Depending on the order and argument, one of three evaluation methods is used: the power series definition, an Airy function expansion, or an asymptotic expansion. Routines to calculate Airy functions and their derivatives are also included.

  4. Computational local stiffness analysis of biological cell: High aspect ratio single wall carbon nanotube tip.

    PubMed

    TermehYousefi, Amin; Bagheri, Samira; Shahnazar, Sheida; Rahman, Md Habibur; Kadri, Nahrizul Adib

    2016-02-01

    Carbon nanotubes (CNTs) are potentially ideal tips for atomic force microscopy (AFM) due to the robust mechanical properties, nanoscale diameter and also their ability to be functionalized by chemical and biological components at the tip ends. This contribution develops the idea of using CNTs as an AFM tip in computational analysis of the biological cells. The proposed software was ABAQUS 6.13 CAE/CEL provided by Dassault Systems, which is a powerful finite element (FE) tool to perform the numerical analysis and visualize the interactions between proposed tip and membrane of the cell. Finite element analysis employed for each section and displacement of the nodes located in the contact area was monitored by using an output database (ODB). Mooney-Rivlin hyperelastic model of the cell allows the simulation to obtain a new method for estimating the stiffness and spring constant of the cell. Stress and strain curve indicates the yield stress point which defines as a vertical stress and plan stress. Spring constant of the cell and the local stiffness was measured as well as the applied force of CNT-AFM tip on the contact area of the cell. This reliable integration of CNT-AFM tip process provides a new class of high performance nanoprobes for single biological cell analysis.

  5. The Human Genome Project: Biology, Computers, and Privacy.

    ERIC Educational Resources Information Center

    Cutter, Mary Ann G.; Drexler, Edward; Gottesman, Kay S.; Goulding, Philip G.; McCullough, Laurence B.; McInerney, Joseph D.; Micikas, Lynda B.; Mural, Richard J.; Murray, Jeffrey C.; Zola, John

    This module, for high school teachers, is the second of two modules about the Human Genome Project (HGP) produced by the Biological Sciences Curriculum Study (BSCS). The first section of this module provides background information for teachers about the structure and objectives of the HGP, aspects of the science and technology that underlie the…

  6. Morpho-chemistry and functionality of diseased biological tissues

    NASA Astrophysics Data System (ADS)

    Lange, Marta; Cicchi, Riccardo; Pavone, Francesco

    2014-09-01

    Heart and cardiovascular diseases are one of the most common in the world, in particular - arthrosclerosis. The aim of the research is to distinguish pathological and healthy tissue regions in biological samples, in this case - to distinguish collagen and lipid rich regions within the arterial wall. In the work a specific combination of such methods are used: FLIM and SHG in order to evaluate the biological tissue morphology and functionality, so that this research could give a contribution for creating a new biological tissue imaging standard in the closest future. During the study the most appropriate parameter for fluorescence lifetime decay was chosen in order to evaluate lifetime decay parameters and the isotropy of the arterial wall and deposition, using statistical methods FFT and GLCM. The research gives a contribution or the future investigations for evaluating lipid properties when it can de-attach from the arterial wall and cause clotting in the blood vessel or even a stroke.

  7. From Structure and Function of Proteins Toward in Silico Biology

    NASA Astrophysics Data System (ADS)

    Yamato, Ichiro

    2013-01-01

    Researches of biology are targeted on three major flows, materials (or chemicals), energy, and information. I have been mainly concerned with the studies on bioenergy transducing mechanisms. I have studied the mechanism of secondary active transport systems and proposed an affinity change mechanism as a general hypothesis, then tried to confirm that it is applicable to other kinds of bioenergy transducing systems. Choosing Na+-translocating V-type ATPase from Enterococcus hirae as target, I hypothesized the affinity change mechanism for the energy transduction of this ATPase. Here I describe several three dimensional structures of parts of the ATPase supporting my hypothesis. From such detailed and extensive researches on protein structure/function relationship, we can proceed toward the in silico biology, which I described previously in 2007 ([1] "Toward in silico biology").

  8. Functional Agents to Biologically Control Deoxynivalenol Contamination in Cereal Grains

    PubMed Central

    Tian, Ye; Tan, Yanglan; Liu, Na; Liao, Yucai; Sun, Changpo; Wang, Shuangxia; Wu, Aibo

    2016-01-01

    Mycotoxins, as microbial secondary metabolites, frequently contaminate cereal grains and pose a serious threat to human and animal health around the globe. Deoxynivalenol (DON), a commonly detected Fusarium mycotoxin, has drawn utmost attention due to high exposure levels and contamination frequency in the food chain. Biological control is emerging as a promising technology for the management of DON contamination. Functional biological control agents (BCAs), which include antagonistic microbes, natural fungicides derived from plants and detoxification enzymes, can be used to control DON contamination at different stages of grain production. In this review, studies regarding different biological agents for DON control in recent years are summarized for the first time. Furthermore, this article highlights the significance of BCAs for controlling DON contamination, as well as the need for more practical and efficient BCAs concerning food safety. PMID:27064760

  9. Computer Use and the Relation between Age and Cognitive Functioning

    ERIC Educational Resources Information Center

    Soubelet, Andrea

    2012-01-01

    This article investigates whether computer use for leisure could mediate or moderate the relations between age and cognitive functioning. Findings supported smaller age differences in measures of cognitive functioning for people who reported spending more hours using a computer. Because of the cross-sectional design of the study, two alternative…

  10. Workshop in computational molecular biology, April 15, 1991--April 14, 1994

    SciTech Connect

    Tavare, S.

    1995-04-12

    Funds from this award were used to the Workshop in Computational Molecular Biology, `91 Symposium entitled Interface: Computing Science and Statistics, Seattle, Washington, April 21, 1991; the Workshop in Statistical Issues in Molecular Biology held at Stanford, California, August 8, 1993; and the Session on Population Genetics a part of the 56th Annual Meeting, Institute of Mathematical Statistics, San Francisco, California, August 9, 1993.

  11. Constructing biological pathway models with hybrid functional Petri nets.

    PubMed

    Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru

    2004-01-01

    In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

  12. Constructing biological pathway models with hybrid functional petri nets.

    PubMed

    Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru

    2011-01-01

    In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

  13. ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.

    PubMed

    Karp, Peter D; Berger, Bonnie; Kovats, Diane; Lengauer, Thomas; Linial, Michal; Sabeti, Pardis; Hide, Winston; Rost, Burkhard

    2015-01-01

    Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida).

  14. The Effects of 3D Computer Simulation on Biology Students' Achievement and Memory Retention

    ERIC Educational Resources Information Center

    Elangovan, Tavasuria; Ismail, Zurida

    2014-01-01

    A quasi experimental study was conducted for six weeks to determine the effectiveness of two different 3D computer simulation based teaching methods, that is, realistic simulation and non-realistic simulation on Form Four Biology students' achievement and memory retention in Perak, Malaysia. A sample of 136 Form Four Biology students in Perak,…

  15. [Biological Function of The Small G Protein Rap].

    PubMed

    Li, Shan-Shan; Guo, Xiao-Xi; An, Shu; Yang, Yang; Liu, Ying; Xu, Tian-Rui

    2016-02-01

    Rap has different biological functions on intracellular signaling pathways, such as regulating cell polarity, cell proliferation, cell differentiation, cell adhesion and cell movement. Furthermore, at tissue and organ level, Rap controls the establishment of neural polarity, synaptic growth, synaptic plasticity, neuronal migration and so on. Rap belongs to Ras family which contains two subtypes, Rap1 and Rap2. By binding GTP or GDP Rap transform between active or inactive state, and plays an important role as a molecular switch. Moreover, in the signal pathway of tumor, Rap inhibits cell transformation induced by the oncogene Ras, therefore inhibits the proliferation, invasion and migration of certain cancer cells by interacting with its downstream target molecules. In this review, we summarized the biological functions of Rap and discussed It's significance in cancer therapy and drug treatment of neurological diseases.

  16. From Raw Data to Biological Discoveries: A Computational Analysis Pipeline for Mass Spectrometry-Based Proteomics

    NASA Astrophysics Data System (ADS)

    Lavallée-Adam, Mathieu; Park, Sung Kyu Robin; Martínez-Bartolomé, Salvador; He, Lin; Yates, John R.

    2015-11-01

    In the last two decades, computational tools for mass spectrometry-based proteomics data analysis have evolved from a few stand-alone software solutions serving specific goals, such as the identification of amino acid sequences based on mass spectrometry spectra, to large-scale complex pipelines integrating multiple computer programs to solve a collection of problems. This software evolution has been mostly driven by the appearance of novel technologies that allowed the community to tackle complex biological problems, such as the identification of proteins that are differentially expressed in two samples under different conditions. The achievement of such objectives requires a large suite of programs to analyze the intricate mass spectrometry data. Our laboratory addresses complex proteomics questions by producing and using algorithms and software packages. Our current computational pipeline includes, among other things, tools for mass spectrometry raw data processing, peptide and protein identification and quantification, post-translational modification analysis, and protein functional enrichment analysis. In this paper, we describe a suite of software packages we have developed to process mass spectrometry-based proteomics data and we highlight some of the new features of previously published programs as well as tools currently under development.

  17. From raw data to biological discoveries: a computational analysis pipeline for mass spectrometry-based proteomics.

    PubMed

    Lavallée-Adam, Mathieu; Park, Sung Kyu Robin; Martínez-Bartolomé, Salvador; He, Lin; Yates, John R

    2015-11-01

    In the last two decades, computational tools for mass spectrometry-based proteomics data analysis have evolved from a few stand-alone software solutions serving specific goals, such as the identification of amino acid sequences based on mass spectrometry spectra, to large-scale complex pipelines integrating multiple computer programs to solve a collection of problems. This software evolution has been mostly driven by the appearance of novel technologies that allowed the community to tackle complex biological problems, such as the identification of proteins that are differentially expressed in two samples under different conditions. The achievement of such objectives requires a large suite of programs to analyze the intricate mass spectrometry data. Our laboratory addresses complex proteomics questions by producing and using algorithms and software packages. Our current computational pipeline includes, among other things, tools for mass spectrometry raw data processing, peptide and protein identification and quantification, post-translational modification analysis, and protein functional enrichment analysis. In this paper, we describe a suite of software packages we have developed to process mass spectrometry-based proteomics data and we highlight some of the new features of previously published programs as well as tools currently under development. Graphical Abstract ᅟ.

  18. Singular Function Integration in Computational Physics

    NASA Astrophysics Data System (ADS)

    Hasbun, Javier

    2009-03-01

    In teaching computational methods in the undergraduate physics curriculum, standard integration approaches taught include the rectangular, trapezoidal, Simpson, Romberg, and others. Over time, these techniques have proven to be invaluable and students are encouraged to employ the most efficient method that is expected to perform best when applied to a given problem. However, some physics research applications require techniques that can handle singularities. While decreasing the step size in traditional approaches is an alternative, this may not always work and repetitive processes make this route even more inefficient. Here, I present two existing integration rules designed to handle singular integrals. I compare them to traditional rules as well as to the exact analytic results. I suggest that it is perhaps time to include such approaches in the undergraduate computational physics course.

  19. SU-E-T-54: Benefits of Biological Cost Functions

    SciTech Connect

    Demirag, N

    2014-06-01

    Purpose: To verify the benefits of the biological cost functions. Methods: TG166 patients were used for the test case scenarios. Patients were planned using Monaco V5.0 (CMS/Elekta, St.Louis, MO) Monaco has 3 biological and 8 physical CFs. In this study the plans were optimized using 3 different scenarios. 1- Biological CFs only 2-Physical CFs only 3- Combination of Physical and Biological CFsMonaco has 3 biological CFs. Target EUD used for the targets, derived from the poisson cell kill model, has an α value that controls the cold spots inside the target. α values used in the optimization were 0.5 and 0.8. if cold spots needs to be penalized α value increased. Serial CF: it's called serial to mimic the behaviour of the serial organs, if a high k value like 12 or 14 is used it controls the maximum dose. Serial CF has a k parameter that is used to shape the whole dvh curve. K value ranges between 1–20. k:1 is used to control the mean dose, lower k value controls the mean dose, higher k value controls the higher dose, using 2 serial CFs with different k values controls the whole DVH. Paralel CF controls the percentage of the volume that tolerates higher doses than the reference dose to mimic the behaviour of the paralel organs. Results: It was possible to achive clinically accepted plans in all 3 scenarios. The benefit of the biological cost functions were to control the mean dose for target and OAR, to shape the DVH curve using one EUD value and one k value simplifies the optimization process. Using the biological CFs alone, it was hard to control the dose at a point. Conclusion: Biological CFs in Monaco doesn't require the ntcp/tcp values from the labs and useful to shape the whole dvh curve. I work as an applications support specialist for Elekta and I am a Ph.D. Student in Istanbul University for radiation therapy physics.

  20. Identification of potential drug targets based on a computational biology algorithm for venous thromboembolism.

    PubMed

    Xie, Ruiqiang; Li, Lei; Chen, Lina; Li, Wan; Chen, Binbin; Jiang, Jing; Huang, Hao; Li, Yiran; He, Yuehan; Lv, Junjie; He, Weiming

    2017-02-01

    Venous thromboembolism (VTE) is a common, fatal and frequently recurrent disease. Changes in the activity of different coagulation factors serve as a pathophysiological basis for the recurrent risk of VTE. Systems biology approaches provide a better understanding of the pathological mechanisms responsible for recurrent VTE. In this study, a novel computational method was presented to identify the recurrent risk modules (RRMs) based on the integration of expression profiles and human signaling network, which hold promise for achieving new and deeper insights into the mechanisms responsible for VTE. The results revealed that the RRMs had good classification performance to discriminate patients with recurrent VTE. The functional annotation analysis demonstrated that the RRMs played a crucial role in the pathogenesis of VTE. Furthermore, a variety of approved drug targets in the RRM M5 were related to VTE. Thus, the M5 may be applied to select potential drug targets for combination therapy and the extended treatment of VTE.

  1. Pair correlation function integrals: Computation and use

    NASA Astrophysics Data System (ADS)

    Wedberg, Rasmus; O'Connell, John P.; Peters, Günther H.; Abildskov, Jens

    2011-08-01

    We describe a method for extending radial distribution functions obtained from molecular simulations of pure and mixed molecular fluids to arbitrary distances. The method allows total correlation function integrals to be reliably calculated from simulations of relatively small systems. The long-distance behavior of radial distribution functions is determined by requiring that the corresponding direct correlation functions follow certain approximations at long distances. We have briefly described the method and tested its performance in previous communications [R. Wedberg, J. P. O'Connell, G. H. Peters, and J. Abildskov, Mol. Simul. 36, 1243 (2010);, 10.1080/08927020903536366 Fluid Phase Equilib. 302, 32 (2011)], 10.1016/j.fluid.2010.10.004, but describe here its theoretical basis more thoroughly and derive long-distance approximations for the direct correlation functions. We describe the numerical implementation of the method in detail, and report numerical tests complementing previous results. Pure molecular fluids are here studied in the isothermal-isobaric ensemble with isothermal compressibilities evaluated from the total correlation function integrals and compared with values derived from volume fluctuations. For systems where the radial distribution function has structure beyond the sampling limit imposed by the system size, the integration is more reliable, and usually more accurate, than simple integral truncation.

  2. Biological framework for soil aggregation: Implications for ecological functions.

    NASA Astrophysics Data System (ADS)

    Ghezzehei, Teamrat; Or, Dani

    2016-04-01

    Soil aggregation is heuristically understood as agglomeration of primary particles bound together by biotic and abiotic cementing agents. The organization of aggregates is believed to be hierarchical in nature; whereby primary particles bond together to form secondary particles and subsequently merge to form larger aggregates. Soil aggregates are not permanent structures, they continuously change in response to internal and external forces and other drivers, including moisture, capillary pressure, temperature, biological activity, and human disturbances. Soil aggregation processes and the resulting functionality span multiple spatial and temporal scales. The intertwined biological and physical nature of soil aggregation, and the time scales involved precluded a universally applicable and quantifiable framework for characterizing the nature and function of soil aggregation. We introduce a biophysical framework of soil aggregation that considers the various modes and factors of the genesis, maturation and degradation of soil aggregates including wetting/drying cycles, soil mechanical processes, biological activity and the nature of primary soil particles. The framework attempts to disentangle mechanical (compaction and soil fragmentation) from in-situ biophysical aggregation and provides a consistent description of aggregate size, hierarchical organization, and life time. It also enables quantitative description of biotic and abiotic functions of soil aggregates including diffusion and storage of mass and energy as well as role of aggregates as hot spots of nutrient accumulation, biodiversity, and biogeochemical cycles.

  3. Bioclojure: a functional library for the manipulation of biological sequences

    PubMed Central

    Plieskatt, Jordan; Rinaldi, Gabriel; Brindley, Paul J.; Jia, Xinying; Potriquet, Jeremy; Bethony, Jeffrey; Mulvenna, Jason

    2014-01-01

    Motivation: BioClojure is an open-source library for the manipulation of biological sequence data written in the language Clojure. BioClojure aims to provide a functional framework for the processing of biological sequence data that provides simple mechanisms for concurrency and lazy evaluation of large datasets. Results: BioClojure provides parsers and accessors for a range of biological sequence formats, including UniProtXML, Genbank XML, FASTA and FASTQ. In addition, it provides wrappers for key analysis programs, including BLAST, SignalP, TMHMM and InterProScan, and parsers for analyzing their output. All interfaces leverage Clojure’s functional style and emphasize laziness and composability, so that BioClojure, and user-defined, functions can be chained into simple pipelines that are thread-safe and seamlessly integrate lazy evaluation. Availability and implementation: BioClojure is distributed under the Lesser GPL, and the source code is freely available from GitHub (https://github.com/s312569/clj-biosequence). Contact: jason.mulvenna@qimrberghofer.edu.au or jason.mulvenna@qimr.edu.au PMID:24794932

  4. [Genotoxic modification of nucleic acid bases and biological consequences of it. Review and prospects of experimental and computational investigations

    NASA Technical Reports Server (NTRS)

    Poltev, V. I.; Bruskov, V. I.; Shuliupina, N. V.; Rein, R.; Shibata, M.; Ornstein, R.; Miller, J.

    1993-01-01

    The review is presented of experimental and computational data on the influence of genotoxic modification of bases (deamination, alkylation, oxidation) on the structure and biological functioning of nucleic acids. Pathways are discussed for the influence of modification on coding properties of bases, on possible errors of nucleic acid biosynthesis, and on configurations of nucleotide mispairs. The atomic structure of nucleic acid fragments with modified bases and the role of base damages in mutagenesis and carcinogenesis are considered.

  5. Computer Center: 2 HyperCard Stacks for Biology.

    ERIC Educational Resources Information Center

    Duhrkopf, Richard, Ed.

    1989-01-01

    Two Hypercard stacks are reviewed including "Amino Acids," created to help students associate amino acid names with their structures, and "DNA Teacher," a tutorial on the structure and function of DNA. Availability, functions, hardware requirements, and general comments on these stacks are provided. (CW)

  6. Modeling Mendel's Laws on Inheritance in Computational Biology and Medical Sciences

    ERIC Educational Resources Information Center

    Singh, Gurmukh; Siddiqui, Khalid; Singh, Mankiran; Singh, Satpal

    2011-01-01

    The current research article is based on a simple and practical way of employing the computational power of widely available, versatile software MS Excel 2007 to perform interactive computer simulations for undergraduate/graduate students in biology, biochemistry, biophysics, microbiology, medicine in college and university classroom setting. To…

  7. A Computer-Aided Self-Testing System for Biological Psychology.

    ERIC Educational Resources Information Center

    Leiblum, M. D.; And Others

    1994-01-01

    Describes the production of a computer-aided, self-testing system for university students enrolled in a first-year course in biological psychology. Project aspects described include selection, acquisition and description of software; question banks and test structures; modes of use (computer or printed version); evaluation; and future plans. (11…

  8. Computer Literacy for Life Sciences: Helping the Digital-Era Biology Undergraduates Face Today's Research

    ERIC Educational Resources Information Center

    Smolinski, Tomasz G.

    2010-01-01

    Computer literacy plays a critical role in today's life sciences research. Without the ability to use computers to efficiently manipulate and analyze large amounts of data resulting from biological experiments and simulations, many of the pressing questions in the life sciences could not be answered. Today's undergraduates, despite the ubiquity of…

  9. Methods in Computational Neuroscience: Marine Biology Laboratory Student Projects

    DTIC Science & Technology

    1988-11-01

    models of hippocampal subsystems, a model of single CA3 and CAt pyramidal neurons was constructed with GENESIS. Biophysical and electrophysiological data...intrinsic to the hippocampus. The circuit included a CAl pyramidal cell and two inhibitory interneurons , one feed-forward, one feedback. Using known... electrophysiological results obtained from detailed experiments for this visual system, the neural network simulator GENESIS has been used during the Computational

  10. Machine learning in cell biology - teaching computers to recognize phenotypes.

    PubMed

    Sommer, Christoph; Gerlich, Daniel W

    2013-12-15

    Recent advances in microscope automation provide new opportunities for high-throughput cell biology, such as image-based screening. High-complex image analysis tasks often make the implementation of static and predefined processing rules a cumbersome effort. Machine-learning methods, instead, seek to use intrinsic data structure, as well as the expert annotations of biologists to infer models that can be used to solve versatile data analysis tasks. Here, we explain how machine-learning methods work and what needs to be considered for their successful application in cell biology. We outline how microscopy images can be converted into a data representation suitable for machine learning, and then introduce various state-of-the-art machine-learning algorithms, highlighting recent applications in image-based screening. Our Commentary aims to provide the biologist with a guide to the application of machine learning to microscopy assays and we therefore include extensive discussion on how to optimize experimental workflow as well as the data analysis pipeline.

  11. Basic mathematical function libraries for scientific computation

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1989-01-01

    Ada packages implementing selected mathematical functions for the support of scientific and engineering applications were written. The packages provide the Ada programmer with the mathematical function support found in the languages Pascal and FORTRAN as well as an extended precision arithmetic and a complete complex arithmetic. The algorithms used are fully described and analyzed. Implementation assumes that the Ada type FLOAT objects fully conform to the IEEE 754-1985 standard for single binary floating-point arithmetic, and that INTEGER objects are 32-bit entities. Codes for the Ada packages are included as appendixes.

  12. Computing Partial Transposes and Related Entanglement Functions

    NASA Astrophysics Data System (ADS)

    Maziero, Jonas

    2016-12-01

    The partial transpose (PT) is an important function for entanglement testing and quantification and also for the study of geometrical aspects of the quantum state space. In this article, considering general bipartite and multipartite discrete systems, explicit formulas ready for the numerical implementation of the PT and of related entanglement functions are presented and the Fortran code produced for that purpose is described. What is more, we obtain an analytical expression for the Hilbert-Schmidt entanglement of two-qudit systems and for the associated closest separable state. In contrast to previous works on this matter, we only use the properties of the PT, not applying Lagrange multipliers.

  13. Systems Biology Toolbox for MATLAB: a computational platform for research in systems biology.

    PubMed

    Schmidt, Henning; Jirstrand, Mats

    2006-02-15

    We present a Systems Biology Toolbox for the widely used general purpose mathematical software MATLAB. The toolbox offers systems biologists an open and extensible environment, in which to explore ideas, prototype and share new algorithms, and build applications for the analysis and simulation of biological and biochemical systems. Additionally it is well suited for educational purposes. The toolbox supports the Systems Biology Markup Language (SBML) by providing an interface for import and export of SBML models. In this way the toolbox connects nicely to other SBML-enabled modelling packages. Models are represented in an internal model format and can be described either by entering ordinary differential equations or, more intuitively, by entering biochemical reaction equations. The toolbox contains a large number of analysis methods, such as deterministic and stochastic simulation, parameter estimation, network identification, parameter sensitivity analysis and bifurcation analysis.

  14. Biological properties of extracellular vesicles and their physiological functions

    PubMed Central

    Yáñez-Mó, María; Siljander, Pia R.-M.; Andreu, Zoraida; Zavec, Apolonija Bedina; Borràs, Francesc E.; Buzas, Edit I.; Buzas, Krisztina; Casal, Enriqueta; Cappello, Francesco; Carvalho, Joana; Colás, Eva; Silva, Anabela Cordeiro-da; Fais, Stefano; Falcon-Perez, Juan M.; Ghobrial, Irene M.; Giebel, Bernd; Gimona, Mario; Graner, Michael; Gursel, Ihsan; Gursel, Mayda; Heegaard, Niels H. H.; Hendrix, An; Kierulf, Peter; Kokubun, Katsutoshi; Kosanovic, Maja; Kralj-Iglic, Veronika; Krämer-Albers, Eva-Maria; Laitinen, Saara; Lässer, Cecilia; Lener, Thomas; Ligeti, Erzsébet; Linē, Aija; Lipps, Georg; Llorente, Alicia; Lötvall, Jan; Manček-Keber, Mateja; Marcilla, Antonio; Mittelbrunn, Maria; Nazarenko, Irina; Hoen, Esther N.M. Nolte-‘t; Nyman, Tuula A.; O'Driscoll, Lorraine; Olivan, Mireia; Oliveira, Carla; Pállinger, Éva; del Portillo, Hernando A.; Reventós, Jaume; Rigau, Marina; Rohde, Eva; Sammar, Marei; Sánchez-Madrid, Francisco; Santarém, N.; Schallmoser, Katharina; Ostenfeld, Marie Stampe; Stoorvogel, Willem; Stukelj, Roman; Van der Grein, Susanne G.; Vasconcelos, M. Helena; Wauben, Marca H. M.; De Wever, Olivier

    2015-01-01

    In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system. PMID:25979354

  15. Mnk kinase pathway: Cellular functions and biological outcomes

    PubMed Central

    Joshi, Sonali; Platanias, Leonidas C

    2014-01-01

    The mitogen-activated protein kinase (MAPK) interacting protein kinases 1 and 2 (Mnk1 and Mnk2) play important roles in controlling signals involved in mRNA translation. In addition to the MAPKs (p38 or Erk), multiple studies suggest that the Mnk kinases can be regulated by other known kinases such as Pak2 and/or other unidentified kinases by phosphorylation of residues distinct from the sites phosphorylated by the MAPKs. Several studies have established multiple Mnk protein targets, including PSF, heterogenous nuclear ribonucleoprotein A1, Sprouty 2 and have lead to the identification of distinct biological functions and substrate specificity for the Mnk kinases. In this review we discuss the pathways regulating the Mnk kinases, their known substrates as well as the functional consequences of engagement of pathways controlled by Mnk kinases. These kinases play an important role in mRNA translation via their regulation of eukaryotic initiation factor 4E (eIF4E) and their functions have important implications in tumor biology as well as the regulation of drug resistance to anti-oncogenic therapies. Other studies have identified a role for the Mnk kinases in cap-independent mRNA translation, suggesting that the Mnk kinases can exert important functional effects independently of the phosphorylation of eIF4E. The role of Mnk kinases in inflammation and inflammation-induced malignancies is also discussed. PMID:25225600

  16. Biological properties of extracellular vesicles and their physiological functions.

    PubMed

    Yáñez-Mó, María; Siljander, Pia R-M; Andreu, Zoraida; Zavec, Apolonija Bedina; Borràs, Francesc E; Buzas, Edit I; Buzas, Krisztina; Casal, Enriqueta; Cappello, Francesco; Carvalho, Joana; Colás, Eva; Cordeiro-da Silva, Anabela; Fais, Stefano; Falcon-Perez, Juan M; Ghobrial, Irene M; Giebel, Bernd; Gimona, Mario; Graner, Michael; Gursel, Ihsan; Gursel, Mayda; Heegaard, Niels H H; Hendrix, An; Kierulf, Peter; Kokubun, Katsutoshi; Kosanovic, Maja; Kralj-Iglic, Veronika; Krämer-Albers, Eva-Maria; Laitinen, Saara; Lässer, Cecilia; Lener, Thomas; Ligeti, Erzsébet; Linē, Aija; Lipps, Georg; Llorente, Alicia; Lötvall, Jan; Manček-Keber, Mateja; Marcilla, Antonio; Mittelbrunn, Maria; Nazarenko, Irina; Nolte-'t Hoen, Esther N M; Nyman, Tuula A; O'Driscoll, Lorraine; Olivan, Mireia; Oliveira, Carla; Pállinger, Éva; Del Portillo, Hernando A; Reventós, Jaume; Rigau, Marina; Rohde, Eva; Sammar, Marei; Sánchez-Madrid, Francisco; Santarém, N; Schallmoser, Katharina; Ostenfeld, Marie Stampe; Stoorvogel, Willem; Stukelj, Roman; Van der Grein, Susanne G; Vasconcelos, M Helena; Wauben, Marca H M; De Wever, Olivier

    2015-01-01

    In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.

  17. Advances in cell surface glycoengineering reveal biological function.

    PubMed

    Nischan, Nicole; Kohler, Jennifer J

    2016-08-01

    Cell surface glycans are critical mediators of cell-cell, cell-ligand, and cell-pathogen interactions. By controlling the set of glycans displayed on the surface of a cell, it is possible to gain insight into the biological functions of glycans. Moreover, control of glycan expression can be used to direct cellular behavior. While genetic approaches to manipulate glycosyltransferase gene expression are available, their utility in glycan engineering has limitations due to the combinatorial nature of glycan biosynthesis and the functional redundancy of glycosyltransferase genes. Biochemical and chemical strategies offer valuable complements to these genetic approaches, notably by enabling introduction of unnatural functionalities, such as fluorophores, into cell surface glycans. Here, we describe some of the most recent developments in glycoengineering of cell surfaces, with an emphasis on strategies that employ novel chemical reagents. We highlight key examples of how these advances in cell surface glycan engineering enable study of cell surface glycans and their function. Exciting new technologies include synthetic lipid-glycans, new chemical reporters for metabolic oligosaccharide engineering to allow tandem and in vivo labeling of glycans, improved chemical and enzymatic methods for glycoproteomics, and metabolic glycosyltransferase inhibitors. Many chemical and biochemical reagents for glycan engineering are commercially available, facilitating their adoption by the biological community.

  18. Computing fuzzy associations for the analysis of biological literature.

    PubMed

    Perez-Iratxeta, Carolina; Keer, Harindar S; Bork, Peer; Andrade, Miguel A

    2002-06-01

    The increase of information in biology makes it difficult for researchers in any field to keep current with the literature. The MEDLINE database of scientific abstracts can be quickly scanned using electronic mechanisms. Potentially interesting abstracts can be selected by matching words joined by Boolean operators. However this means of selecting documents is not optimal. Nonspecific queries have to be effected, resulting in large numbers of irrelevant abstracts that have to be manually scanned To facilitate this analysis, we have developed a system that compiles a summary of subjects and related documents on the results of a MEDLINE query. For this, we have applied a fuzzy binary relation formalism that deduces relations between words present in a set of abstracts preprocessed with a standard grammatical tagger. Those relations are used to derive ensembles of related words and their associated subsets of abstracts. The algorithm can be used publicly at http:// www.bork.embl-heidelberg.de/xplormed/.

  19. How computational models can help unlock biological systems.

    PubMed

    Brodland, G Wayne

    2015-12-01

    With computation models playing an ever increasing role in the advancement of science, it is important that researchers understand what it means to model something; recognize the implications of the conceptual, mathematical and algorithmic steps of model construction; and comprehend what models can and cannot do. Here, we use examples to show that models can serve a wide variety of roles, including hypothesis testing, generating new insights, deepening understanding, suggesting and interpreting experiments, tracing chains of causation, doing sensitivity analyses, integrating knowledge, and inspiring new approaches. We show that models can bring together information of different kinds and do so across a range of length scales, as they do in multi-scale, multi-faceted embryogenesis models, some of which connect gene expression, the cytoskeleton, cell properties, tissue mechanics, morphogenetic movements and phenotypes. Models cannot replace experiments nor can they prove that particular mechanisms are at work in a given situation. But they can demonstrate whether or not a proposed mechanism is sufficient to produce an observed phenomenon. Although the examples in this article are taken primarily from the field of embryo mechanics, most of the arguments and discussion are applicable to any form of computational modelling.

  20. Biological water: Its vital role in macromolecular structure and function.

    PubMed

    Despa, Florin

    2005-12-01

    Water in tissues and cells is confined by intervening cellular components and is subject to structural effects that are not present in its bulk counterpart. The structuring effects lower the dielectric susceptibility of water molecules and induce a "red shift" of their relaxation frequency. This is also a source of polarization fields that contribute to the effective interactions between macromolecules. The behavior of water molecules at hydrophilic sites is different from that at hydrophobic sites, and this dissimilar behavior promotes the anisotropy of the hydration shell of proteins. The anisotropy of the hydration shell is essential for the enzyme function, but it is also important in detecting denaturation of the protein (i.e., proteins expose their hydrophobic parts to water during unfolding). The most significant differences between biological and ordinary water will be presented along with how this information can be used to decipher patterns in dynamical behavior of biological water and to detect possible structural changes of the cellular components.

  1. Click Chemistry Mediated Functionalization of Vertical Nanowires for Biological Applications.

    PubMed

    Vutti, Surendra; Schoffelen, Sanne; Bolinsson, Jessica; Buch-Månson, Nina; Bovet, Nicolas; Nygård, Jesper; Martinez, Karen L; Meldal, Morten

    2016-01-11

    Semiconductor nanowires (NWs) are gaining significant importance in various biological applications, such as biosensing and drug delivery. Efficient and controlled immobilization of biomolecules on the NW surface is crucial for many of these applications. Here, we present for the first time the use of the Cu(I) -catalyzed alkyne-azide cycloaddition and its strain-promoted variant for the covalent functionalization of vertical NWs with peptides and proteins. The potential of the approach was demonstrated in two complementary applications of measuring enzyme activity and protein binding, which is of general interest for biological studies. The attachment of a peptide substrate provided NW arrays for the detection of protease activity. In addition, green fluorescent protein was immobilized in a site-specific manner and recognized by antibody binding to demonstrate the proof-of-concept for the use of covalently modified NWs for diagnostic purposes using minute amounts of material.

  2. Phenological response of a key ecosystem function to biological invasion.

    PubMed

    Alp, Maria; Cucherousset, Julien; Buoro, Mathieu; Lecerf, Antoine

    2016-05-01

    Although climate warming has been widely demonstrated to induce shifts in the timing of many biological events, the phenological consequences of other prominent global change drivers remain largely unknown. Here, we investigated the effects of biological invasions on the seasonality of leaf litter decomposition, a crucial freshwater ecosystem function. Decomposition rates were quantified in 18 temperate shallow lakes distributed along a gradient of crayfish invasion and a temperature-based model was constructed to predict yearly patterns of decomposition. We found that, through direct detritus consumption, omnivorous invasive crayfish accelerated decomposition rates up to fivefold in spring, enhancing temperature dependence of the process and shortening the period of major detritus availability in the ecosystem by up to 39 days (95% CI: 15-61). The fact that our estimates are an order of magnitude higher than any previously reported climate-driven phenological shifts indicates that some powerful drivers of phenological change have been largely overlooked.

  3. Density functional theory across chemistry, physics and biology.

    PubMed

    van Mourik, Tanja; Bühl, Michael; Gaigeot, Marie-Pierre

    2014-03-13

    The past decades have seen density functional theory (DFT) evolve from a rising star in computational quantum chemistry to one of its major players. This Theme Issue, which comes half a century after the publication of the Hohenberg-Kohn theorems that laid the foundations of modern DFT, reviews progress and challenges in present-day DFT research. Rather than trying to be comprehensive, this Theme Issue attempts to give a flavour of selected aspects of DFT.

  4. Considerations to improve functional annotations in biological databases.

    PubMed

    Benítez-Páez, Alfonso

    2009-12-01

    Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community.

  5. The Human Glucocorticoid Receptor: Molecular Basis of Biologic Function

    PubMed Central

    Nicolaides, Nicolas C.; Galata, Zoi; Kino, Tomoshige; Chrousos, George P.; Charmandari, Evangelia

    2009-01-01

    The characterization of the subfamily of steroid hormone receptors has enhanced our understanding of how a set of hormonally derived lipophilic ligands controls cellular and molecular functions to influence development and help achieve homeostasis. The glucocorticopid receptor (GR), the first member of this subfamily, is a ubiquitously expressed intracellular protein, which functions as a ligand-dependent transcription factor that regulates the expression of glucocorticoid-responsive genes. The effector domains of the GR mediate transcriptional activation by recruiting coregulatory multi-subunit complexes that remodel chromatin, target initiation sites, and stabilize the RNA polymerase II machinery for repeated rounds of transcription of target genes. This review summarizes the basic aspects of the structure and of the human (h) GR, and the molecular basis of its biologic function. PMID:19818358

  6. The human glucocorticoid receptor: molecular basis of biologic function.

    PubMed

    Nicolaides, Nicolas C; Galata, Zoi; Kino, Tomoshige; Chrousos, George P; Charmandari, Evangelia

    2010-01-01

    The characterization of the subfamily of steroid hormone receptors has enhanced our understanding of how a set of hormonally derived lipophilic ligands controls cellular and molecular functions to influence development and help achieve homeostasis. The glucocorticoid receptor (GR), the first member of this subfamily, is a ubiquitously expressed intracellular protein, which functions as a ligand-dependent transcription factor that regulates the expression of glucocorticoid-responsive genes. The effector domains of the GR mediate transcriptional activation by recruiting coregulatory multi-subunit complexes that remodel chromatin, target initiation sites, and stabilize the RNA-polymerase II machinery for repeated rounds of transcription of target genes. This review summarizes the basic aspects of the structure and actions of the human (h) GR, and the molecular basis of its biologic functions.

  7. A synthetic biology framework for programming eukaryotic transcription functions.

    PubMed

    Khalil, Ahmad S; Lu, Timothy K; Bashor, Caleb J; Ramirez, Cherie L; Pyenson, Nora C; Joung, J Keith; Collins, James J

    2012-08-03

    Eukaryotic transcription factors (TFs) perform complex and combinatorial functions within transcriptional networks. Here, we present a synthetic framework for systematically constructing eukaryotic transcription functions using artificial zinc fingers, modular DNA-binding domains found within many eukaryotic TFs. Utilizing this platform, we construct a library of orthogonal synthetic transcription factors (sTFs) and use these to wire synthetic transcriptional circuits in yeast. We engineer complex functions, such as tunable output strength and transcriptional cooperativity, by rationally adjusting a decomposed set of key component properties, e.g., DNA specificity, affinity, promoter design, protein-protein interactions. We show that subtle perturbations to these properties can transform an individual sTF between distinct roles (activator, cooperative factor, inhibitory factor) within a transcriptional complex, thus drastically altering the signal processing behavior of multi-input systems. This platform provides new genetic components for synthetic biology and enables bottom-up approaches to understanding the design principles of eukaryotic transcriptional complexes and networks.

  8. Biomarkers of Aging: From Function to Molecular Biology.

    PubMed

    Wagner, Karl-Heinz; Cameron-Smith, David; Wessner, Barbara; Franzke, Bernhard

    2016-06-02

    Aging is a major risk factor for most chronic diseases and functional impairments. Within a homogeneous age sample there is a considerable variation in the extent of disease and functional impairment risk, revealing a need for valid biomarkers to aid in characterizing the complex aging processes. The identification of biomarkers is further complicated by the diversity of biological living situations, lifestyle activities and medical treatments. Thus, there has been no identification of a single biomarker or gold standard tool that can monitor successful or healthy aging. Within this short review the current knowledge of putative biomarkers is presented, focusing on their application to the major physiological mechanisms affected by the aging process including physical capability, nutritional status, body composition, endocrine and immune function. This review emphasizes molecular and DNA-based biomarkers, as well as recent advances in other biomarkers such as microRNAs, bilirubin or advanced glycation end products.

  9. Systemic Modeling of Biological Functions in Consideration of Physiome Project

    NASA Astrophysics Data System (ADS)

    Minamitani, Haruyuki

    Emerging of the physiome project provides various influences on the medical, biological and pharmaceutical development. In this paper, as an example of physiome research, neural network model analysis providing the conduction mechanisms of pain and tactile sensations was presented, and the functional relations between neural activities of the network cells and stimulus intensity applied on the peripheral receptive fields were described. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature. The functional activities of spinothalamic and thalamocortical cells show a good agreement with the physiological and psychophysical functions of somatosensory system that are very instructive for covering the gap between physiologically and psychophysically aspects of pain and tactile sensation.

  10. Biomarkers of Aging: From Function to Molecular Biology

    PubMed Central

    Wagner, Karl-Heinz; Cameron-Smith, David; Wessner, Barbara; Franzke, Bernhard

    2016-01-01

    Aging is a major risk factor for most chronic diseases and functional impairments. Within a homogeneous age sample there is a considerable variation in the extent of disease and functional impairment risk, revealing a need for valid biomarkers to aid in characterizing the complex aging processes. The identification of biomarkers is further complicated by the diversity of biological living situations, lifestyle activities and medical treatments. Thus, there has been no identification of a single biomarker or gold standard tool that can monitor successful or healthy aging. Within this short review the current knowledge of putative biomarkers is presented, focusing on their application to the major physiological mechanisms affected by the aging process including physical capability, nutritional status, body composition, endocrine and immune function. This review emphasizes molecular and DNA-based biomarkers, as well as recent advances in other biomarkers such as microRNAs, bilirubin or advanced glycation end products. PMID:27271660

  11. Enumeration of Bent Boolean Functions by Reconfigurable Computer

    DTIC Science & Technology

    2010-05-01

    Publishing Company, 1986. [10] D. H. Knuth , The Art of Computer Programming, 2nd Ed., Addison- Wesley Publishing Co., Reading, Menlo Park, London...Enumeration of Bent Boolean Functions by Reconfigurable Computer J. L. Shafer S. W. Schneider J. T. Butler P. Stănică ECE Department Department of ...it yields a new realization of the transeunt triangle that has less complexity and delay. Finally, we show computational results from a

  12. Supervised learning with decision tree-based methods in computational and systems biology.

    PubMed

    Geurts, Pierre; Irrthum, Alexandre; Wehenkel, Louis

    2009-12-01

    At the intersection between artificial intelligence and statistics, supervised learning allows algorithms to automatically build predictive models from just observations of a system. During the last twenty years, supervised learning has been a tool of choice to analyze the always increasing and complexifying data generated in the context of molecular biology, with successful applications in genome annotation, function prediction, or biomarker discovery. Among supervised learning methods, decision tree-based methods stand out as non parametric methods that have the unique feature of combining interpretability, efficiency, and, when used in ensembles of trees, excellent accuracy. The goal of this paper is to provide an accessible and comprehensive introduction to this class of methods. The first part of the review is devoted to an intuitive but complete description of decision tree-based methods and a discussion of their strengths and limitations with respect to other supervised learning methods. The second part of the review provides a survey of their applications in the context of computational and systems biology.

  13. Computational biology approach to uncover hepatitis C virus helicase operation

    PubMed Central

    Flechsig, Holger

    2014-01-01

    Hepatitis C virus (HCV) helicase is a molecular motor that splits nucleic acid duplex structures during viral replication, therefore representing a promising target for antiviral treatment. Hence, a detailed understanding of the mechanism by which it operates would facilitate the development of efficient drug-assisted therapies aiming to inhibit helicase activity. Despite extensive investigations performed in the past, a thorough understanding of the activity of this important protein was lacking since the underlying internal conformational motions could not be resolved. Here we review investigations that have been previously performed by us for HCV helicase. Using methods of structure-based computational modelling it became possible to follow entire operation cycles of this motor protein in structurally resolved simulations and uncover the mechanism by which it moves along the nucleic acid and accomplishes strand separation. We also discuss observations from that study in the light of recent experimental studies that confirm our findings. PMID:24707123

  14. Computational biology approach to uncover hepatitis C virus helicase operation.

    PubMed

    Flechsig, Holger

    2014-04-07

    Hepatitis C virus (HCV) helicase is a molecular motor that splits nucleic acid duplex structures during viral replication, therefore representing a promising target for antiviral treatment. Hence, a detailed understanding of the mechanism by which it operates would facilitate the development of efficient drug-assisted therapies aiming to inhibit helicase activity. Despite extensive investigations performed in the past, a thorough understanding of the activity of this important protein was lacking since the underlying internal conformational motions could not be resolved. Here we review investigations that have been previously performed by us for HCV helicase. Using methods of structure-based computational modelling it became possible to follow entire operation cycles of this motor protein in structurally resolved simulations and uncover the mechanism by which it moves along the nucleic acid and accomplishes strand separation. We also discuss observations from that study in the light of recent experimental studies that confirm our findings.

  15. mRNA capping: biological functions and applications

    PubMed Central

    Ramanathan, Anand; Robb, G. Brett; Chan, Siu-Hong

    2016-01-01

    The 5′ m7G cap is an evolutionarily conserved modification of eukaryotic mRNA. Decades of research have established that the m7G cap serves as a unique molecular module that recruits cellular proteins and mediates cap-related biological functions such as pre-mRNA processing, nuclear export and cap-dependent protein synthesis. Only recently has the role of the cap 2′O methylation as an identifier of self RNA in the innate immune system against foreign RNA has become clear. The discovery of the cytoplasmic capping machinery suggests a novel level of control network. These new findings underscore the importance of a proper cap structure in the synthesis of functional messenger RNA. In this review, we will summarize the current knowledge of the biological roles of mRNA caps in eukaryotic cells. We will also discuss different means that viruses and their host cells use to cap their RNA and the application of these capping machineries to synthesize functional mRNA. Novel applications of RNA capping enzymes in the discovery of new RNA species and sequencing the microbiome transcriptome will also be discussed. We will end with a summary of novel findings in RNA capping and the questions these findings pose. PMID:27317694

  16. Hyaluronan: A Simple Polysaccharide with Diverse Biological Functions

    PubMed Central

    Dicker, Kevin T.; Gurski, Lisa A.; Pradhan-Bhatt, Swati; Witt, Robert L.; Farach-Carson, Mary C.; Jia, Xinqiao

    2014-01-01

    Hyaluronan (HA) is a linear polysaccharide with disaccharide repeats of D-glucuronic acid and N-acetyl-D-glucosamine. It is evolutionary conserved and abundantly expressed in the extracellular matrix (ECM), on the cell surface and even inside cells. Being a simple polysaccharide, HA exhibits an astonishing array of biological functions. HA interacts with various proteins or proteoglycans to organize the ECM and to maintain tissue homeostasis. The unique physical and mechanical properties of HA contribute to the maintenance of tissue hydration, the mediation of solute diffusion through the extracellular space and the lubrication of certain tissues. The diverse biological functions of HA are manifested through its complex interactions with matrix components and resident cells. Binding of HA with cell surface receptors activates various signaling pathways that regulate cell function, tissue development, inflammation, wound healing and tumor progression and metastasis. Taking advantage of the inherent biocompatibility and biodegradability of HA, as well as its susceptibility to chemical modification, researchers have developed various HA-based biomaterials and tissue constructs with promising and broad clinical potential. In this article, we illustrate the properties of HA from a matrix biology perspective by first introducing principles underlying the biosynthesis and biodegradation of HA, as well as the interactions of HA with various proteins and proteoglycans. We next highlight the roles of HA in physiological and pathological states, including morphogenesis, wound healing and tumor metastasis. A deeper understanding of the mechanisms underlying the roles of HA in various physiological processes can provide new insights and tools for the engineering of complex tissues and tissue models. PMID:24361428

  17. Biological neural networks as model systems for designing future parallel processing computers

    NASA Technical Reports Server (NTRS)

    Ross, Muriel D.

    1991-01-01

    One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.

  18. Functionalization of polydopamine coated magnetic nanoparticles with biological entities

    NASA Astrophysics Data System (ADS)

    Mǎgeruşan, Lidia; Mrówczyński, Radosław; Turcu, Rodica

    2015-12-01

    New hybrid materials, obtained through introduction of cysteine, lysine and folic acid as biological entities into polydopamine-coated magnetite nanoparticles, are reported. The syntheses are straight forward and various methods were applied for structural and morphological characterization of the resulting nanoparticles. XPS proved a very powerful tool for surface chemical analysis and it evidences the functionalization of polydopamine coated magnetite nanoparticles. The superparamagnetic behavior and the high values of saturation magnetization recommend all products for further application where magnetism is important for targeting, separation, or heating by alternative magnetic fields.

  19. Iterated Function System and Multifractal Analysis of Biological Sequences

    NASA Astrophysics Data System (ADS)

    Yu, Zu-Guo; Anh, Vo; Lau, Ka-Sing

    The fractal method has been successfully used to study many problems in physics, mathematics, engineering, finance, even in biology till now. In the past decade or so there has been a ground swell of interest in unravelling the mysteries of DNA. How to get more bioinformations from these DNA sequences is a challenging problem. The problem of classification and evolution relationship of organisms are the central problems in bioinformatics. And it is also very hard to predict the secondary and space structure of a protein from its amino acid sequence. In this paper, some recent results related these problems obtained through multifractal analysis and iterated function system (IFS) model are introduced.

  20. Big data and computational biology strategy for personalized prognosis.

    PubMed

    Ow, Ghim Siong; Tang, Zhiqun; Kuznetsov, Vladimir A

    2016-06-28

    The era of big data and precision medicine has led to accumulation of massive datasets of gene expression data and clinical information of patients. For a new patient, we propose that identification of a highly similar reference patient from an existing patient database via similarity matching of both clinical and expression data could be useful for predicting the prognostic risk or therapeutic efficacy.Here, we propose a novel methodology to predict disease/treatment outcome via analysis of the similarity between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). Our analyses revealed that Euclidean distance rather correlation distance measure was effective in defining an unbiased similarity measure calculated between two PSVs.We implemented our methods to high-grade serous ovarian cancer (HGSC) based on a 36-mRNA predictor that was previously shown to stratify patients into 3 distinct prognostic subgroups. We studied and revealed that patient's age, when converted into binary variable, was positively correlated with the overall risk of succumbing to the disease. When applied to an independent testing dataset, the inclusion of age into the molecular predictor provided more robust personalized prognosis of overall survival correlated with the therapeutic response of HGSC and provided benefit for treatment targeting of the tumors in HGSC patients.Finally, our method can be generalized and implemented in many other diseases to accurately predict personalized patients' outcomes.

  1. Big data and computational biology strategy for personalized prognosis

    PubMed Central

    Ow, Ghim Siong; Tang, Zhiqun; Kuznetsov, Vladimir A.

    2016-01-01

    The era of big data and precision medicine has led to accumulation of massive datasets of gene expression data and clinical information of patients. For a new patient, we propose that identification of a highly similar reference patient from an existing patient database via similarity matching of both clinical and expression data could be useful for predicting the prognostic risk or therapeutic efficacy. Here, we propose a novel methodology to predict disease/treatment outcome via analysis of the similarity between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). Our analyses revealed that Euclidean distance rather correlation distance measure was effective in defining an unbiased similarity measure calculated between two PSVs. We implemented our methods to high-grade serous ovarian cancer (HGSC) based on a 36-mRNA predictor that was previously shown to stratify patients into 3 distinct prognostic subgroups. We studied and revealed that patient's age, when converted into binary variable, was positively correlated with the overall risk of succumbing to the disease. When applied to an independent testing dataset, the inclusion of age into the molecular predictor provided more robust personalized prognosis of overall survival correlated with the therapeutic response of HGSC and provided benefit for treatment targeting of the tumors in HGSC patients. Finally, our method can be generalized and implemented in many other diseases to accurately predict personalized patients’ outcomes. PMID:27229533

  2. Persistence and availability of Web services in computational biology.

    PubMed

    Schultheiss, Sebastian J; Münch, Marc-Christian; Andreeva, Gergana D; Rätsch, Gunnar

    2011-01-01

    We have conducted a study on the long-term availability of bioinformatics Web services: an observation of 927 Web services published in the annual Nucleic Acids Research Web Server Issues between 2003 and 2009. We found that 72% of Web sites are still available at the published addresses, only 9% of services are completely unavailable. Older addresses often redirect to new pages. We checked the functionality of all available services: for 33%, we could not test functionality because there was no example data or a related problem; 13% were truly no longer working as expected; we could positively confirm functionality only for 45% of all services. Additionally, we conducted a survey among 872 Web Server Issue corresponding authors; 274 replied. 78% of all respondents indicate their services have been developed solely by students and researchers without a permanent position. Consequently, these services are in danger of falling into disrepair after the original developers move to another institution, and indeed, for 24% of services, there is no plan for maintenance, according to the respondents. We introduce a Web service quality scoring system that correlates with the number of citations: services with a high score are cited 1.8 times more often than low-scoring services. We have identified key characteristics that are predictive of a service's survival, providing reviewers, editors, and Web service developers with the means to assess or improve Web services. A Web service conforming to these criteria receives more citations and provides more reliable service for its users. The most effective way of ensuring continued access to a service is a persistent Web address, offered either by the publishing journal, or created on the authors' own initiative, for example at http://bioweb.me. The community would benefit the most from a policy requiring any source code needed to reproduce results to be deposited in a public repository.

  3. Converting differential-equation models of biological systems to membrane computing.

    PubMed

    Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

    2013-12-01

    This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular.

  4. Computationally efficient measure of topological redundancy of biological and social networks

    NASA Astrophysics Data System (ADS)

    Albert, Réka; Dasgupta, Bhaskar; Hegde, Rashmi; Sivanathan, Gowri Sangeetha; Gitter, Anthony; Gürsoy, Gamze; Paul, Pradyut; Sontag, Eduardo

    2011-09-01

    It is well known that biological and social interaction networks have a varying degree of redundancy, though a consensus of the precise cause of this is so far lacking. In this paper, we introduce a topological redundancy measure for labeled directed networks that is formal, computationally efficient, and applicable to a variety of directed networks such as cellular signaling, and metabolic and social interaction networks. We demonstrate the computational efficiency of our measure by computing its value and statistical significance on a number of biological and social networks with up to several thousands of nodes and edges. Our results suggest a number of interesting observations: (1) Social networks are more redundant that their biological counterparts, (2) transcriptional networks are less redundant than signaling networks, (3) the topological redundancy of the C. elegans metabolic network is largely due to its inclusion of currency metabolites, and (4) the redundancy of signaling networks is highly (negatively) correlated with the monotonicity of their dynamics.

  5. Computational predictions provide insights into the biology of TAL effector target sites.

    PubMed

    Grau, Jan; Wolf, Annett; Reschke, Maik; Bonas, Ulla; Posch, Stefan; Boch, Jens

    2013-01-01

    Transcription activator-like (TAL) effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs) that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open-source Java library

  6. Diffusion of innovations dynamics, biological growth and catenary function

    NASA Astrophysics Data System (ADS)

    Guseo, Renato

    2016-12-01

    The catenary function has a well-known role in determining the shape of chains and cables supported at their ends under the force of gravity. This enables design using a specific static equilibrium over space. Its reflected version, the catenary arch, allows the construction of bridges and arches exploiting the dual equilibrium property under uniform compression. In this paper, we emphasize a further connection with well-known aggregate biological growth models over time and the related diffusion of innovation key paradigms (e.g., logistic and Bass distributions over time) that determine self-sustaining evolutionary growth dynamics in naturalistic and socio-economic contexts. Moreover, we prove that the 'local entropy function', related to a logistic distribution, is a catenary and vice versa. This special invariance may be explained, at a deeper level, through the Verlinde's conjecture on the origin of gravity as an effect of the entropic force.

  7. STAT6: its role in interleukin 4-mediated biological functions.

    PubMed

    Takeda, K; Kishimoto, T; Akira, S

    1997-05-01

    Interleukin (IL) 4 is known to be a cytokine which plays a central role in the regulation of immune response. Studies on cytokine signal transduction have clarified the mechanism by which IL4 exerts its functions. Two cytoplasmic proteins, signal transducer and activator of transcription (STAT) 6 and IL4-induced phosphotyrosine substrate/insulin receptor substrate 2 (4PS/IRS2), are activated in IL4 signal transduction. Recent studies from STAT6-deficient mice have revealed the essential role of STAT6 in IL4-mediated biological actions. In addition, STAT6 has also been demonstrated to be important for the functions mediated by IL13, which is related to IL4. IL4 and IL13 have been shown to induce the production of IgE, which is a major mediator in an allergic response. These findings indicate that STAT6 activation is involved in IL4- and IL13-mediated disorders such as allergy.

  8. Adaptive diffusion kernel learning from biological networks for protein function prediction

    PubMed Central

    Sun, Liang; Ji, Shuiwang; Ye, Jieping

    2008-01-01

    Background Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods are suitable for learning from graph-based data such as biological networks, as they only require the abstraction of the similarities between objects into the kernel matrix. One key issue in kernel methods is the selection of a good kernel function. Diffusion kernels, the discretization of the familiar Gaussian kernel of Euclidean space, are commonly used for graph-based data. Results In this paper, we address the issue of learning an optimal diffusion kernel, in the form of a convex combination of a set of pre-specified kernels constructed from biological networks, for protein function prediction. Most prior work on this kernel learning task focus on variants of the loss function based on Support Vector Machines (SVM). Their extensions to other loss functions such as the one based on Kullback-Leibler (KL) divergence, which is more suitable for mining biological networks, lead to expensive optimization problems. By exploiting the special structure of the diffusion kernel, we show that this KL divergence based kernel learning problem can be formulated as a simple optimization problem, which can then be solved efficiently. It is further extended to the multi-task case where we predict multiple functions of a protein simultaneously. We evaluate the efficiency and effectiveness of the proposed algorithms using two benchmark data sets. Conclusion Results show that the performance of linearly combined diffusion kernel is better than every single candidate diffusion kernel. When the number of tasks is large, the algorithms based on multiple tasks are favored due to their competitive recognition performance and small computational costs. PMID:18366736

  9. Dynamics of Boolean networks controlled by biologically meaningful functions.

    PubMed

    Raeymaekers, L

    2002-10-07

    The remarkably stable dynamics displayed by randomly constructed Boolean networks is one of the most striking examples of the spontaneous emergence of self-organization in model systems composed of many interacting elements (Kauffman, S., J. theor. Biol.22, 437-467, 1969; The Origins of Order, Oxford University Press, Oxford, 1993). The dynamics of such networks is most stable for a connectivity of two inputs per element, and decreases dramatically with increasing number of connections. Whereas the simplicity of this model system allows the tracing of the dynamical trajectories, it leaves out many features of real biological connections. For instance, the dynamics has been studied in detail only for networks constructed by allowing all theoretically possible Boolean rules, whereas only a subset of them make sense in the material world. This paper analyses the effect on the dynamics of using only Boolean functions which are meaningful in a biological sense. This analysis is particularly relevant for nets with more than two inputs per element because biological networks generally appear to be more extensively interconnected. Sets of the meaningful functions were assembled for up to four inputs per element. The use of these rules results in a smaller number of distinct attractors which have a shorter length, with relatively little sensitivity to the size of the network and to the number of inputs per element. Forcing away the activator/inhibitor ratio from the expected value of 50% further enhances the stability. This effect is more pronounced for networks consisting of a majority of activators than for networks with a corresponding majority of inhibitors, indicating that the former allow the evolution of larger genetic networks. The data further support the idea of the usefulness of logical networks as a conceptual framework for the understanding of real-world phenomena.

  10. [Histidine triad protein superfamily--biological function and enzymatic activity].

    PubMed

    Krakowiak, Agnieszka; Fryc, Izabela

    2012-01-01

    The HIT superfamily consists of proteins that share the histidine triad motif, His-X-His-X-His-X-X (where X is a hydrophobic amino acid), which constitutes enzymatic catalytic center. These enzymes act as nucleotidylyl hydrolase or transferase, and the mutation of the second histidine in the triad abolishes their activity. HIT proteins were found ubiquitous in all organisms and they were classified into 5 branches, which are represented by human proteins: HINT1, FHIT, Aprataxin, GALT and DCPS. Because HINT1 orthologs, which belong to the evolutionally oldest family branch, were found from prokaryotes to eukaryotes, it is clear that HIT motif was conserved during the evolution what means that the enzymatic activity is necessary for functions of these proteins. However, in few cases, e.g. HINT1 and FHIT, the connection between the biological function and the enzymatic activity is still obscure. In this review, the relations between biology and activity for 7 HIT proteins, which were found in human, are highlighted.

  11. Sucrose metabolism gene families and their biological functions

    PubMed Central

    Jiang, Shu-Ye; Chi, Yun-Hua; Wang, Ji-Zhou; Zhou, Jun-Xia; Cheng, Yan-Song; Zhang, Bao-Lan; Ma, Ali; Vanitha, Jeevanandam; Ramachandran, Srinivasan

    2015-01-01

    Sucrose, as the main product of photosynthesis, plays crucial roles in plant development. Although studies on general metabolism pathway were well documented, less information is available on the genome-wide identification of these genes, their expansion and evolutionary history as well as their biological functions. We focused on four sucrose metabolism related gene families including sucrose synthase, sucrose phosphate synthase, sucrose phosphate phosphatase and UDP-glucose pyrophosphorylase. These gene families exhibited different expansion and evolutionary history as their host genomes experienced differentiated rates of the whole genome duplication, tandem and segmental duplication, or mobile element mediated gene gain and loss. They were evolutionarily conserved under purifying selection among species and expression divergence played important roles for gene survival after expansion. However, we have detected recent positive selection during intra-species divergence. Overexpression of 15 sorghum genes in Arabidopsis revealed their roles in biomass accumulation, flowering time control, seed germination and response to high salinity and sugar stresses. Our studies uncovered the molecular mechanisms of gene expansion and evolution and also provided new insight into the role of positive selection in intra-species divergence. Overexpression data revealed novel biological functions of these genes in flowering time control and seed germination under normal and stress conditions. PMID:26616172

  12. Event-based text mining for biology and functional genomics

    PubMed Central

    Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B.

    2015-01-01

    The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. PMID:24907365

  13. iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

    PubMed Central

    Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

    2008-01-01

    The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource

  14. iTools: a framework for classification, categorization and integration of computational biology resources.

    PubMed

    Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

    2008-05-28

    The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management

  15. DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics

    SciTech Connect

    Wallace, Susan S.

    2008-02-21

    The overall goal of the DOE EPSCoR Initiative in Structural and Computational Biology was to enhance the competiveness of Vermont research in these scientific areas. To develop self-sustaining infrastructure, we increased the critical mass of faculty, developed shared resources that made junior researchers more competitive for federal research grants, implemented programs to train graduate and undergraduate students who participated in these research areas and provided seed money for research projects. During the time period funded by this DOE initiative: (1) four new faculty were recruited to the University of Vermont using DOE resources, three in Computational Biology and one in Structural Biology; (2) technical support was provided for the Computational and Structural Biology facilities; (3) twenty-two graduate students were directly funded by fellowships; (4) fifteen undergraduate students were supported during the summer; and (5) twenty-eight pilot projects were supported. Taken together these dollars resulted in a plethora of published papers, many in high profile journals in the fields and directly impacted competitive extramural funding based on structural or computational biology resulting in 49 million dollars awarded in grants (Appendix I), a 600% return on investment by DOE, the State and University.

  16. Computer-Intensive Algebra and Students' Conceptual Knowledge of Functions.

    ERIC Educational Resources Information Center

    O'Callaghan, Brian R.

    1998-01-01

    Describes a research project that examined the effects of the Computer-Intensive Algebra (CIA) and traditional algebra curricula on students' (N=802) understanding of the function concept. Results indicate that CIA students achieved a better understanding of functions and were better at the components of modeling, interpreting, and translating.…

  17. Evaluation of Computer Games for Learning about Mathematical Functions

    ERIC Educational Resources Information Center

    Tüzün, Hakan; Arkun, Selay; Bayirtepe-Yagiz, Ezgi; Kurt, Funda; Yermeydan-Ugur, Benlihan

    2008-01-01

    In this study, researchers evaluated the usability of game environments for teaching and learning about mathematical functions. A 3-Dimensional multi-user computer game called as "Quest Atlantis" has been used, and an educational game about mathematical functions has been developed in parallel to the Quest Atlantis' technical and…

  18. Positive Wigner functions render classical simulation of quantum computation efficient.

    PubMed

    Mari, A; Eisert, J

    2012-12-07

    We show that quantum circuits where the initial state and all the following quantum operations can be represented by positive Wigner functions can be classically efficiently simulated. This is true both for continuous-variable as well as discrete variable systems in odd prime dimensions, two cases which will be treated on entirely the same footing. Noting the fact that Clifford and Gaussian operations preserve the positivity of the Wigner function, our result generalizes the Gottesman-Knill theorem. Our algorithm provides a way of sampling from the output distribution of a computation or a simulation, including the efficient sampling from an approximate output distribution in the case of sampling imperfections for initial states, gates, or measurements. In this sense, this work highlights the role of the positive Wigner function as separating classically efficiently simulable systems from those that are potentially universal for quantum computing and simulation, and it emphasizes the role of negativity of the Wigner function as a computational resource.

  19. An interdepartmental Ph.D. program in computational biology and bioinformatics: the Yale perspective.

    PubMed

    Gerstein, Mark; Greenbaum, Dov; Cheung, Kei; Miller, Perry L

    2007-02-01

    Computational biology and bioinformatics (CBB), the terms often used interchangeably, represent a rapidly evolving biological discipline. With the clear potential for discovery and innovation, and the need to deal with the deluge of biological data, many academic institutions are committing significant resources to develop CBB research and training programs. Yale formally established an interdepartmental Ph.D. program in CBB in May 2003. This paper describes Yale's program, discussing the scope of the field, the program's goals and curriculum, as well as a number of issues that arose in implementing the program. (Further updated information is available from the program's website, www.cbb.yale.edu.)

  20. Analogy between language and biology: a functional approach.

    PubMed

    Victorri, Bernard

    2007-03-01

    We adopt here a functional approach to the classical comparison between language and biology. We first parallel events which have a functional signification in each domain, by matching the utterance of a sentence with the release of a protein. The meaning of a protein is then defined by analogy as "the constant contribution of the biochemical material composing the protein to the effects produced by any release of the protein". The proteome of an organism corresponds to an I-language (the idiolect of an individual), and the proteome of a species is equivalent to an E-language (a language in the common sense). Proteins and sentences are both characterized by a complex hierarchical structure, but the language property of 'double articulation' has no equivalent in the biological domain in this analogy, contrary to previous proposals centered on the genetic code. Besides, the same intimate relation between structure and meaning holds in both cases (syntactic structure for sentences and three-dimensional conformation for proteins). An important disanalogy comes from the combinatorial power of language which is not shared by the proteome as a whole, but it must be noted that the immune system possesses interesting properties in this respect. Regarding evolutionary aspects, the analogy still works to a certain extent. Languages and proteomes can be both considered as belonging to a general class of systems, that we call "productive self-reproductive systems", characterized by the presence of two dynamics: a fast dynamics in an external domain where functional events occur (productive aspect), and a slow dynamics responsible for the evolution of the system itself, driven by the feed-back of events related to the reproduction process.

  1. Drug target identification in sphingolipid metabolism by computational systems biology tools: metabolic control analysis and metabolic pathway analysis.

    PubMed

    Ozbayraktar, F Betül Kavun; Ulgen, Kutlu O

    2010-08-01

    Sphingolipids regulate cellular processes that are critically important in cell's fate and function in cancer development and progression. This fact underlies the basics of the novel cancer therapy approach. The pharmacological manipulation of the sphingolipid metabolism in cancer therapeutics necessitates the detailed understanding of the pathway. Two computational systems biology tools are used to identify potential drug target enzymes among sphingolipid pathway that can be further utilized in drug design studies for cancer therapy. The enzymes in sphingolipid pathway were ranked according to their roles in controlling the metabolic network by metabolic control analysis. The physiologically connected reactions, i.e. biologically significant and functional modules of network, were identified by metabolic pathway analysis. The final set of candidate drug target enzymes are selected such that their manipulation leads to ceramide accumulation and long chain base phosphates depletion. The mathematical tools' efficiency for drug target identification performed in this study is validated by clinically available drugs.

  2. Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

    PubMed

    Hucka, M; Finney, A; Bornstein, B J; Keating, S M; Shapiro, B E; Matthews, J; Kovitz, B L; Schilstra, M J; Funahashi, A; Doyle, J C; Kitano, H

    2004-06-01

    Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

  3. Removing the center from computing: biology's new mode of digital knowledge production.

    PubMed

    November, Joseph

    2011-06-01

    This article shows how the USA's National Institutes of Health (NIH) helped to bring about a major shift in the way computers are used to produce knowledge and in the design of computers themselves as a consequence of its early 1960s efforts to introduce information technology to biologists. Starting in 1960 the NIH sought to reform the life sciences by encouraging researchers to make use of digital electronic computers, but despite generous federal support biologists generally did not embrace the new technology. Initially the blame fell on biologists' lack of appropriate (i.e. digital) data for computers to process. However, when the NIH consulted MIT computer architect Wesley Clark about this problem, he argued that the computer's quality as a device that was centralized posed an even greater challenge to potential biologist users than did the computer's need for digital data. Clark convinced the NIH that if the agency hoped to effectively computerize biology, it would need to satisfy biologists' experimental and institutional needs by providing them the means to use a computer without going to a computing center. With NIH support, Clark developed the 1963 Laboratory Instrument Computer (LINC), a small, real-time interactive computer intended to be used inside the laboratory and controlled entirely by its biologist users. Once built, the LINC provided a viable alternative to the 1960s norm of large computers housed in computing centers. As such, the LINC not only became popular among biologists, but also served in later decades as an important precursor of today's computing norm in the sciences and far beyond, the personal computer.

  4. Proteomic profiling of high risk medulloblastoma reveals functional biology.

    PubMed

    Staal, Jerome A; Lau, Ling San; Zhang, Huizhen; Ingram, Wendy J; Hallahan, Andrew R; Northcott, Paul A; Pfister, Stefan M; Wechsler-Reya, Robert J; Rusert, Jessica M; Taylor, Michael D; Cho, Yoon-Jae; Packer, Roger J; Brown, Kristy J; Rood, Brian R

    2015-06-10

    Genomic characterization of medulloblastoma has improved molecular risk classification but struggles to define functional biological processes, particularly for the most aggressive subgroups. We present here a novel proteomic approach to this problem using a reference library of stable isotope labeled medulloblastoma-specific proteins as a spike-in standard for accurate quantification of the tumor proteome. Utilizing high-resolution mass spectrometry, we quantified the tumor proteome of group 3 medulloblastoma cells and demonstrate that high-risk MYC amplified tumors can be segregated based on protein expression patterns. We cross-validated the differentially expressed protein candidates using an independent transcriptomic data set and further confirmed them in a separate cohort of medulloblastoma tissue samples to identify the most robust proteogenomic differences. Interestingly, highly expressed proteins associated with MYC-amplified tumors were significantly related to glycolytic metabolic pathways via alternative splicing of pyruvate kinase (PKM) by heterogeneous ribonucleoproteins (HNRNPs). Furthermore, when maintained under hypoxic conditions, these MYC-amplified tumors demonstrated increased viability compared to non-amplified tumors within the same subgroup. Taken together, these findings highlight the power of proteomics as an integrative platform to help prioritize genetic and molecular drivers of cancer biology and behavior.

  5. Androgen Receptor Structure, Function and Biology: From Bench to Bedside

    PubMed Central

    Davey, Rachel A; Grossmann, Mathis

    2016-01-01

    The actions of androgens such as testosterone and dihydrotestosterone are mediated via the androgen receptor (AR), a ligand-dependent nuclear transcription factor and member of the steroid hormone nuclear receptor family. Given its widespread expression in many cells and tissues, the AR has a diverse range of biological actions including important roles in the development and maintenance of the reproductive, musculoskeletal, cardiovascular, immune, neural and haemopoietic systems. AR signalling may also be involved in the development of tumours in the prostate, bladder, liver, kidney and lung. Androgens can exert their actions via the AR in a DNA binding-dependent manner to regulate target gene transcription, or in a non-DNA binding-dependent manner to initiate rapid, cellular events such as the phosphorylation of 2nd messenger signalling cascades. More recently, ligand-independent actions of the AR have also been identified. Given the large volume of studies relating to androgens and the AR, this review is not intended as an extensive review of all studies investigating the AR, but rather as an overview of the structure, function, signalling pathways and biology of the AR as well as its important role in clinical medicine, with emphasis on recent developments in this field. PMID:27057074

  6. Discoveries of rhythms in human biological functions: a historical review.

    PubMed

    Lemmer, Björn

    2009-08-01

    Though there are very early and ancient observations on the daily variation in physiological and pathophysiological functions (e.g., bronchial asthma), more detailed and scientific reports were not published until the beginning of the 17th century. The aim of this review is to bring those reports to the attention of researchers of chronobiology and chronopharmacology. The ancient books and their contents, which constitute the basis for this review, are part of the personal library collection of the author; numerous observations and reports on biologic rhythms in man are presented here for the first time. The intent of this review is to demonstrate that the fields of chronobiology and chronopharmacology are not only a new and modern branch of science, but that it stands on the shoulders of wonderful and insightful observations and explanations made by our scientific forefathers. It is the hope that the reader will enjoy the richness of the ancient reports that contribute to our present knowledge achieved through astute early biologic rhythm research.

  7. Biologically functionalized nanochannels on ferroelectric lead zirconium titanate surfaces.

    SciTech Connect

    Ocola, L. E.; Pan, W. C.; Kuo, M.; Tirumala, V. R.; Reiss, B. D.; Firestone, M. A.; Illinois Mathematics and Science Academy

    2005-01-01

    We recently started a program at Argonne to exploit patterned, polarizable ferroelectric surfaces, such as lead zirconium titanate (PZT), as a means to create field-responsive inorganic-biomolecule interfaces to study and manipulate biomatter on surfaces. In this paper we will discuss the integration of nanochannels on the surface of PZT films and their selective functionalization to create nanovalves to control nanofluidic flow. Microfluidic devices have been fabricated using a variety of methods, ranging from thermal decomposition of buried patterned channels, to fabricating trenches via plasma etch or hot embossing followed by trench capping. Our work focuses on an alternative method by using a bilayer resist in an inverted configuration normally used for T- and Gamma- gate fabrication. This method is capable of yielding sub-100 nm nanochannels with high aspect ratios and sub-500nm alignment. We have recently demonstrated that the polarization hysteresis loop of PZT is the same before and after exposure to an aqueous environment. This opens the possibility of selective surface modification of PZT via coupling of a wide range of biomolecules (e.g., peptides, proteins) and the use of the electric-field-responsive properties of PZT to manipulate the function (e.g., orientation) of the tethered biomolecules. We have used phage display techniques to evolve specific peptide motifs that selectively bind to PZT. The optimum heptapeptide that facilitates both the attachment of functional biological molecules to the surface of PZT has been identified.

  8. Linking biological soil crust diversity to ecological functions

    NASA Astrophysics Data System (ADS)

    Glaser, Karin; Borchhardt, Nadine; Schulz, Karoline; Mikhailyuk, Tatiana; Baumann, Karen; Leinweber, Peter; Ulf, Karsten

    2016-04-01

    Biological soil crusts (BSCs) are an association of different microorganisms and soil particles in the top millimeters of the soil. They are formed by algae, cyanobacteria, microfungi, bacteria, bryophytes and lichens in various compositions. Our aim was to determine and compare the biodiversity of all occurring organisms in biogeographically different habitats, ranging from polar (both Arctic and Antarctic), subpolar (Scandinavia), temperate (Germany) to dry regions (Chile). The combination of microscopy and molecular techniques (next-generation sequencing) revealed highly diverse crust communities, whose composition clustered by region and correlates with habitat characteristics such as water content. The BSC biodiversity was then linked to the ecological function of the crusts. The functional role of the BSCs in the biogeochemical cycles of carbon, nitrogen and phosphorous is evaluated using an array of state of the art soil chemistry methods including Py-FIMS (pyrolysis field ionization mass spectrometry) and XANES (x-ray absorbance near edge structure). Total P as well as P fractions were quantified in all BSCs, adjacent soil underneath and comparable nearby soil of BSC-free areas revealing a remarkable accumulation of total phosphorous and a distinct pattern of P fractions in the crust. Further, we observed an indication of a different P-speciation composition in the crust compared with BSC-free soil. The data allow answering the question whether BSCs act as sink or source for these compounds, and how biodiversity controls the biogeochemical function of BSCs.

  9. Comparative genomics of pectinacetylesterases: Insight on function and biology

    PubMed Central

    de Souza, Amancio José; Pauly, Markus

    2015-01-01

    Pectin acetylation influences the gelling ability of this important plant polysaccharide for the food industry. Plant apoplastic pectinacetylesterases (PAEs) play a key role in regulating the degree of pectin acetylation and modifying their expression thus represents one way to engineer plant polysaccharides for food applications. Identifying the major active enzymes within the PAE gene family will aid in our understanding of this biological phenomena as well as provide the tools for direct trait manipulation. Using comparative genomics we propose that there is a minimal set of 4 distinct PAEs in plants. Possible functional diversification of the PAE family in the grasses is also explored with the identification of 3 groups of PAE genes specific to grasses. PMID:26237162

  10. Biological activity of lactoferrin-functionalized biomimetic hydroxyapatite nanocrystals

    PubMed Central

    Nocerino, Nunzia; Fulgione, Andrea; Iannaccone, Marco; Tomasetta, Laura; Ianniello, Flora; Martora, Francesca; Lelli, Marco; Roveri, Norberto; Capuano, Federico; Capparelli, Rosanna

    2014-01-01

    The emergence of bacterial strains resistant to antibiotics is a general public health problem. Progress in developing new molecules with antimicrobial properties has been made. In this study, we evaluated the biological activity of a hybrid nanocomposite composed of synthetic biomimetic hydroxyapatite surface-functionalized by lactoferrin (LF-HA). We evaluated the antimicrobial, anti-inflammatory, and antioxidant properties of LF-HA and found that the composite was active against both Gram-positive and Gram-negative bacteria, and that it modulated proinflammatory and anti-inflammatory responses and enhanced antioxidant properties as compared with LF alone. These results indicate the possibility of using LF-HA as an antimicrobial system and biomimetic hydroxyapatite as a candidate for innovative biomedical applications. PMID:24623976

  11. Peptide Self-Assembly for Crafting Functional Biological Materials

    PubMed Central

    Matson, John B.; Zha, R. Helen; Stupp, Samuel I.

    2011-01-01

    Self-assembling, peptide-based scaffolds are frontrunners in the search for biomaterials with widespread impact in regenerative medicine. The inherent biocompatibility and cell signaling capabilities of peptides, in combination with control of secondary structure, has led to the development of a broad range of functional materials with potential for many novel therapies. More recently, membranes formed through complexation of peptide nanostructures with natural biopolymers have led to the development of hierarchically-structured constructs with potentially far-reaching applications in biology and medicine. In this review, we highlight recent advances in peptide-based gels and membranes, including work from our group and others. Specifically, we discuss the application of peptide-based materials in the regeneration of bone and enamel, cartilage, and the central nervous system, as well as the transplantation of islets, wound-healing, cardiovascular therapies, and treatment of erectile dysfunction after prostatectomy PMID:22125413

  12. Derivation and computation of discrete-delay and continuous-delay SDEs in mathematical biology.

    PubMed

    Allen, Edward J

    2014-06-01

    Stochastic versions of several discrete-delay and continuous-delay differential equations, useful in mathematical biology, are derived from basic principles carefully taking into account the demographic, environmental, or physiological randomness in the dynamic processes. In particular, stochastic delay differential equation (SDDE) models are derived and studied for Nicholson's blowflies equation, Hutchinson's equation, an SIS epidemic model with delay, bacteria/phage dynamics, and glucose/insulin levels. Computational methods for approximating the SDDE models are described. Comparisons between computational solutions of the SDDEs and independently formulated Monte Carlo calculations support the accuracy of the derivations and of the computational methods.

  13. Effects of Computer-Assisted Instruction on Performance of Senior High School Biology Students in Ghana

    ERIC Educational Resources Information Center

    Owusu, K. A.; Monney, K. A.; Appiah, J. Y.; Wilmot, E. M.

    2010-01-01

    This study investigated the comparative efficiency of computer-assisted instruction (CAI) and conventional teaching method in biology on senior high school students. A science class was selected in each of two randomly selected schools. The pretest-posttest non equivalent quasi experimental design was used. The students in the experimental group…

  14. Final report for Conference Support Grant "From Computational Biophysics to Systems Biology - CBSB12"

    SciTech Connect

    Hansmann, Ulrich H.E.

    2012-07-02

    This report summarizes the outcome of the international workshop From Computational Biophysics to Systems Biology (CBSB12) which was held June 3-5, 2012, at the University of Tennessee Conference Center in Knoxville, TN, and supported by DOE through the Conference Support Grant 120174. The purpose of CBSB12 was to provide a forum for the interaction between a data-mining interested systems biology community and a simulation and first-principle oriented computational biophysics/biochemistry community. CBSB12 was the sixth in a series of workshops of the same name organized in recent years, and the second that has been held in the USA. As in previous years, it gave researchers from physics, biology, and computer science an opportunity to acquaint each other with current trends in computational biophysics and systems biology, to explore venues of cooperation, and to establish together a detailed understanding of cells at a molecular level. The conference grant of $10,000 was used to cover registration fees and provide travel fellowships to selected students and postdoctoral scientists. By educating graduate students and providing a forum for young scientists to perform research into the working of cells at a molecular level, the workshop adds to DOE's mission of paving the way to exploit the abilities of living systems to capture, store and utilize energy.

  15. Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology (Final Report)

    EPA Science Inventory

    EPA announced the release of the final report, Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology. This report describes new approaches that are faster, less resource intensive, and more robust that can help ...

  16. A Study of the Effectiveness of Computer-Assisted Instruction in the High School Biology Classroom.

    ERIC Educational Resources Information Center

    Ybarrondo, Brent A.

    This study ascertained whether or not computer assisted instruction (CAI) enhanced the quality of the educational experience and resulted in increased learning. The study involved the teaching of a 3-week instructional unit on population genetics and evolutionary processes to advanced placement biology students. The control group (N=38) received…

  17. Effects of Computer Assisted Instruction (CAI) on Secondary School Students' Performance in Biology

    ERIC Educational Resources Information Center

    Yusuf, Mudasiru Olalere; Afolabi, Adedeji Olufemi

    2010-01-01

    This study investigated the effects of computer assisted instruction (CAI) on secondary school students' performance in biology. Also, the influence of gender on the performance of students exposed to CAI in individualised or cooperative learning settings package was examined. The research was a quasi experimental involving a 3 x 2 factorial…

  18. Effects of Constructivist and Computer-Facilitated Strategies on Achievement in Heterogeneous Secondary Biology.

    ERIC Educational Resources Information Center

    Duffy, Maryellen; Barowy, William

    This paper describes the effects of the implementation of constructivist techniques with interactive computer simulations on conceptual understanding of plant nutrition and critical thinking skills in heterogeneously grouped secondary biology classrooms. The study focused on three strategies for teaching plant nutrition: (1) traditional; (2)…

  19. Using a Computer Simulation To Teach Science Process Skills to College Biology and Elementary Education Majors.

    ERIC Educational Resources Information Center

    Lee, Aimee T.; Hairston, Rosalina V.; Thames, Rachel; Lawrence, Tonya; Herron, Sherry S.

    2002-01-01

    Describes the Lateblight computer simulation implemented in the general biology laboratory and science methods course for elementary teachers to reinforce the processes of science and allow students to engage, explore, explain, elaborate, and evaluate the methods of building concepts in science. (Author/KHR)

  20. PARTNERING WITH DOE TO APPLY ADVANCED BIOLOGICAL, ENVIRONMENTAL, AND COMPUTATIONAL SCIENCE TO ENVIRONMENTAL ISSUES

    EPA Science Inventory

    On February 18, 2004, the U.S. Environmental Protection Agency and Department of Energy signed a Memorandum of Understanding to expand the research collaboration of both agencies to advance biological, environmental, and computational sciences for protecting human health and the ...

  1. A direct method for computing extreme value (Gumbel) parameters for gapped biological sequence alignments.

    PubMed

    Quinn, Terrance; Sinkala, Zachariah

    2014-01-01

    We develop a general method for computing extreme value distribution (Gumbel, 1958) parameters for gapped alignments. Our approach uses mixture distribution theory to obtain associated BLOSUM matrices for gapped alignments, which in turn are used for determining significance of gapped alignment scores for pairs of biological sequences. We compare our results with parameters already obtained in the literature.

  2. Computer Labs as Techno-Pedagogical Tools for Learning Biology--Exploring ICT Practices in India

    ERIC Educational Resources Information Center

    Nayark, Ajitha K.; Barker, Miles

    2014-01-01

    In Indian secondary schools, as in many countries, Information and Communication Technologies, ICT, are changing the image of learning places, the roles of teachers and students, and often the entire classroom learning ambience. This study investigates current practices for learning biology in school computer labs in India in the light of the…

  3. Harnessing Polypharmacology with Computer-Aided Drug Design and Systems Biology.

    PubMed

    Wathieu, Henri; Issa, Naiem T; Byers, Stephen W; Dakshanamurthy, Sivanesan

    2016-01-01

    The ascent of polypharmacology in drug development has many implications for disease therapy, most notably in the efforts of drug discovery, drug repositioning, precision medicine and combination therapy. The single- target approach to drug development has encountered difficulties in predicting drugs that are both clinically efficacious and avoid toxicity. By contrast, polypharmacology offers the possibility of a controlled distribution of effects on a biological system. This review addresses possibilities and bottlenecks in the efficient computational application of polypharmacology. The two major areas we address are the discovery and prediction of multiple protein targets using the tools of computer-aided drug design, and the use of these protein targets in predicting therapeutic potential in the context of biological networks. The successful application of polypharmacology to systems biology and pharmacology has the potential to markedly accelerate the pace of development of novel therapies for multiple diseases, and has implications for the intellectual property landscape, likely requiring targeted changes in patent law.

  4. Functionalized nanoparticles for biological imaging and detection applications

    NASA Astrophysics Data System (ADS)

    Mei, Bing C.

    Semiconductor quantum dots (QDs) and gold nanoparticles (AuNPs) have gained tremendous attention in the last decade as a result of their size-dependent spectroscopic properties. These nanoparticles have been a subject of intense study to bridge the gap between macroscopic and atomic behavior, as well as to generate new materials for novel applications in therapeutics, biological sensing, light emitting devices, microelectronics, lasers, and solar cells. One of the most promising areas for the use of these nanoparticles is in biotechnology, where their size-dependent optical properties are harnessed for imaging and sensing applications. However, these nanoparticles, as synthesized, are often not stable in aqueous media and lack simple and reliable means of covalently linking to biomolecules. The focus of this work is to advance the progress of these nanomaterials for biotechnology by synthesizing them, characterizing their optical properties and rendering them water-soluble and functional while maintaining their coveted optical properties. QDs were synthesized by an organometallic chemical procedure that utilizes coordinating solvents to provide brightly luminescent nanoparticles. The optical interactions of these QDs were studied as a function of concentration to identify particle size-dependent optimal concentrations, where scattering and indirection excitation are minimized and the amount light observed per particle is maximized. Both QDs and AuNPs were rendered water-soluble and stable in a broad range of biologically relevant conditions by using a series of ligands composed of dihydrolipoic acid (DHLA) appended to poly(ethylene glycol) methyl ether. By studying the stability of the surface modified AuNPs, we revealed some interesting information regarding the role of the surface ligand on the nanoparticle stability (i.e. solubility in high salt concentration, resistance to dithiothreitol competition and cyanide decomposition). Furthermore, the nanoparticles

  5. Local-basis-function approach to computed tomography

    NASA Astrophysics Data System (ADS)

    Hanson, K. M.; Wecksung, G. W.

    1985-12-01

    In the local basis-function approach, a reconstruction is represented as a linear expansion of basis functions, which are arranged on a rectangular grid and possess a local region of support. The basis functions considered here are positive and may overlap. It is found that basis functions based on cubic B-splines offer significant improvements in the calculational accuracy that can be achieved with iterative tomographic reconstruction algorithms. By employing repetitive basis functions, the computational effort involved in these algorithms can be minimized through the use of tabulated values for the line or strip integrals over a single-basis function. The local nature of the basis functions reduces the difficulties associated with applying local constraints on reconstruction values, such as upper and lower limits. Since a reconstruction is specified everywhere by a set of coefficients, display of a coarsely represented image does not require an arbitrary choice of an interpolation function.

  6. Taking the example of computer systems engineering for the analysis of biological cell systems.

    PubMed

    Pronk, Tessa E; Pimentel, Andy D; Roos, Marco; Breit, Timo M

    2007-01-01

    In this paper, we discuss the potential for the use of engineering methods that were originally developed for the design of embedded computer systems, to analyse biological cell systems. For embedded systems as well as for biological cell systems, design is a feature that defines their identity. The assembly of different components in designs of both systems can vary widely. In contrast to the biology domain, the computer engineering domain has the opportunity to quickly evaluate design options and consequences of its systems by methods for computer aided design and in particular design space exploration. We argue that there are enough concrete similarities between the two systems to assume that the engineering methodology from the computer systems domain, and in particular that related to embedded systems, can be applied to the domain of cellular systems. This will help to understand the myriad of different design options cellular systems have. First we compare computer systems with cellular systems. Then, we discuss exactly what features of engineering methods could aid researchers with the analysis of cellular systems, and what benefits could be gained.

  7. Biologically relevant molecular transducer with increased computing power and iterative abilities.

    PubMed

    Ratner, Tamar; Piran, Ron; Jonoska, Natasha; Keinan, Ehud

    2013-05-23

    As computing devices, which process data and interconvert information, transducers can encode new information and use their output for subsequent computing, offering high computational power that may be equivalent to a universal Turing machine. We report on an experimental DNA-based molecular transducer that computes iteratively and produces biologically relevant outputs. As a proof of concept, the transducer accomplished division of numbers by 3. The iterative power was demonstrated by a recursive application on an obtained output. This device reads plasmids as input and processes the information according to a predetermined algorithm, which is represented by molecular software. The device writes new information on the plasmid using hardware that comprises DNA-manipulating enzymes. The computation produces dual output: a quotient, represented by newly encoded DNA, and a remainder, represented by E. coli phenotypes. This device algorithmically manipulates genetic codes.

  8. An Integrated Bioinformatics and Computational Biology Approach Identifies New BH3-Only Protein Candidates.

    PubMed

    Hawley, Robert G; Chen, Yuzhong; Riz, Irene; Zeng, Chen

    2012-05-04

    In this study, we utilized an integrated bioinformatics and computational biology approach in search of new BH3-only proteins belonging to the BCL2 family of apoptotic regulators. The BH3 (BCL2 homology 3) domain mediates specific binding interactions among various BCL2 family members. It is composed of an amphipathic α-helical region of approximately 13 residues that has only a few amino acids that are highly conserved across all members. Using a generalized motif, we performed a genome-wide search for novel BH3-containing proteins in the NCBI Consensus Coding Sequence (CCDS) database. In addition to known pro-apoptotic BH3-only proteins, 197 proteins were recovered that satisfied the search criteria. These were categorized according to α-helical content and predictive binding to BCL-xL (encoded by BCL2L1) and MCL-1, two representative anti-apoptotic BCL2 family members, using position-specific scoring matrix models. Notably, the list is enriched for proteins associated with autophagy as well as a broad spectrum of cellular stress responses such as endoplasmic reticulum stress, oxidative stress, antiviral defense, and the DNA damage response. Several potential novel BH3-containing proteins are highlighted. In particular, the analysis strongly suggests that the apoptosis inhibitor and DNA damage response regulator, AVEN, which was originally isolated as a BCL-xL-interacting protein, is a functional BH3-only protein representing a distinct subclass of BCL2 family members.

  9. Computer method for identification of boiler transfer functions

    NASA Technical Reports Server (NTRS)

    Miles, J. H.

    1971-01-01

    An iterative computer method is described for identifying boiler transfer functions using frequency response data. An objective penalized performance measure and a nonlinear minimization technique are used to cause the locus of points generated by a transfer function to resemble the locus of points obtained from frequency response measurements. Different transfer functions can be tried until a satisfactory empirical transfer function to the system is found. To illustrate the method, some examples and some results from a study of a set of data consisting of measurements of the inlet impedance of a single tube forced flow boiler with inserts are given.

  10. Biosynthesis and biological functions of terpenoids in plants.

    PubMed

    Tholl, Dorothea

    2015-01-01

    Terpenoids (isoprenoids) represent the largest and most diverse class of chemicals among the myriad compounds produced by plants. Plants employ terpenoid metabolites for a variety of basic functions in growth and development but use the majority of terpenoids for more specialized chemical interactions and protection in the abiotic and biotic environment. Traditionally, plant-based terpenoids have been used by humans in the food, pharmaceutical, and chemical industries, and more recently have been exploited in the development of biofuel products. Genomic resources and emerging tools in synthetic biology facilitate the metabolic engineering of high-value terpenoid products in plants and microbes. Moreover, the ecological importance of terpenoids has gained increased attention to develop strategies for sustainable pest control and abiotic stress protection. Together, these efforts require a continuous growth in knowledge of the complex metabolic and molecular regulatory networks in terpenoid biosynthesis. This chapter gives an overview and highlights recent advances in our understanding of the organization, regulation, and diversification of core and specialized terpenoid metabolic pathways, and addresses the most important functions of volatile and nonvolatile terpenoid specialized metabolites in plants.

  11. Quantum computing without wavefunctions: time-dependent density functional theory for universal quantum computation.

    PubMed

    Tempel, David G; Aspuru-Guzik, Alán

    2012-01-01

    We prove that the theorems of TDDFT can be extended to a class of qubit Hamiltonians that are universal for quantum computation. The theorems of TDDFT applied to universal Hamiltonians imply that single-qubit expectation values can be used as the basic variables in quantum computation and information theory, rather than wavefunctions. From a practical standpoint this opens the possibility of approximating observables of interest in quantum computations directly in terms of single-qubit quantities (i.e. as density functionals). Additionally, we also demonstrate that TDDFT provides an exact prescription for simulating universal Hamiltonians with other universal Hamiltonians that have different, and possibly easier-to-realize two-qubit interactions. This establishes the foundations of TDDFT for quantum computation and opens the possibility of developing density functionals for use in quantum algorithms.

  12. A large-scale evaluation of computational protein function prediction.

    PubMed

    Radivojac, Predrag; Clark, Wyatt T; Oron, Tal Ronnen; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kaßner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Boehm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas A; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-03-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

  13. Efficient and accurate computation of the incomplete Airy functions

    NASA Technical Reports Server (NTRS)

    Constantinides, E. D.; Marhefka, R. J.

    1993-01-01

    The incomplete Airy integrals serve as canonical functions for the uniform ray optical solutions to several high-frequency scattering and diffraction problems that involve a class of integrals characterized by two stationary points that are arbitrarily close to one another or to an integration endpoint. Integrals with such analytical properties describe transition region phenomena associated with composite shadow boundaries. An efficient and accurate method for computing the incomplete Airy functions would make the solutions to such problems useful for engineering purposes. In this paper a convergent series solution for the incomplete Airy functions is derived. Asymptotic expansions involving several terms are also developed and serve as large argument approximations. The combination of the series solution with the asymptotic formulae provides for an efficient and accurate computation of the incomplete Airy functions. Validation of accuracy is accomplished using direct numerical integration data.

  14. A large-scale evaluation of computational protein function prediction

    PubMed Central

    Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-01-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

  15. Shaping Small Bioactive Molecules to Untangle Their Biological Function: A Focus on Fluorescent Plant Hormones.

    PubMed

    Lace, Beatrice; Prandi, Cristina

    2016-08-01

    Modern biology overlaps with chemistry in explaining the structure and function of all cellular processes at the molecular level. Plant hormone research is perfectly located at the interface between these two disciplines, taking advantage of synthetic and computational chemistry as a tool to decipher the complex biological mechanisms regulating the action of plant hormones. These small signaling molecules regulate a wide range of developmental processes, adapting plant growth to ever changing environmental conditions. The synthesis of small bioactive molecules mimicking the activity of endogenous hormones allows us to unveil many molecular features of their functioning, giving rise to a new field, plant chemical biology. In this framework, fluorescence labeling of plant hormones is emerging as a successful strategy to track the fate of these challenging molecules inside living organisms. Thanks to the increasing availability of new fluorescent probes as well as advanced and innovative imaging technologies, we are now in a position to investigate many of the dynamic mechanisms through which plant hormones exert their action. Such a deep and detailed comprehension is mandatory for the development of new green technologies for practical applications. In this review, we summarize the results obtained so far concerning the fluorescent labeling of plant hormones, highlighting the basic steps leading to the design and synthesis of these compelling molecular tools and their applications.

  16. Efficient algorithm for computing exact partition functions of lattice polymer models

    NASA Astrophysics Data System (ADS)

    Hsieh, Yu-Hsin; Chen, Chi-Ning; Hu, Chin-Kun

    2016-12-01

    Polymers are important macromolecules in many physical, chemical, biological and industrial problems. Studies on simple lattice polymer models are very helpful for understanding behaviors of polymers. We develop an efficient algorithm for computing exact partition functions of lattice polymer models, and we use this algorithm and personal computers to obtain exact partition functions of the interacting self-avoiding walks with N monomers on the simple cubic lattice up to N = 28 and on the square lattice up to N = 40. Our algorithm can be extended to study other lattice polymer models, such as the HP model for protein folding and the charged HP model for protein aggregation. It also provides references for checking accuracy of numerical partition functions obtained by simulations.

  17. Robust Computation of Morse-Smale Complexes of Bilinear Functions

    SciTech Connect

    Norgard, G; Bremer, P T

    2010-11-30

    The Morse-Smale (MS) complex has proven to be a useful tool in extracting and visualizing features from scalar-valued data. However, existing algorithms to compute the MS complex are restricted to either piecewise linear or discrete scalar fields. This paper presents a new combinatorial algorithm to compute MS complexes for two dimensional piecewise bilinear functions defined on quadrilateral meshes. We derive a new invariant of the gradient flow within a bilinear cell and use it to develop a provably correct computation which is unaffected by numerical instabilities. This includes a combinatorial algorithm to detect and classify critical points as well as a way to determine the asymptotes of cell-based saddles and their intersection with cell edges. Finally, we introduce a simple data structure to compute and store integral lines on quadrilateral meshes which by construction prevents intersections and enables us to enforce constraints on the gradient flow to preserve known invariants.

  18. Functional Characteristics of Intelligent Computer-Assisted Instruction: Intelligent Features.

    ERIC Educational Resources Information Center

    Park, Ok-choon

    1988-01-01

    Examines the functional characteristics of intelligent computer assisted instruction (ICAI) and discusses the requirements of a multidisciplinary cooperative effort of its development. A typical ICAI model is presented and intelligent features of ICAI systems are described, including modeling the student's learning process, qualitative decision…

  19. SNAP: A computer program for generating symbolic network functions

    NASA Technical Reports Server (NTRS)

    Lin, P. M.; Alderson, G. E.

    1970-01-01

    The computer program SNAP (symbolic network analysis program) generates symbolic network functions for networks containing R, L, and C type elements and all four types of controlled sources. The program is efficient with respect to program storage and execution time. A discussion of the basic algorithms is presented, together with user's and programmer's guides.

  20. Supporting Executive Functions during Children's Preliteracy Learning with the Computer

    ERIC Educational Resources Information Center

    Van de Sande, E.; Segers, E.; Verhoeven, L.

    2016-01-01

    The present study examined how embedded activities to support executive functions helped children to benefit from a computer intervention that targeted preliteracy skills. Three intervention groups were compared on their preliteracy gains in a randomized controlled trial design: an experimental group that worked with software to stimulate early…

  1. Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data

    PubMed Central

    2013-01-01

    currently integrated as an analysis module as well as additional tools to support biological interpretation. Confero is a standalone system that also integrates with Galaxy, an open-source workflow management and data integration system. To illustrate Confero platform functionality we walk through major aspects of the Confero workflow and results using the Bioconductor estrogen package dataset. Conclusion Confero provides a unique and flexible platform to support downstream computational analysis facilitating biological interpretation. The system has been designed in order to provide the researcher with a simple, innovative, and extensible solution to store and exploit analyzed data in a sustainable and reproducible manner thereby accelerating knowledge-driven research. Confero source code is freely available from http://sourceforge.net/projects/confero/. PMID:23895370

  2. Quantum One Go Computation and the Physical Computation Level of Biological Information Processing

    NASA Astrophysics Data System (ADS)

    Castagnoli, Giuseppe

    2010-02-01

    By extending the representation of quantum algorithms to problem-solution interdependence, the unitary evolution part of the algorithm entangles the register containing the problem with the register containing the solution. Entanglement becomes correlation, or mutual causality, between the two measurement outcomes: the string of bits encoding the problem and that encoding the solution. In former work, we showed that this is equivalent to the algorithm knowing in advance 50% of the bits of the solution it will find in the future, which explains the quantum speed up. Mutual causality between bits of information is also equivalent to seeing quantum measurement as a many body interaction between the parts of a perfect classical machine whose normalized coordinates represent the qubit populations. This “hidden machine” represents the problem to be solved. The many body interaction (measurement) satisfies all the constraints of a nonlinear Boolean network “together and at the same time”—in one go—thus producing the solution. Quantum one go computation can formalize the physical computation level of the theories that place consciousness in quantum measurement. In fact, in visual perception, we see, thus recognize, thus process, a significant amount of information “together and at the same time”. Identifying the fundamental mechanism of consciousness with that of the quantum speed up gives quantum consciousness, with respect to classical consciousness, a potentially enormous evolutionary advantage.

  3. Computing the origin and evolution of the ribosome from its structure — Uncovering processes of macromolecular accretion benefiting synthetic biology

    PubMed Central

    Caetano-Anollés, Gustavo; Caetano-Anollés, Derek

    2015-01-01

    Accretion occurs pervasively in nature at widely different timeframes. The process also manifests in the evolution of macromolecules. Here we review recent computational and structural biology studies of evolutionary accretion that make use of the ideographic (historical, retrodictive) and nomothetic (universal, predictive) scientific frameworks. Computational studies uncover explicit timelines of accretion of structural parts in molecular repertoires and molecules. Phylogenetic trees of protein structural domains and proteomes and their molecular functions were built from a genomic census of millions of encoded proteins and associated terminal Gene Ontology terms. Trees reveal a ‘metabolic-first’ origin of proteins, the late development of translation, and a patchwork distribution of proteins in biological networks mediated by molecular recruitment. Similarly, the natural history of ancient RNA molecules inferred from trees of molecular substructures built from a census of molecular features shows patchwork-like accretion patterns. Ideographic analyses of ribosomal history uncover the early appearance of structures supporting mRNA decoding and tRNA translocation, the coevolution of ribosomal proteins and RNA, and a first evolutionary transition that brings ribosomal subunits together into a processive protein biosynthetic complex. Nomothetic structural biology studies of tertiary interactions and ancient insertions in rRNA complement these findings, once concentric layering assumptions are removed. Patterns of coaxial helical stacking reveal a frustrated dynamics of outward and inward ribosomal growth possibly mediated by structural grafting. The early rise of the ribosomal ‘turnstile’ suggests an evolutionary transition in natural biological computation. Results make explicit the need to understand processes of molecular growth and information transfer of macromolecules. PMID:27096056

  4. Polymer biomaterial constructs for regenerative medicine and functional biological systems

    NASA Astrophysics Data System (ADS)

    Meng, Linghui

    The use of collagen as a biomaterial is currently undergoing a renaissance in the tissue engineering field. The excellent biocompatibility and safety due to its biological characteristics, such as biodegradability and weak antigenicity, make collagen a primary material resource in medical applications. Described herein is work towards the development of novel collagen-based matrices, with additional multi-functionality imparted through a novel in-situ crosslinking approach. The process of electrospinning has become a widely used technique for the creation of fibrous scaffolds for tissue engineering applications due to its ability to rapidly create structures composed of nano-scale polymer fibers closely resembling the architecture of the extracellular matrix (ECM). Collagen-PCL sheath-core bicomponent fibrous scaffolds were fabricated using a novel variation on traditional electrospinning, known as co-axial electrospinning. The results showed that the addition of a synthetic polymer core into collagen nanofibers remarkably increased the mechanical strength of collagen matrices spun from the benign solvent system. A novel single-step, in-situ collagen crosslink approach was developed in order to solve the problems dominating traditional collagen crosslinking methods, such as dimensional shrinking and loss of porous morphology, and to simplify the crosslinking procedure for electrospun collagen scaffolds. The excess amount of NHS present in the crosslinking mixture was found to delay the EDC/collagen coupling reaction in a controlled fashion. Fundamental investigations into the development and characterization of in-situ crosslinked collagen matrices such as fibrous scaffolds, gels and sponges, as well as their biomedical applications including cell culture substrates, wound dressings, drug delivery matrices and bone regeneration substitutes, were performed. The preliminary mice studies indicated that the in-situ crosslinked collagen matrices could be good candidates

  5. GENIUS: web server to predict local gene networks and key genes for biological functions.

    PubMed

    Puelma, Tomas; Araus, Viviana; Canales, Javier; Vidal, Elena A; Cabello, Juan M; Soto, Alvaro; Gutiérrez, Rodrigo A

    2016-12-19

    GENIUS is a user-friendly web server that uses a novel machine learning algorithm to infer functional gene networks focused on specific genes and experimental conditions that are relevant to biological functions of interest. These functions may have different levels of complexity, from specific biological processes to complex traits that involve several interacting processes. GENIUS also enriches the network with new genes related to the biological function of interest, with accuracies comparable to highly discriminative Support Vector Machine methods.

  6. Insect MicroRNAs: Biogenesis, Expression Profiling and Biological Functions

    PubMed Central

    Lucas, Keira; Raikhel, Alexander S.

    2012-01-01

    MicroRNAs (miRNA) are a class of endogenous regulatory RNA molecules 21-24 nucleotides in length that modulate gene expression at the post-transcriptional level via base pairing to target sites within messenger RNAs (mRNA). Typically, the miRNA “seed sequence” (nucleotides 2-8 at the 5′ end) binds complementary seed match sites within the 3′ untranslated region of mRNAs, resulting in either translational inhibition or mRNA degradation. MicroRNAs were first discovered in Caenorhabditis elegans and were shown to be involved in the timed regulation of developmental events. Since their discovery in the 1990s, thousands of potential miRNAs have since been identified in various organisms through small RNA cloning methods and/or computational prediction, and have been shown to play functionally important roles of gene regulation in invertebrates, vertebrates, plants, fungi and viruses. Numerous functions of miRNAs identified in Drosophila melanogaster have demonstrated a great significance of these regulatory molecules. However, elucidation of miRNA roles in non-drosophilid insects presents a challenging and important task. PMID:23165178

  7. Computer program for calculating and fitting thermodynamic functions

    NASA Technical Reports Server (NTRS)

    Mcbride, Bonnie J.; Gordon, Sanford

    1992-01-01

    A computer program is described which (1) calculates thermodynamic functions (heat capacity, enthalpy, entropy, and free energy) for several optional forms of the partition function, (2) fits these functions to empirical equations by means of a least-squares fit, and (3) calculates, as a function of temperture, heats of formation and equilibrium constants. The program provides several methods for calculating ideal gas properties. For monatomic gases, three methods are given which differ in the technique used for truncating the partition function. For diatomic and polyatomic molecules, five methods are given which differ in the corrections to the rigid-rotator harmonic-oscillator approximation. A method for estimating thermodynamic functions for some species is also given.

  8. Networks of spiking neurons that compute linear functions using action potential timing

    NASA Astrophysics Data System (ADS)

    Ruf, Berthold

    1999-03-01

    For fast neural computations within the brain it is very likely that the timing of single firing events is relevant. Recently Maass has shown that under certain weak assumptions a weighted sum can be computed in temporal coding by leaky integrate-and-fire neurons. This construction can be extended to approximate arbitrary functions. In comparison to integrate-and-fire neurons there are several sources in biologically more realistic neurons for additional nonlinear effects like e.g. the spatial and temporal interaction of postsynaptic potentials or voltage-gated ion channels at the soma. Here we demonstrate with the help of computer simulations using GENESIS that despite of these nonlinearities such neurons can compute linear functions in a natural and straightforward way based on the main principles of the construction given by Maass. One only has to assume that a neuron receives all its inputs in a time interval of approximately the length of the rising segment of its excitatory postsynaptic potentials. We also show that under certain assumptions there exists within this construction some type of activation function being computed by such neurons. Finally we demonstrate that on the basis of these results it is possible to realize in a simple way pattern analysis with spiking neurons. It allows the analysis of a mixture of several learned patterns within a few milliseconds.

  9. A survey of computational intelligence techniques in protein function prediction.

    PubMed

    Tiwari, Arvind Kumar; Srivastava, Rajeev

    2014-01-01

    During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction.

  10. Environment parameters and basic functions for floating-point computation

    NASA Technical Reports Server (NTRS)

    Brown, W. S.; Feldman, S. I.

    1978-01-01

    A language-independent proposal for environment parameters and basic functions for floating-point computation is presented. Basic functions are proposed to analyze, synthesize, and scale floating-point numbers. The model provides a small set of parameters and a small set of axioms along with sharp measures of roundoff error. The parameters and functions can be used to write portable and robust codes that deal intimately with the floating-point representation. Subject to underflow and overflow constraints, a number can be scaled by a power of the floating-point radix inexpensively and without loss of precision. A specific representation for FORTRAN is included.

  11. Computing the hadronic vacuum polarization function by analytic continuation

    DOE PAGES

    Feng, Xu; Hashimoto, Shoji; Hotzel, Grit; ...

    2013-08-29

    We propose a method to compute the hadronic vacuum polarization function on the lattice at continuous values of photon momenta bridging between the spacelike and timelike regions. We provide two independent demonstrations to show that this method leads to the desired hadronic vacuum polarization function in Minkowski spacetime. We present with the example of the leading-order QCD correction to the muon anomalous magnetic moment that this approach can provide a valuable alternative method for calculations of physical quantities where the hadronic vacuum polarization function enters.

  12. Biological function of a polysaccharide degrading enzyme in the periplasm.

    PubMed

    Wang, Yajie; Moradali, M Fata; Goudarztalejerdi, Ali; Sims, Ian M; Rehm, Bernd H A

    2016-11-08

    Carbohydrate polymers are industrially and medically important. For instance, a polysaccharide, alginate (from seaweed), is widely used in food, textile and pharmaceutical industries. Certain bacteria also produce alginate through membrane spanning multi-protein complexes. Using Pseudomonas aeruginosa as a model organism, we investigated the biological function of an alginate degrading enzyme, AlgL, in alginate production and biofilm formation. We showed that AlgL negatively impacts alginate production through its enzymatic activity. We also demonstrated that deletion of AlgL does not interfere with polymer length control, epimerization degree or stability of the biosynthesis complex, arguing that AlgL is a free periplasmic protein dispensable for alginate production. This was further supported by our protein-stability and interaction experiments. Interestingly, over-production of AlgL interfered with polymer length control, suggesting that AlgL could be loosely associated with the biosynthesis complex. In addition, chromosomal expression of algL enhanced alginate O-acetylation; both attachment and dispersal stages of the bacterial biofilm lifecycle were sensitive to the level of O-acetylation. Since this modification also protects the pathogen against host defences and enhances other virulence factors, chromosomal expression of algL could be important for the pathogenicity of this organism. Overall, this work improves our understanding of bacterial alginate production and provides new knowledge for alginate production and disease control.

  13. Biological function of a polysaccharide degrading enzyme in the periplasm

    PubMed Central

    Wang, Yajie; Moradali, M. Fata; Goudarztalejerdi, Ali; Sims, Ian M.; Rehm, Bernd H. A.

    2016-01-01

    Carbohydrate polymers are industrially and medically important. For instance, a polysaccharide, alginate (from seaweed), is widely used in food, textile and pharmaceutical industries. Certain bacteria also produce alginate through membrane spanning multi-protein complexes. Using Pseudomonas aeruginosa as a model organism, we investigated the biological function of an alginate degrading enzyme, AlgL, in alginate production and biofilm formation. We showed that AlgL negatively impacts alginate production through its enzymatic activity. We also demonstrated that deletion of AlgL does not interfere with polymer length control, epimerization degree or stability of the biosynthesis complex, arguing that AlgL is a free periplasmic protein dispensable for alginate production. This was further supported by our protein-stability and interaction experiments. Interestingly, over-production of AlgL interfered with polymer length control, suggesting that AlgL could be loosely associated with the biosynthesis complex. In addition, chromosomal expression of algL enhanced alginate O-acetylation; both attachment and dispersal stages of the bacterial biofilm lifecycle were sensitive to the level of O-acetylation. Since this modification also protects the pathogen against host defences and enhances other virulence factors, chromosomal expression of algL could be important for the pathogenicity of this organism. Overall, this work improves our understanding of bacterial alginate production and provides new knowledge for alginate production and disease control. PMID:27824067

  14. Function and Regulation of Lipid Biology in Caenorhabditis elegans Aging

    PubMed Central

    Hou, Nicole Shangming; Taubert, Stefan

    2012-01-01

    Rapidly expanding aging populations and a concomitant increase in the prevalence of age-related diseases are global health problems today. Over the past three decades, a large body of work has led to the identification of genes and regulatory networks that affect longevity and health span, often benefiting from the tremendous power of genetics in vertebrate and invertebrate model organisms. Interestingly, many of these factors appear linked to lipids, important molecules that participate in cellular signaling, energy metabolism, and structural compartmentalization. Despite the putative link between lipids and longevity, the role of lipids in aging remains poorly understood. Emerging data from the model organism Caenorhabditis elegans suggest that lipid composition may change during aging, as several pathways that influence aging also regulate lipid metabolism enzymes; moreover, some of these enzymes apparently play key roles in the pathways that affect the rate of aging. By understanding how lipid biology is regulated during C. elegans aging, and how it impacts molecular, cellular, and organismal function, we may gain insight into novel ways to delay aging using genetic or pharmacological interventions. In the present review we discuss recent insights into the roles of lipids in C. elegans aging, including regulatory roles played by lipids themselves, the regulation of lipid metabolic enzymes, and the roles of lipid metabolism genes in the pathways that affect aging. PMID:22629250

  15. Understanding Nuclear Receptor Form and Function Using Structural Biology

    PubMed Central

    Rastinejad, Fraydoon; Huang, Pengxiang; Chandra, Vikas; Khorasanizadeh, Sepideh

    2013-01-01

    Nuclear receptors (NR) are a major transcription factor family whose members selectively bind small molecule lipophilic ligands and transduce those signals into specific changes in gene programs. For over two decades, structural biology efforts were directed exclusively on the individual ligand binding domains (LBDs) or DNA binding domains (DBDs) of NRs. These analyses revealed the basis for both ligand and DNA binding, and also revealed receptor conformations representing both the activated and repressed states. Additionally, crystallographic studies explained how NR LBD surfaces recognize discrete portions of transcriptional coregulators. The many structural snapshots of LBDs have also guided the development of synthetic ligands with therapeutic potential. Yet, the exclusive structural focus on isolated NR domains has made it difficult to conceptualize how all the NR polypeptide segments are coordinated physically and functionally in the context of receptor quaternary architectures. Newly emerged crystal structures of the PPARγ-RXRα heterodimer and HNF-4α homodimer have recently revealed the higher order organizations of these receptor complexes on DNA, as well as the complexity and uniqueness of their domain-domain interfaces. These emerging structural advances promise to better explain how signals in one domain can be allosterically transmitted to distal receptor domains, also providing much better frameworks for guiding future drug discovery efforts. PMID:24103914

  16. Functional Synchronization of Biological Rhythms in a Tritrophic System

    PubMed Central

    Zhang, Sufang; Wei, Jianing; Guo, Xiaojiao; Liu, Tong-Xian; Kang, Le

    2010-01-01

    In a tritrophic system formed by a plant, an herbivore and a natural enemy, each component has its own biological rhythm. However, the rhythm correlations among the three levels and the underlying mechanisms in any tritrophic system are largely unknown. Here, we report that the rhythms exhibited bidirectional correlations in a model tritrophic system involving a lima bean, a pea leafminer and a parasitoid. From the bottom-up perspective, the rhythm was initiated from herbivore feeding, which triggered the rhythms of volatile emissions; then the rhythmic pattern of parasitoid activities was affected, and these rhythms were synchronized by a light switch signal. Increased volatile concentration can enhance the intensity of parasitoid locomotion and oviposition only under light. From the top-down perspective, naive and oviposition-experienced parasitoids were able to utilize the different volatile rhythm information from the damaged plant to locate host leafminers respectively. Our results indicated that the three interacting organisms in this system can achieve rhythmic functional synchronization under a natural light-dark photoperiod, but not under constant light or darkness. These findings provide new insight into the rhythm synchronization of three key players that contribute to the utilization of light and chemical signals, and our results may be used as potential approaches for manipulating natural enemies. PMID:20552008

  17. Computation of three-dimensional flows using two stream functions

    NASA Technical Reports Server (NTRS)

    Greywall, Mahesh S.

    1991-01-01

    An approach to compute 3-D flows using two stream functions is presented. The method generates a boundary fitted grid as part of its solution. Commonly used two steps for computing the flow fields are combined into a single step in the present approach: (1) boundary fitted grid generation; and (2) solution of Navier-Stokes equations on the generated grid. The presented method can be used to directly compute 3-D viscous flows, or the potential flow approximation of this method can be used to generate grids for other algorithms to compute 3-D viscous flows. The independent variables used are chi, a spatial coordinate, and xi and eta, values of stream functions along two sets of suitably chosen intersecting stream surfaces. The dependent variables used are the streamwise velocity, and two functions that describe the stream surfaces. Since for a 3-D flow there is no unique way to define two sets of intersecting stream surfaces to cover the given flow, different types of two sets of intersecting stream surfaces are considered. First, the metric of the (chi, xi, eta) curvilinear coordinate system associated with each type is presented. Next, equations for the steady state transport of mass, momentum, and energy are presented in terms of the metric of the (chi, xi, eta) coordinate system. Also included are the inviscid and the parabolized approximations to the general transport equations.

  18. Lung function, biological monitoring, and biological effect monitoring of gemstone cutters exposed to beryls

    PubMed Central

    Wegner, R.; Heinrich-Ramm, R.; Nowak, D.; Olma, K.; Poschadel, B.; Szadkowski, D.

    2000-01-01

    OBJECTIVES—Gemstone cutters are potentially exposed to various carcinogenic and fibrogenic metals such as chromium, nickel, aluminium, and beryllium, as well as to lead. Increased beryllium concentrations had been reported in the air of workplaces of beryl cutters in Idar-Oberstein, Germany. The aim of the survey was to study the excretion of beryllium in cutters and grinders with occupational exposure to beryls—for example, aquamarines and emeralds—to examine the prevalence of beryllium sensitisation with the beryllium lymphocyte transformation test (BeLT), to examine the prevalence of lung disease induced by beryllium, to describe the internal load of the respective metals relative to work process, and to screen for genotoxic effects in this particular profession.
METHODS—In a cross sectional investigation, 57 out of 100 gemstone cutters working in 12 factories in Idar-Oberstein with occupational exposure to beryls underwent medical examinations, a chest radiograph, lung function testing (spirometry, airway resistance with the interrupter technique), and biological monitoring, including measurements of aluminium, chromium, and nickel in urine as well as lead in blood. Beryllium in urine was measured with a newly developed direct electrothermal atomic absorption spectroscopy technique with a measurement limit of 0.06 µg/l. Also, cytogenetic tests (rates of micronuclei and sister chromatid exchange), and a BeLT were performed. Airborne concentrations of beryllium were measured in three factories. As no adequate local control group was available, the cutters were categorised into those with an exposure to beryls of >4 hours/week (group A) and ⩽4 hours/week (group B).
RESULTS—Clinical, radiological, or spirometric abnormalities indicating pneumoconiosis were detected in none of the gemstone cutters. Metal concentrations in biological material were far below the respective biological limit values, and beryllium in urine was only measurable in

  19. 3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

    NASA Technical Reports Server (NTRS)

    Ross, Muriel D.; Meyer, Glenn; Lam, Tony; Cutler, Lynn; Vaziri, Parshaw

    1990-01-01

    Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

  20. A Gaussian mixture model based cost function for parameter estimation of chaotic biological systems

    NASA Astrophysics Data System (ADS)

    Shekofteh, Yasser; Jafari, Sajad; Sprott, Julien Clinton; Hashemi Golpayegani, S. Mohammad Reza; Almasganj, Farshad

    2015-02-01

    As we know, many biological systems such as neurons or the heart can exhibit chaotic behavior. Conventional methods for parameter estimation in models of these systems have some limitations caused by sensitivity to initial conditions. In this paper, a novel cost function is proposed to overcome those limitations by building a statistical model on the distribution of the real system attractor in state space. This cost function is defined by the use of a likelihood score in a Gaussian mixture model (GMM) which is fitted to the observed attractor generated by the real system. Using that learned GMM, a similarity score can be defined by the computed likelihood score of the model time series. We have applied the proposed method to the parameter estimation of two important biological systems, a neuron and a cardiac pacemaker, which show chaotic behavior. Some simulated experiments are given to verify the usefulness of the proposed approach in clean and noisy conditions. The results show the adequacy of the proposed cost function.

  1. Computational approaches and metrics required for formulating biologically realistic nanomaterial pharmacokinetic models

    NASA Astrophysics Data System (ADS)

    Riviere, Jim E.; Scoglio, Caterina; Sahneh, Faryad D.; Monteiro-Riviere, Nancy A.

    2013-01-01

    The field of nanomaterial pharmacokinetics is in its infancy, with major advances largely restricted by a lack of biologically relevant metrics, fundamental differences between particles and small molecules of organic chemicals and drugs relative to biological processes involved in disposition, a scarcity of sufficiently rich and characterized in vivo data and a lack of computational approaches to integrating nanomaterial properties to biological endpoints. A central concept that links nanomaterial properties to biological disposition, in addition to their colloidal properties, is the tendency to form a biocorona which modulates biological interactions including cellular uptake and biodistribution. Pharmacokinetic models must take this crucial process into consideration to accurately predict in vivo disposition, especially when extrapolating from laboratory animals to humans since allometric principles may not be applicable. The dynamics of corona formation, which modulates biological interactions including cellular uptake and biodistribution, is thereby a crucial process involved in the rate and extent of biodisposition. The challenge will be to develop a quantitative metric that characterizes a nanoparticle's surface adsorption forces that are important for predicting biocorona dynamics. These types of integrative quantitative approaches discussed in this paper for the dynamics of corona formation must be developed before realistic engineered nanomaterial risk assessment can be accomplished.

  2. Accelerating Computation of Large Biological Datasets using MapReduce Framework.

    PubMed

    Wang, Chao; Dai, Dong; Li, Xi; Wang, Aili; Zhou, Xuehai

    2016-04-05

    The maximal information coefficient (MIC) has been proposed to discover relationships and associations between pairs of variables. It poses significant challenges for bioinformatics scientists to accelerate the MIC calculation, especially in genome sequencing and biological annotations. In this paper we explore a parallel approach which uses MapReduce framework to improve the computing efficiency and throughput of the MIC computation. The acceleration system includes biological data storage on HDFS, preprocessing algorithms, distributed memory cache mechanism, and the partition of MapReduce jobs. Based on the acceleration approach, we extend the traditional two-variable algorithm to multiple variables algorithm. The experimental results show that our parallel solution provides a linear speedup comparing with original algorithm without affecting the correctness and sensitivity.

  3. Meeting report from the first meetings of the Computational Modeling in Biology Network (COMBINE)

    PubMed Central

    Le Novère, Nicolas; Hucka, Michael; Anwar, Nadia; Bader, Gary D; Demir, Emek; Moodie, Stuart; Sorokin, Anatoly

    2011-01-01

    The Computational Modeling in Biology Network (COMBINE), is an initiative to coordinate the development of the various community standards and formats in computational systems biology and related fields. This report summarizes the activities pursued at the first annual COMBINE meeting held in Edinburgh on October 6-9 2010 and the first HARMONY hackathon, held in New York on April 18-22 2011. The first of those meetings hosted 81 attendees. Discussions covered both official COMBINE standards-(BioPAX, SBGN and SBML), as well as emerging efforts and interoperability between different formats. The second meeting, oriented towards software developers, welcomed 59 participants and witnessed many technical discussions, development of improved standards support in community software systems and conversion between the standards. Both meetings were resounding successes and showed that the field is now mature enough to develop representation formats and related standards in a coordinated manner. PMID:22180826

  4. Interdisciplinary research and education at the biology-engineering-computer science interface: a perspective.

    PubMed

    Tadmor, Brigitta; Tidor, Bruce

    2005-09-01

    Progress in the life sciences, including genome sequencing and high-throughput experimentation, offers an opportunity for understanding biology and medicine from a systems perspective. This 'new view', which complements the more traditional component-based approach, involves the integration of biological research with approaches from engineering disciplines and computer science. The result is more than a new set of technologies. Rather, it promises a fundamental reconceptualization of the life sciences based on the development of quantitative and predictive models to describe crucial processes. To achieve this change, learning communities are being formed at the interface of the life sciences, engineering and computer science. Through these communities, research and education will be integrated across disciplines and the challenges associated with multidisciplinary team-based science will be addressed.

  5. Large Scale Computing and Storage Requirements for Biological and Environmental Research

    SciTech Connect

    DOE Office of Science, Biological and Environmental Research Program Office ,

    2009-09-30

    In May 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of Biological and Environmental Research (BER) held a workshop to characterize HPC requirements for BER-funded research over the subsequent three to five years. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. Chief among them: scientific progress in BER-funded research is limited by current allocations of computational resources. Additionally, growth in mission-critical computing -- combined with new requirements for collaborative data manipulation and analysis -- will demand ever increasing computing, storage, network, visualization, reliability and service richness from NERSC. This report expands upon these key points and adds others. It also presents a number of"case studies" as significant representative samples of the needs of science teams within BER. Workshop participants were asked to codify their requirements in this"case study" format, summarizing their science goals, methods of solution, current and 3-5 year computing requirements, and special software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel,"multi-core" environment that is expected to dominate HPC architectures over the next few years.

  6. Computer Literacy for Life Sciences: Helping the Digital-Era Biology Undergraduates Face Today's Research

    PubMed Central

    2010-01-01

    Computer literacy plays a critical role in today's life sciences research. Without the ability to use computers to efficiently manipulate and analyze large amounts of data resulting from biological experiments and simulations, many of the pressing questions in the life sciences could not be answered. Today's undergraduates, despite the ubiquity of computers in their lives, seem to be largely unfamiliar with how computers are being used to pursue and answer such questions. This article describes an innovative undergraduate-level course, titled Computer Literacy for Life Sciences, that aims to teach students the basics of a computerized scientific research pursuit. The purpose of the course is for students to develop a hands-on working experience in using standard computer software tools as well as computer techniques and methodologies used in life sciences research. This paper provides a detailed description of the didactical tools and assessment methods used in and outside of the classroom as well as a discussion of the lessons learned during the first installment of the course taught at Emory University in fall semester 2009. PMID:20810969

  7. Phytochrome from Green Plants: Properties and biological Function

    SciTech Connect

    Quail, Peter H.

    2014-07-25

    Pfr conformer reverses this activity upon initial light exposure, inducing the switch to photomorphogenic development. This reversal involves light-triggered translocation of the photoactivated phy molecule into the nucleus where it interacts with PIF-family members, inducing rapid phosphorylation and degradation of the PIFs via the ubiquitin-proteasome system. This degradation in turn elicits rapid alterations in gene expression that drive the deetiolation transition. This project has made considerable progress in defining phy-PIF signaling activity in controlling the SAR. The biological functions of the multiple PIF-family members in controlling the SAR, including dissection of the relative contributions of the individual PIFs to this process, as well as to diurnal growth-control oscillations, have been investigated using higher-order pif-mutant combinations. Using microarray analysis of a quadruple pif mutant we have defined the shade-induced, PIF-regulated transcriptional network genome-wide. This has revealed that a dynamic antagonism between the phys and PIFs generates selective reciprocal responses during deetiolation and the SAR in a rapidly light-responsive transcriptional network. Using integrated RNA-seq and ChIP-seq analysis of higher order pif-mutant combinations, we have defined the direct gene-targets of PIF transcriptional regulation, and have obtained evidence that this regulation involves differential direct targeting of rapidly light-responsive genes by the individual PIF-family members. This project has provided significant advances in our understanding of the molecular mechanisms by which the phy-PIF photosensory signaling pathway regulates an important bioenergy-related plant response to the light environment. The identification of molecular targets in the primary transcriptional-regulatory circuitry of this pathway has the potential to enable genetic or reverse-genetic manipulation of the partitioning of carbon between reproductive and

  8. Network-based drug discovery by integrating systems biology and computational technologies.

    PubMed

    Leung, Elaine L; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua; Liu, Liang

    2013-07-01

    Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple '-omics' databases. The newly developed algorithm- or network-based computational models can tightly integrate '-omics' databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various '-omics' platforms and computational tools would accelerate development of network-based drug discovery and network medicine.

  9. Network-based drug discovery by integrating systems biology and computational technologies

    PubMed Central

    Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

    2013-01-01

    Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

  10. Optimization of removal function in computer controlled optical surfacing

    NASA Astrophysics Data System (ADS)

    Chen, Xi; Guo, Peiji; Ren, Jianfeng

    2010-10-01

    The technical principle of computer controlled optical surfacing (CCOS) and the common method of optimizing removal function that is used in CCOS are introduced in this paper. A new optimizing method time-sharing synthesis of removal function is proposed to solve problems of the removal function being far away from Gaussian type and slow approaching of the removal function error that encountered in the mode of planet motion or translation-rotation. Detailed time-sharing synthesis of using six removal functions is discussed. For a given region on the workpiece, six positions are selected as the centers of the removal function; polishing tool controlled by the executive system of CCOS revolves around each centre to complete a cycle in proper order. The overall removal function obtained by the time-sharing process is the ratio of total material removal in six cycles to time duration of the six cycles, which depends on the arrangement and distribution of the six removal functions. Simulations on the synthesized overall removal functions under two different modes of motion, i.e., planet motion and translation-rotation are performed from which the optimized combination of tool parameters and distribution of time-sharing synthesis removal functions are obtained. The evaluation function when optimizing is determined by an approaching factor which is defined as the ratio of the material removal within the area of half of the polishing tool coverage from the polishing center to the total material removal within the full polishing tool coverage area. After optimization, it is found that the optimized removal function obtained by time-sharing synthesis is closer to the ideal Gaussian type removal function than those by the traditional methods. The time-sharing synthesis method of the removal function provides an efficient way to increase the convergence speed of the surface error in CCOS for the fabrication of aspheric optical surfaces, and to reduce the intermediate- and high

  11. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

    PubMed Central

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2017-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

  12. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

    PubMed

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2016-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

  13. Efficient Computation of Functional Brain Networks: toward Real-Time Functional Connectivity

    PubMed Central

    García-Prieto, Juan; Bajo, Ricardo; Pereda, Ernesto

    2017-01-01

    Functional Connectivity has demonstrated to be a key concept for unraveling how the brain balances functional segregation and integration properties while processing information. This work presents a set of open-source tools that significantly increase computational efficiency of some well-known connectivity indices and Graph-Theory measures. PLV, PLI, ImC, and wPLI as Phase Synchronization measures, Mutual Information as an information theory based measure, and Generalized Synchronization indices are computed much more efficiently than prior open-source available implementations. Furthermore, network theory related measures like Strength, Shortest Path Length, Clustering Coefficient, and Betweenness Centrality are also implemented showing computational times up to thousands of times faster than most well-known implementations. Altogether, this work significantly expands what can be computed in feasible times, even enabling whole-head real-time network analysis of brain function. PMID:28220071

  14. Efficient Computation of Functional Brain Networks: toward Real-Time Functional Connectivity.

    PubMed

    García-Prieto, Juan; Bajo, Ricardo; Pereda, Ernesto

    2017-01-01

    Functional Connectivity has demonstrated to be a key concept for unraveling how the brain balances functional segregation and integration properties while processing information. This work presents a set of open-source tools that significantly increase computational efficiency of some well-known connectivity indices and Graph-Theory measures. PLV, PLI, ImC, and wPLI as Phase Synchronization measures, Mutual Information as an information theory based measure, and Generalized Synchronization indices are computed much more efficiently than prior open-source available implementations. Furthermore, network theory related measures like Strength, Shortest Path Length, Clustering Coefficient, and Betweenness Centrality are also implemented showing computational times up to thousands of times faster than most well-known implementations. Altogether, this work significantly expands what can be computed in feasible times, even enabling whole-head real-time network analysis of brain function.

  15. Computations involving differential operators and their actions on functions

    NASA Technical Reports Server (NTRS)

    Crouch, Peter E.; Grossman, Robert; Larson, Richard

    1991-01-01

    The algorithms derived by Grossmann and Larson (1989) are further developed for rewriting expressions involving differential operators. The differential operators involved arise in the local analysis of nonlinear dynamical systems. These algorithms are extended in two different directions: the algorithms are generalized so that they apply to differential operators on groups and the data structures and algorithms are developed to compute symbolically the action of differential operators on functions. Both of these generalizations are needed for applications.

  16. COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

    PubMed Central

    Kapetanovic, I.M.

    2008-01-01

    It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

  17. Efficient quantum algorithm for computing n-time correlation functions.

    PubMed

    Pedernales, J S; Di Candia, R; Egusquiza, I L; Casanova, J; Solano, E

    2014-07-11

    We propose a method for computing n-time correlation functions of arbitrary spinorial, fermionic, and bosonic operators, consisting of an efficient quantum algorithm that encodes these correlations in an initially added ancillary qubit for probe and control tasks. For spinorial and fermionic systems, the reconstruction of arbitrary n-time correlation functions requires the measurement of two ancilla observables, while for bosonic variables time derivatives of the same observables are needed. Finally, we provide examples applicable to different quantum platforms in the frame of the linear response theory.

  18. Computational prediction of functional abortive RNA in E. coli.

    PubMed

    Marcus, Jeremy I; Hassoun, Soha; Nair, Nikhil U

    2017-03-24

    Failure by RNA polymerase to break contacts with promoter DNA results in release of bound RNA and re-initiation of transcription. These abortive RNAs were assumed to be non-functional but have recently been shown to affect termination in bacteriophage T7. Little is known about the functional role of these RNA in other genetic models. Using a computational approach, we investigated whether abortive RNA could exert function in E. coli. Fragments generated from 3780 transcription units were used as query sequences within their respective transcription units to search for possible binding sites. Sites that fell within known regulatory features were then ranked based upon the free energy of hybridization to the abortive. We further hypothesize about mechanisms of regulatory action for a select number of likely matches. Future experimental validation of these putative abortive-mRNA pairs may confirm our findings and promote exploration of functional abortive RNAs (faRNAs) in natural and synthetic systems.

  19. LGL: creating a map of protein function with an algorithm for visualizing very large biological networks.

    PubMed

    Adai, Alex T; Date, Shailesh V; Wieland, Shannon; Marcotte, Edward M

    2004-06-25

    Networks are proving to be central to the study of gene function, protein-protein interaction, and biochemical pathway data. Visualization of networks is important for their study, but visualization tools are often inadequate for working with very large biological networks. Here, we present an algorithm, called large graph layout (LGL), which can be used to dynamically visualize large networks on the order of hundreds of thousands of vertices and millions of edges. LGL applies a force-directed iterative layout guided by a minimal spanning tree of the network in order to generate coordinates for the vertices in two or three dimensions, which are subsequently visualized and interactively navigated with companion programs. We demonstrate the use of LGL in visualizing an extensive protein map summarizing the results of approximately 21 billion sequence comparisons between 145579 proteins from 50 genomes. Proteins are positioned in the map according to sequence homology and gene fusions, with the map ultimately serving as a theoretical framework that integrates inferences about gene function derived from sequence homology, remote homology, gene fusions, and higher-order fusions. We confirm that protein neighbors in the resulting map are functionally related, and that distinct map regions correspond to distinct cellular systems, enabling a computational strategy for discovering proteins' functions on the basis of the proteins' map positions. Using the map produced by LGL, we infer general functions for 23 uncharacterized protein families.

  20. Computational modeling of chemo-bio-mechanical coupling: a systems-biology approach toward wound healing.

    PubMed

    Buganza Tepole, A; Kuhl, E

    2016-01-01

    Wound healing is a synchronized cascade of chemical, biological, and mechanical phenomena, which act in concert to restore the damaged tissue. An imbalance between these events can induce painful scarring. Despite intense efforts to decipher the mechanisms of wound healing, the role of mechanics remains poorly understood. Here, we establish a computational systems biology model to identify the chemical, biological, and mechanical mechanisms of scar formation. First, we introduce the generic problem of coupled chemo-bio-mechanics. Then, we introduce the model problem of wound healing in terms of a particular chemical signal, inflammation, a particular biological cell type, fibroblasts, and a particular mechanical model, isotropic hyperelasticity. We explore the cross-talk between chemical, biological, and mechanical signals and show that all three fields have a significant impact on scar formation. Our model is the first step toward rigorous multiscale, multifield modeling in wound healing. Our formulation has the potential to improve effective wound management and optimize treatment on an individualized patient-specific basis.

  1. Structural and Computational Biology in the Design of Immunogenic Vaccine Antigens.

    PubMed

    Liljeroos, Lassi; Malito, Enrico; Ferlenghi, Ilaria; Bottomley, Matthew James

    2015-01-01

    Vaccination is historically one of the most important medical interventions for the prevention of infectious disease. Previously, vaccines were typically made of rather crude mixtures of inactivated or attenuated causative agents. However, over the last 10-20 years, several important technological and computational advances have enabled major progress in the discovery and design of potently immunogenic recombinant protein vaccine antigens. Here we discuss three key breakthrough approaches that have potentiated structural and computational vaccine design. Firstly, genomic sciences gave birth to the field of reverse vaccinology, which has enabled the rapid computational identification of potential vaccine antigens. Secondly, major advances in structural biology, experimental epitope mapping, and computational epitope prediction have yielded molecular insights into the immunogenic determinants defining protective antigens, enabling their rational optimization. Thirdly, and most recently, computational approaches have been used to convert this wealth of structural and immunological information into the design of improved vaccine antigens. This review aims to illustrate the growing power of combining sequencing, structural and computational approaches, and we discuss how this may drive the design of novel immunogens suitable for future vaccines urgently needed to increase the global prevention of infectious disease.

  2. Structural and Computational Biology in the Design of Immunogenic Vaccine Antigens

    PubMed Central

    Liljeroos, Lassi; Malito, Enrico; Ferlenghi, Ilaria; Bottomley, Matthew James

    2015-01-01

    Vaccination is historically one of the most important medical interventions for the prevention of infectious disease. Previously, vaccines were typically made of rather crude mixtures of inactivated or attenuated causative agents. However, over the last 10–20 years, several important technological and computational advances have enabled major progress in the discovery and design of potently immunogenic recombinant protein vaccine antigens. Here we discuss three key breakthrough approaches that have potentiated structural and computational vaccine design. Firstly, genomic sciences gave birth to the field of reverse vaccinology, which has enabled the rapid computational identification of potential vaccine antigens. Secondly, major advances in structural biology, experimental epitope mapping, and computational epitope prediction have yielded molecular insights into the immunogenic determinants defining protective antigens, enabling their rational optimization. Thirdly, and most recently, computational approaches have been used to convert this wealth of structural and immunological information into the design of improved vaccine antigens. This review aims to illustrate the growing power of combining sequencing, structural and computational approaches, and we discuss how this may drive the design of novel immunogens suitable for future vaccines urgently needed to increase the global prevention of infectious disease. PMID:26526043

  3. Prioritizing drug targets in Clostridium botulinum with a computational systems biology approach.

    PubMed

    Muhammad, Syed Aun; Ahmed, Safia; Ali, Amjad; Huang, Hui; Wu, Xiaogang; Yang, X Frank; Naz, Anam; Chen, Jake

    2014-07-01

    A computational and in silico system level framework was developed to identify and prioritize the antibacterial drug targets in Clostridium botulinum (Clb), the causative agent of flaccid paralysis in humans that can be fatal in 5 to 10% of cases. This disease is difficult to control due to the emergence of drug-resistant pathogenic strains and the only available treatment antitoxin which can target the neurotoxin at the extracellular level and cannot reverse the paralysis. This study framework is based on comprehensive systems-scale analysis of genomic sequence homology and phylogenetic relationships among Clostridium, other infectious bacteria, host and human gut flora. First, the entire 2628-annotated genes of this bacterial genome were categorized into essential, non-essential and virulence genes. The results obtained showed that 39% of essential proteins that functionally interact with virulence proteins were identified, which could be a key to new interventions that may kill the bacteria and minimize the host damage caused by the virulence factors. Second, a comprehensive comparative COGs and blast sequence analysis of these proteins and host proteins to minimize the risks of side effects was carried out. This revealed that 47% of a set of C. botulinum proteins were evolutionary related with Homo sapiens proteins to sort out the non-human homologs. Third, orthology analysis with other infectious bacteria to assess broad-spectrum effects was executed and COGs were mostly found in Clostridia, Bacilli (Firmicutes), and in alpha and beta Proteobacteria. Fourth, a comparative phylogenetic analysis was performed with human microbiota to filter out drug targets that may also affect human gut flora. This reduced the list of candidate proteins down to 131. Finally, the role of these putative drug targets in clostridial biological pathways was studied while subcellular localization of these candidate proteins in bacterial cellular system exhibited that 68% of the

  4. Teacher Perceptions of the Integration of Laptop Computers in Their High School Biology Classrooms

    NASA Astrophysics Data System (ADS)

    Gundy, Morag S.

    2011-12-01

    Studies indicate that teachers, and in particular science teachers in the senior high school grades, do not integrate laptop computers into their instruction to the extent anticipated by researchers. This technology has not spread easily to other teachers even with improved access to hardware and software, increased support, and a paradigm shift from teacher-centred to student-centred education. Although a number of studies have focused on the issues and problems related to the integration of laptops in classroom instruction, these studies, largely quantitative in nature, have tended to bypass the role teachers play in integrating laptop computers into their instruction. This thesis documents and describes the role of Ontario high school science teachers in the integration of laptop computers in the classroom. Ten teachers who have successfully integrated laptop computers into their biology courses participated in this descriptive study. Their perceptions of implementing laptops into their biology courses, key factors about the implementation process, and how the implementation was accomplished are examined. The study also identifies the conditions which they feel would allow this innovation to be implemented by other teachers. Key findings of the study indicate that teachers must initiate, implement and sustain an emergent and still evolving innovation; teacher perceptions change and continue to change with increased experience using laptops in the science classroom; changes in teaching approaches are significant as a result of the introduction of laptop technology; and, the teachers considered the acquisition and use of new teaching materials to be an important aspect of integrating laptop computers into instruction. Ongoing challenges for appropriate professional development, sharing of knowledge, skills and teaching materials are identified. The study provides a body of practical knowledge for biology teachers who are considering the integration of laptops into

  5. Biological adaptations for functional features of language in the face of cultural evolution.

    PubMed

    Christiansen, Morten H; Reali, Florencia; Chater, Nick

    2011-04-01

    Although there may be no true language universals, it is nonetheless possible to discern several family resemblance patterns across the languages of the world. Recent work on the cultural evolution of language indicates the source of these patterns is unlikely to be an innate universal grammar evolved through biological adaptations for arbitrary linguistic features. Instead, it has been suggested that the patterns of resemblance emerge because language has been shaped by the brain, with individual languages representing different but partially overlapping solutions to the same set of nonlinguistic constraints. Here, we use computational simulations to investigate whether biological adaptation for functional features of language, deriving from cognitive and communicative constraints, may nonetheless be possible alongside rapid cultural evolution. Specifically, we focus on the Baldwin effect as an evolutionary mechanism by which previously learned linguistic features might become innate through natural selection across many generations of language users. The results indicate that cultural evolution of language does not necessarily prevent functional features of language from becoming genetically fixed, thus potentially providing a particularly informative source of constraints on cross-linguistic resemblance patterns.

  6. Discovery of biological networks from diverse functional genomic data

    PubMed Central

    Myers, Chad L; Robson, Drew; Wible, Adam; Hibbs, Matthew A; Chiriac, Camelia; Theesfeld, Chandra L; Dolinski, Kara; Troyanskaya, Olga G

    2005-01-01

    We have developed a general probabilistic system for query-based discovery of pathway-specific networks through integration of diverse genome-wide data. This framework was validated by accurately recovering known networks for 31 biological processes in Saccharomyces cerevisiae and experimentally verifying predictions for the process of chromosomal segregation. Our system, bioPIXIE, a public, comprehensive system for integration, analysis, and visualization of biological network predictions for S. cerevisiae, is freely accessible over the worldwide web. PMID:16420673

  7. A general computational framework for modeling cellular structure and function.

    PubMed Central

    Schaff, J; Fink, C C; Slepchenko, B; Carson, J H; Loew, L M

    1997-01-01

    The "Virtual Cell" provides a general system for testing cell biological mechanisms and creates a framework for encapsulating the burgeoning knowledge base comprising the distribution and dynamics of intracellular biochemical processes. It approaches the problem by associating biochemical and electrophysiological data describing individual reactions with experimental microscopic image data describing their subcellular localizations. Individual processes are collected within a physical and computational infrastructure that accommodates any molecular mechanism expressible as rate equations or membrane fluxes. An illustration of the method is provided by a dynamic simulation of IP3-mediated Ca2+ release from endoplasmic reticulum in a neuronal cell. The results can be directly compared to experimental observations and provide insight into the role of experimentally inaccessible components of the overall mechanism. Images FIGURE 1 FIGURE 2 FIGURE 4 FIGURE 5 PMID:9284281

  8. Distinguishing Pattern Formation Phenotypes: Applying Minkowski Functionals to Cell Biology Systems

    NASA Astrophysics Data System (ADS)

    Rericha, Erin; Guven, Can; Parent, Carole; Losert, Wolfgang

    2011-03-01

    Spatial Clustering of proteins within cells or cells themselves frequently occur in cell biology systems. However quantifying the underlying order and determining the regulators of these cluster patterns have proved difficult due to the inherent high noise levels in the systems. For instance the patterns formed by wild type and cyclic-AMP regulatory mutant Dictyostelium cells are visually distinctive, yet the large error bars in measurements of the fractal number, area, Euler number, eccentricity, and wavelength making it difficult to quantitatively distinguish between the patterns. We apply a spatial analysis technique based on Minkowski functionals and develop metrics which clearly separate wild type and mutant cell lines into distinct categories. Having such a metric facilitated the development of a computational model for cellular aggregation and its regulators. Supported by NIH-NGHS Nanotechnology (R01GM085574) and the Burroughs Wellcome Fund.

  9. Ab Initio Calculations of the Electronic Structures and Biological Functions of Protein Molecules

    NASA Astrophysics Data System (ADS)

    Zheng, Haoping

    The self-consistent cluster-embedding (SCCE) calculation method reduces the computational effort from M3 to about M1 (M is the number of atoms in the system) with precise calculations. Thus the ab initio, all-electron calculation of the electronic structure and biological function of protein molecule has become a reality, which will promote new proteomics considerably. The calculated results of two real protein molecules, the trypsin inhibitor from the seeds of squash Cucurbita maxima (CMTI-I, 436 atoms) and the ascaris trypsin inhibitor (912 atoms, two three-dimensional structures), will be presented in this paper. The reactive sites of the inhibitors are determined and explained. The accuracy of structure determination of the inhibitors are tested theoretically.

  10. Ab Initio Calculations of the Electronic Structures and Biological Functions of Protein Molecules

    NASA Astrophysics Data System (ADS)

    Zheng, Haoping

    2003-04-01

    The self-consistent cluster-embedding (SCCE) calculation method reduces the computational effort from M3 to about M1 (M is the number of atoms in the system) with unchanged calculation precision. So the ab initio, all-electron calculation of the electronic structure and biological function of protein molecule becomes a reality, which will promote new proteomics considerably. The calculated results of two real protein molecules, the trypsin inhibitor from the seeds of squash Cucurbita maxima (CMTI-I, 436 atoms) and the Ascaris trypsin inhibitor (912 atoms, two three-dimensional structures), are presented. The reactive sites of the inhibitors are determined and explained. The precision of structure determination of inhibitors are tested theoretically.

  11. Heterogeneous processes at the intersection of chemistry and biology: A computational approach

    SciTech Connect

    Kuo, I W; Mundy, C J

    2008-02-11

    Heterogeneous processes hold the key to understanding many problems in biology and atmospheric science. In particular, recent experiments have shown that heterogeneous chemistry at the surface of sea-salt aerosols plays a large role in important atmospheric processes with far reaching implications towards understanding of the fate and transport of aerosolized chemical weapons (i.e. organophosphates such as sarin and VX). Unfortunately, the precise mechanistic details of the simplest surface enhanced chemical reactions remain unknown. Understanding heterogeneous processes also has implications in the biological sciences. Traditionally, it is accepted that enzymes catalyze reactions by stabilizing the transition state, thereby lowering the free energy barrier. However, recent findings have shown that a multitude of phenomena likely contribute to the efficiency of enzymes, such as coupled protein motion, quantum mechanical tunneling, or strong electrostatic binding. The objective of this project was to develop and validate a single computational framework based on first principles simulations using tera-scale computational resources to answer fundamental scientific questions about heterogeneous chemical processes relevant to atmospheric chemistry and biological sciences.

  12. Computational modeling of STED microscopy through multiple biological cells under one- and two-photon excitation

    NASA Astrophysics Data System (ADS)

    Mark, Andrew E.; Davis, Mitchell A.; Starosta, Matthew S.; Dunn, Andrew K.

    2015-03-01

    While superresolution optical microscopy techniques afford enhanced resolution for biological applications, they have largely been used to study structures in isolated cells. We use the FDTD method to simulate the propagation of focused beams for STED microscopy through multiple biological cells. We model depletion beams that provide 2D and 3D confinement of the fluorescence spot and assess the effective PSF of the system as a function of focal depth. We compare the relative size of the STED effective PSF under one- and two-photon excitation. PSF calculations suggest that imaging is possible up to the maximum simulation depth if the fluorescence emission remains detectable.

  13. Synthetic biology in cyanobacteria engineering and analyzing novel functions.

    PubMed

    Heidorn, Thorsten; Camsund, Daniel; Huang, Hsin-Ho; Lindberg, Pia; Oliveira, Paulo; Stensjö, Karin; Lindblad, Peter

    2011-01-01

    Cyanobacteria are the only prokaryotes capable of using sunlight as their energy, water as an electron donor, and air as a source of carbon and, for some nitrogen-fixing strains, nitrogen. Compared to algae and plants, cyanobacteria are much easier to genetically engineer, and many of the standard biological parts available for Synthetic Biology applications in Escherichia coli can also be used in cyanobacteria. However, characterization of such parts in cyanobacteria reveals differences in performance when compared to E. coli, emphasizing the importance of detailed characterization in the cellular context of a biological chassis. Furthermore, cyanobacteria possess special characteristics (e.g., multiple copies of their chromosomes, high content of photosynthetically active proteins in the thylakoids, the presence of exopolysaccharides and extracellular glycolipids, and the existence of a circadian rhythm) that have to be taken into account when genetically engineering them. With this chapter, the synthetic biologist is given an overview of existing biological parts, tools and protocols for the genetic engineering, and molecular analysis of cyanobacteria for Synthetic Biology applications.

  14. On the Hydrodynamic Function of Sharkskin: A Computational Investigation

    NASA Astrophysics Data System (ADS)

    Boomsma, Aaron; Sotiropoulos, Fotis

    2014-11-01

    Denticles (placoid scales) are small structures that cover the epidermis of some sharks. The hydrodynamic function of denticles is unclear. Because they resemble riblets, they have been thought to passively reduce skin-friction-for which there is some experimental evidence. Others have experimentally shown that denticles increase skin-friction and have hypothesized that denticles act as vortex generators to delay separation. To help clarify their function, we use high-resolution large eddy and direct numerical simulations, with an immersed boundary method, to simulate flow patterns past and calculate the drag force on Mako Short Fin denticles. Simulations are carried out for the denticles placed in a canonical turbulent boundary layer as well as in the vicinity of a separation bubble. The computed results elucidate the three-dimensional structure of the flow around denticles and provide insights into the hydrodynamic function of sharkskin.

  15. Structure-based Methods for Computational Protein Functional Site Prediction

    PubMed Central

    Dukka, B KC

    2013-01-01

    Due to the advent of high throughput sequencing techniques and structural genomic projects, the number of gene and protein sequences has been ever increasing. Computational methods to annotate these genes and proteins are even more indispensable. Proteins are important macromolecules and study of the function of proteins is an important problem in structural bioinformatics. This paper discusses a number of methods to predict protein functional site especially focusing on protein ligand binding site prediction. Initially, a short overview is presented on recent advances in methods for selection of homologous sequences. Furthermore, a few recent structural based approaches and sequence-and-structure based approaches for protein functional sites are discussed in details. PMID:24688745

  16. Motion as a source of environmental information: a fresh view on biological motion computation by insect brains.

    PubMed

    Egelhaaf, Martin; Kern, Roland; Lindemann, Jens Peter

    2014-01-01

    Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around ("optic flow") to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and-in many behavioral contexts-less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.

  17. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  18. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  19. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  20. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  1. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  2. Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy.

    PubMed

    Schroll, Henning; Hamker, Fred H

    2013-12-30

    Over the past 15 years, computational models have had a considerable impact on basal-ganglia research. Most of these models implement multiple distinct basal-ganglia pathways and assume them to fulfill different functions. As there is now a multitude of different models, it has become complex to keep track of their various, sometimes just marginally different assumptions on pathway functions. Moreover, it has become a challenge to oversee to what extent individual assumptions are corroborated or challenged by empirical data. Focusing on computational, but also considering non-computational models, we review influential concepts of pathway functions and show to what extent they are compatible with or contradict each other. Moreover, we outline how empirical evidence favors or challenges specific model assumptions and propose experiments that allow testing assumptions against each other.

  3. Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy

    PubMed Central

    Schroll, Henning; Hamker, Fred H.

    2013-01-01

    Over the past 15 years, computational models have had a considerable impact on basal-ganglia research. Most of these models implement multiple distinct basal-ganglia pathways and assume them to fulfill different functions. As there is now a multitude of different models, it has become complex to keep track of their various, sometimes just marginally different assumptions on pathway functions. Moreover, it has become a challenge to oversee to what extent individual assumptions are corroborated or challenged by empirical data. Focusing on computational, but also considering non-computational models, we review influential concepts of pathway functions and show to what extent they are compatible with or contradict each other. Moreover, we outline how empirical evidence favors or challenges specific model assumptions and propose experiments that allow testing assumptions against each other. PMID:24416002

  4. [Evolutionary-biological peculiarities of transglutaminase. Structure, physiological functions, application].

    PubMed

    Shleĭkin, A G; Danilov, N P

    2011-01-01

    Transglutaminasc (protein-glutamine gamma-glutamyltransferase, EC 2.3.2.13, TG) catalyzes reactions of the acyl transfer, which introduce the epsilon-(gamma-glutamyl)lysine bonds between proteins to create polymers of high mol. mass. Properties of the TG enzyme are described. Its structure is considered: there are characterized items of the TG life cycle and stability, its biological (physiological) role, and significance in pathology and medicine as well as obtaining of the purified enzyme preparations and their use. There are compared TG from different sources: of animal and microbial origin. Mechanism of catalysis of microbial TG is discussed. There are presented characteristics of isoenzymes from different biological sources.

  5. [The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology].

    PubMed

    Menshutkin, V V; Kazanskiĭ, A B; Levchenko, V F

    2010-01-01

    The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.

  6. The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt

    PubMed Central

    Mulder, Nicola J.; Christoffels, Alan; de Oliveira, Tulio; Gamieldien, Junaid; Hazelhurst, Scott; Joubert, Fourie; Kumuthini, Judit; Pillay, Ché S.; Snoep, Jacky L.; Tastan Bishop, Özlem; Tiffin, Nicki

    2016-01-01

    Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt. PMID:26845152

  7. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

    PubMed Central

    Laraia, Luca; McKenzie, Grahame; Spring, David R.; Venkitaraman, Ashok R.; Huggins, David J.

    2015-01-01

    Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs. PMID:26091166

  8. Fuzzy Logic as a Computational Tool for Quantitative Modelling of Biological Systems with Uncertain Kinetic Data.

    PubMed

    Bordon, Jure; Moskon, Miha; Zimic, Nikolaj; Mraz, Miha

    2015-01-01

    Quantitative modelling of biological systems has become an indispensable computational approach in the design of novel and analysis of existing biological systems. However, kinetic data that describe the system's dynamics need to be known in order to obtain relevant results with the conventional modelling techniques. These data are often hard or even impossible to obtain. Here, we present a quantitative fuzzy logic modelling approach that is able to cope with unknown kinetic data and thus produce relevant results even though kinetic data are incomplete or only vaguely defined. Moreover, the approach can be used in the combination with the existing state-of-the-art quantitative modelling techniques only in certain parts of the system, i.e., where kinetic data are missing. The case study of the approach proposed here is performed on the model of three-gene repressilator.

  9. The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt.

    PubMed

    Mulder, Nicola J; Christoffels, Alan; de Oliveira, Tulio; Gamieldien, Junaid; Hazelhurst, Scott; Joubert, Fourie; Kumuthini, Judit; Pillay, Ché S; Snoep, Jacky L; Tastan Bishop, Özlem; Tiffin, Nicki

    2016-02-01

    Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt.

  10. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions.

    PubMed

    Laraia, Luca; McKenzie, Grahame; Spring, David R; Venkitaraman, Ashok R; Huggins, David J

    2015-06-18

    Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs.

  11. Computer Modeling of the Earliest Cellular Structures and Functions

    NASA Technical Reports Server (NTRS)

    Pohorille, Andrew; Chipot, Christophe; Schweighofer, Karl

    2000-01-01

    In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.

  12. Translating Lung Function Genome-Wide Association Study (GWAS) Findings: New Insights for Lung Biology.

    PubMed

    Kheirallah, A K; Miller, S; Hall, I P; Sayers, I

    2016-01-01

    Chronic respiratory diseases are a major cause of worldwide mortality and morbidity. Although hereditary severe deficiency of α1 antitrypsin (A1AD) has been established to cause emphysema, A1AD accounts for only ∼ 1% of Chronic Obstructive Pulmonary Disease (COPD) cases. Genome-wide association studies (GWAS) have been successful at detecting multiple loci harboring variants predicting the variation in lung function measures and risk of COPD. However, GWAS are incapable of distinguishing causal from noncausal variants. Several approaches can be used for functional translation of genetic findings. These approaches have the scope to identify underlying alleles and pathways that are important in lung function and COPD. Computational methods aim at effective functional variant prediction by combining experimentally generated regulatory information with associated region of the human genome. Classically, GWAS association follow-up concentrated on manipulation of a single gene. However association data has identified genetic variants in >50 loci predicting disease risk or lung function. Therefore there is a clear precedent for experiments that interrogate multiple candidate genes in parallel, which is now possible with genome editing technology. Gene expression profiling can be used for effective discovery of biological pathways underpinning gene function. This information may be used for informed decisions about cellular assays post genetic manipulation. Investigating respiratory phenotypes in human lung tissue and specific gene knockout mice is a valuable in vivo approach that can complement in vitro work. Herein, we review state-of-the-art in silico, in vivo, and in vitro approaches that may be used to accelerate functional translation of genetic findings.

  13. Oxidative metabolites of lycopene and their biological functions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To gain a better understanding of the beneficial biological activities of lycopene on cancer prevention, a greater knowledge of the metabolism of lycopene is needed. In particular, the identification of lycopene metabolites and oxidation products in vivo; the importance of tissue specific lycopene c...

  14. A Combination of Hand-Held Models and Computer Imaging Programs Helps Students Answer Oral Questions about Molecular Structure and Function: A Controlled Investigation of Student Learning

    ERIC Educational Resources Information Center

    Harris, Michelle A.; Peck, Ronald F.; Colton, Shannon; Morris, Jennifer; Neto, Elias Chaibub; Kallio, Julie

    2009-01-01

    We conducted a controlled investigation to examine whether a combination of computer imagery and tactile tools helps introductory cell biology laboratory undergraduate students better learn about protein structure/function relationships as compared with computer imagery alone. In all five laboratory sections, students used the molecular imaging…

  15. Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference.

    PubMed

    Wren, Jonathan D; Dozmorov, Mikhail G; Burian, Dennis; Kaundal, Rakesh; Perkins, Andy; Perkins, Ed; Kupfer, Doris M; Springer, Gordon K

    2013-01-01

    The tenth annual conference of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS 2013), "The 10th Anniversary in a Decade of Change: Discovery in a Sea of Data", took place at the Stoney Creek Inn & Conference Center in Columbia, Missouri on April 5-6, 2013. This year's Conference Chairs were Gordon Springer and Chi-Ren Shyu from the University of Missouri and Edward Perkins from the US Army Corps of Engineers Engineering Research and Development Center, who is also the current MCBIOS President (2012-3). There were 151 registrants and a total of 111 abstracts (51 oral presentations and 60 poster session abstracts).

  16. Non-functioning adrenal adenomas discovered incidentally on computed tomography

    SciTech Connect

    Mitnick, J.S.; Bosniak, M.A.; Megibow, A.J.; Naidich, D.P.

    1983-08-01

    Eighteen patients with unilateral non-metastatic non-functioning adrenal masses were studied with computed tomography (CT). Pathological examination in cases revealed benign adrenal adenomas. The others were followed up with serial CT scans and found to show no change in tumor size over a period of six months to three years. On the basis of these findings, the authors suggest certain criteria of a benign adrenal mass, including (a) diameter less than 5 cm, (b) smooth contour, (c) well-defined margin, and (d) no change in size on follow-up. Serial CT scanning can be used as an alternative to surgery in the management of many of these patients.

  17. Material reconstruction for spectral computed tomography with detector response function

    NASA Astrophysics Data System (ADS)

    Liu, Jiulong; Gao, Hao

    2016-11-01

    Different from conventional computed tomography (CT), spectral CT using energy-resolved photon-counting detectors is able to provide the unprecedented material compositions. However accurate spectral CT needs to account for the detector response function (DRF), which is often distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. The simulation results suggest that the proposed methods reconstructed more accurate material compositions than the conventional method without DRF. Moreover, the proposed linearized method with linear data fidelity from spectral resampling had improved reconstruction quality from the nonlinear method directly based on nonlinear data fidelity.

  18. ISCB: past-present perspective for the International Society for Computational Biology.

    PubMed

    Rost, Burkhard

    2014-01-01

    Since its establishment in 1997, International Society for Computational Biology (ISCB) has contributed importantly toward advancing the understanding of living systems through computation. The ISCB represents nearly 3000 members working in >70 countries. It has doubled the number of members since 2007. At the same time, the number of meetings organized by the ISCB has increased from two in 2007 to eight in 2013, and the society has cemented many lasting alliances with regional societies and specialist groups. ISCB is ready to grow into a challenging and promising future. The progress over the past 7 years has resulted from the vision, and possibly more importantly, the passion and hard working dedication of many individuals.

  19. ISCB: past-present perspective for the International Society for Computational Biology.

    PubMed

    Rost, Burkhard

    2013-12-15

    Since its establishment in 1997, International Society for Computational Biology (ISCB) has contributed importantly toward advancing the understanding of living systems through computation. The ISCB represents nearly 3000 members working in >70 countries. It has doubled the number of members since 2007. At the same time, the number of meetings organized by the ISCB has increased from two in 2007 to eight in 2013, and the society has cemented many lasting alliances with regional societies and specialist groups. ISCB is ready to grow into a challenging and promising future. The progress over the past 7 years has resulted from the vision, and possibly more importantly, the passion and hard working dedication of many individuals.

  20. Understanding sequence similarity and framework analysis between centromere proteins using computational biology.

    PubMed

    Doss, C George Priya; Chakrabarty, Chiranjib; Debajyoti, C; Debottam, S

    2014-11-01

    Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.

  1. Multiscale modeling of biological functions: from enzymes to molecular machines (Nobel Lecture).

    PubMed

    Warshel, Arieh

    2014-09-15

    A detailed understanding of the action of biological molecules is a pre-requisite for rational advances in health sciences and related fields. Here, the challenge is to move from available structural information to a clear understanding of the underlying function of the system. In light of the complexity of macromolecular complexes, it is essential to use computer simulations to describe how the molecular forces are related to a given function. However, using a full and reliable quantum mechanical representation of large molecular systems has been practically impossible. The solution to this (and related) problems has emerged from the realization that large systems can be spatially divided into a region where the quantum mechanical description is essential (e.g. a region where bonds are being broken), with the remainder of the system being represented on a simpler level by empirical force fields. This idea has been particularly effective in the development of the combined quantum mechanics/molecular mechanics (QM/MM) models. Here, the coupling between the electrostatic effects of the quantum and classical subsystems has been a key to the advances in describing the functions of enzymes and other biological molecules. The same idea of representing complex systems in different resolutions in both time and length scales has been found to be very useful in modeling the action of complex systems. In such cases, starting with coarse grained (CG) representations that were originally found to be very useful in simulating protein folding, and augmenting them with a focus on electrostatic energies, has led to models that are particularly effective in probing the action of molecular machines. The same multiscale idea is likely to play a major role in modeling of even more complex systems, including cells and collections of cells.

  2. Multiscale Modeling of Biological Functions: From Enzymes to Molecular Machines (Nobel Lecture)

    PubMed Central

    Warshel, Arieh

    2016-01-01

    Adetailed understanding of the action of biological molecules is a pre-requisite for rational advances in health sciences and related fields. Here, the challenge is to move from available structural information to a clear understanding of the underlying function of the system. In light of the complexity of macromolecular complexes, it is essential to use computer simulations to describe how the molecular forces are related to a given function. However, using a full and reliable quantum mechanical representation of large molecular systems has been practically impossible. The solution to this (and related) problems has emerged from the realization that large systems can be spatially divided into a region where the quantum mechanical description is essential (e.g. a region where bonds are being broken), with the remainder of the system being represented on a simpler level by empirical force fields. This idea has been particularly effective in the development of the combined quantum mechanics/molecular mechanics (QM/MM) models. Here, the coupling between the electrostatic effects of the quantum and classical subsystems has been a key to the advances in describing the functions of enzymes and other biological molecules. The same idea of representing complex systems in different resolutions in both time and length scales has been found to be very useful in modeling the action of complex systems. In such cases, starting with coarse grained (CG) representations that were originally found to be very useful in simulating protein folding, and augmenting them with a focus on electrostatic energies, has led to models that are particularly effective in probing the action of molecular machines. The same multiscale idea is likely to play a major role in modeling of even more complex systems, including cells and collections of cells. PMID:25060243

  3. Computation of the lattice Green function for a dislocation

    NASA Astrophysics Data System (ADS)

    Tan, Anne Marie Z.; Trinkle, Dallas R.

    2016-08-01

    Modeling isolated dislocations is challenging due to their long-ranged strain fields. Flexible boundary condition methods capture the correct long-range strain field of a defect by coupling the defect core to an infinite harmonic bulk through the lattice Green function (LGF). To improve the accuracy and efficiency of flexible boundary condition methods, we develop a numerical method to compute the LGF specifically for a dislocation geometry; in contrast to previous methods, where the LGF was computed for the perfect bulk as an approximation for the dislocation. Our approach directly accounts for the topology of a dislocation, and the errors in the LGF computation converge rapidly for edge dislocations in a simple cubic model system as well as in BCC Fe with an empirical potential. When used within the flexible boundary condition approach, the dislocation LGF relaxes dislocation core geometries in fewer iterations than when the perfect bulk LGF is used as an approximation for the dislocation, making a flexible boundary condition approach more efficient.

  4. Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts

    PubMed Central

    Capitani, Guido; Duarte, Jose M.; Baskaran, Kumaran; Bliven, Spencer; Somody, Joseph C.

    2016-01-01

    Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein–protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein–protein docking. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: guido.capitani@psi.ch PMID:26508758

  5. A proposal for augmenting biological model construction with a semi-intelligent computational modeling assistant

    PubMed Central

    Christley, Scott; An, Gary

    2013-01-01

    The translational challenge in biomedical research lies in the effective and efficient transfer of mechanistic knowledge from one biological context to another. Implicit in this process is the establishment of causality from correlation in the form of mechanistic hypotheses. Effectively addressing the translational challenge requires the use of automated methods, including the ability to computationally capture the dynamic aspect of putative hypotheses such that they can be evaluated in a high throughput fashion. Ontologies provide structure and organization to biomedical knowledge; converting these representations into executable models/simulations is the next necessary step. Researchers need the ability to map their conceptual models into a model specification that can be transformed into an executable simulation program. We suggest this mapping process, which approximates certain steps in the development of a computational model, can be expressed as a set of logical rules, and a semi-intelligent computational agent, the Computational Modeling Assistant (CMA), can perform reasoning to develop a plan to achieve the construction of an executable model. Presented herein is a description and implementation for a model construction reasoning process between biomedical and simulation ontologies that is performed by the CMA to produce the specification of an executable model that can be used for dynamic knowledge representation. PMID:23990750

  6. Algebraic properties of automata associated to Petri nets and applications to computation in biological systems.

    PubMed

    Egri-Nagy, Attila; Nehaniv, Chrystopher L

    2008-01-01

    Biochemical and genetic regulatory networks are often modeled by Petri nets. We study the algebraic structure of the computations carried out by Petri nets from the viewpoint of algebraic automata theory. Petri nets comprise a formalized graphical modeling language, often used to describe computation occurring within biochemical and genetic regulatory networks, but the semantics may be interpreted in different ways in the realm of automata. Therefore, there are several different ways to turn a Petri net into a state-transition automaton. Here, we systematically investigate different conversion methods and describe cases where they may yield radically different algebraic structures. We focus on the existence of group components of the corresponding transformation semigroups, as these reflect symmetries of the computation occurring within the biological system under study. Results are illustrated by applications to the Petri net modelling of intermediary metabolism. Petri nets with inhibition are shown to be computationally rich, regardless of the particular interpretation method. Along these lines we provide a mathematical argument suggesting a reason for the apparent all-pervasiveness of inhibitory connections in living systems.

  7. CMB anisotropy in compact hyperbolic universes. I. Computing correlation functions

    NASA Astrophysics Data System (ADS)

    Bond, J. Richard; Pogosyan, Dmitry; Souradeep, Tarun

    2000-08-01

    Cosmic microwave background (CMB) anisotropy measurements have brought the issue of global topology of the universe from the realm of theoretical possibility to within the grasp of observations. The global topology of the universe modifies the correlation properties of cosmic fields. In particular, strong correlations are predicted in CMB anisotropy patterns on the largest observable scales if the size of the universe is comparable to the distance to the CMB last scattering surface. We describe in detail our completely general scheme using a regularized method of images for calculating such correlation functions in models with nontrivial topology, and apply it to the computationally challenging compact hyperbolic spaces. Our procedure directly sums over images within a specified radius, ideally many times the diameter of the space, effectively treats more distant images in a continuous approximation, and uses Cesaro resummation to further sharpen the results. At all levels of approximation the symmetries of the space are preserved in the correlation function. This new technique eliminates the need for the difficult task of spatial eigenmode decomposition on these spaces. Although the eigenspectrum can be obtained by this method if desired, at a given level of approximation the correlation functions are more accurately determined. We use the 3-torus example to demonstrate that the method works very well. We apply it to power spectrum as well as correlation function evaluations in a number of compact hyperbolic (CH) spaces. Application to the computation of CMB anisotropy correlations on CH spaces, and the observational constraints following from them, are given in a companion paper.

  8. Opposing Biological Functions of Tryptophan Catabolizing Enzymes During Intracellular Infection

    PubMed Central

    Divanovic, Senad; Sawtell, Nancy M.; Trompette, Aurelien; Warning, Jamie I.; Dias, Alexandra; Cooper, Andrea M.; Yap, George S.; Arditi, Moshe; Shimada, Kenichi; DuHadaway, James B.; Prendergast, George C.; Basaraba, Randall J.; Mellor, Andrew L.; Munn, David H.; Aliberti, Julio

    2012-01-01

    Recent studies have underscored physiological and pathophysiological roles for the tryptophan-degrading enzyme indolamine 2,3-dioxygenase (IDO) in immune counterregulation. However, IDO was first recognized as an antimicrobial effector, restricting tryptophan availability to Toxoplasma gondii and other pathogens in vitro. The biological relevance of these findings came under question when infectious phenotypes were not forthcoming in IDO-deficient mice. The recent discovery of an IDO homolog, IDO-2, suggested that the issue deserved reexamination. IDO inhibition during murine toxoplasmosis led to 100% mortality, with increased parasite burdens and no evident effects on the immune response. Similar studies revealed a counterregulatory role for IDO during leishmaniasis (restraining effector immune responses and parasite clearance), and no evident role for IDO in herpes simplex virus type 1 (HSV-1) infection. Thus, IDO plays biologically important roles in the host response to diverse intracellular infections, but the dominant nature of this role—antimicrobial or immunoregulatory—is pathogen-specific. PMID:21990421

  9. Functional Connectivity’s Degenerate View of Brain Computation

    PubMed Central

    Giron, Alain; Rudrauf, David

    2016-01-01

    Brain computation relies on effective interactions between ensembles of neurons. In neuroimaging, measures of functional connectivity (FC) aim at statistically quantifying such interactions, often to study normal or pathological cognition. Their capacity to reflect a meaningful variety of patterns as expected from neural computation in relation to cognitive processes remains debated. The relative weights of time-varying local neurophysiological dynamics versus static structural connectivity (SC) in the generation of FC as measured remains unsettled. Empirical evidence features mixed results: from little to significant FC variability and correlation with cognitive functions, within and between participants. We used a unified approach combining multivariate analysis, bootstrap and computational modeling to characterize the potential variety of patterns of FC and SC both qualitatively and quantitatively. Empirical data and simulations from generative models with different dynamical behaviors demonstrated, largely irrespective of FC metrics, that a linear subspace with dimension one or two could explain much of the variability across patterns of FC. On the contrary, the variability across BOLD time-courses could not be reduced to such a small subspace. FC appeared to strongly reflect SC and to be partly governed by a Gaussian process. The main differences between simulated and empirical data related to limitations of DWI-based SC estimation (and SC itself could then be estimated from FC). Above and beyond the limited dynamical range of the BOLD signal itself, measures of FC may offer a degenerate representation of brain interactions, with limited access to the underlying complexity. They feature an invariant common core, reflecting the channel capacity of the network as conditioned by SC, with a limited, though perhaps meaningful residual variability. PMID:27736900

  10. Computational modeling of skin reflectance spectra for biological parameter estimation through machine learning

    NASA Astrophysics Data System (ADS)

    Vyas, Saurabh; Van Nguyen, Hien; Burlina, Philippe; Banerjee, Amit; Garza, Luis; Chellappa, Rama

    2012-06-01

    A computational skin re ectance model is used here to provide the re ectance, absorption, scattering, and transmittance based on the constitutive biological components that make up the layers of the skin. The changes in re ectance are mapped back to deviations in model parameters, which include melanosome level, collagen level and blood oxygenation. The computational model implemented in this work is based on the Kubelka- Munk multi-layer re ectance model and the Fresnel Equations that describe a generic N-layer model structure. This assumes the skin as a multi-layered material, with each layer consisting of specic absorption, scattering coecients, re ectance spectra and transmittance based on the model parameters. These model parameters include melanosome level, collagen level, blood oxygenation, blood level, dermal depth, and subcutaneous tissue re ectance. We use this model, coupled with support vector machine based regression (SVR), to predict the biological parameters that make up the layers of the skin. In the proposed approach, the physics-based forward mapping is used to generate a large set of training exemplars. The samples in this dataset are then used as training inputs for the SVR algorithm to learn the inverse mapping. This approach was tested on VIS-range hyperspectral data. Performance validation of the proposed approach was performed by measuring the prediction error on the skin constitutive parameters and exhibited very promising results.

  11. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

    PubMed

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work.

  12. A review on data mining and continuous optimization applications in computational biology and medicine.

    PubMed

    Weber, Gerhard-Wilhelm; Ozöğür-Akyüz, Süreyya; Kropat, Erik

    2009-06-01

    An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology. It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetics. Given the data from DNA microarray experiments and environmental measurements, we extract nonlinear ordinary differential equations which contain parameters that are to be determined. This is done by a generalized Chebychev approximation and generalized semi-infinite optimization. Then, time-discretized dynamical systems are studied. By a combinatorial algorithm which constructs and follows polyhedra sequences, the region of parametric stability is detected. In addition, we analyze the topological landscape of gene-environment networks in terms of structural stability. As a second strategy, we will review recent model selection and kernel learning methods for binary classification which can be used to classify microarray data for cancerous cells or for discrimination of other kind of diseases. This review is practically motivated and theoretically elaborated; it is devoted to a contribution to better health care, progress in medicine, a better education, and more healthy living conditions.

  13. Filter design for molecular factor computing using wavelet functions.

    PubMed

    Li, Xiaoyong; Xu, Zhihong; Cai, Wensheng; Shao, Xueguang

    2015-06-23

    Molecular factor computing (MFC) is a new strategy that employs chemometric methods in an optical instrument to obtain analytical results directly using an appropriate filter without data processing. In the present contribution, a method for designing an MFC filter using wavelet functions was proposed for spectroscopic analysis. In this method, the MFC filter is designed as a linear combination of a set of wavelet functions. A multiple linear regression model relating the concentration to the wavelet coefficients is constructed, so that the wavelet coefficients are obtained by projecting the spectra onto the selected wavelet functions. These wavelet functions are selected by optimizing the model using a genetic algorithm (GA). Once the MFC filter is obtained, the concentration of a sample can be calculated directly by projecting the spectrum onto the filter. With three NIR datasets of corn, wheat and blood, it was shown that the performance of the designed filter is better than that of the optimized partial least squares models, and commonly used signal processing methods, such as background correction and variable selection, were not needed. More importantly, the designed filter can be used as an MFC filter in designing MFC-based instruments.

  14. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach

    PubMed Central

    Li, Jun; Zhao, Patrick X.

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/. PMID:27446133

  15. Computational optimization for S-type biological systems: cockroach genetic algorithm.

    PubMed

    Wu, Shinq-Jen; Wu, Cheng-Tao

    2013-10-01

    S-type biological systems (S-systems) are demonstrated to be universal approximations of continuous biological systems. S-systems are easy to be generalized to large systems. The systems are identified through data-driven identification techniques (cluster-based algorithms or computational methods). However, S-systems' identification is challenging because multiple attractors exist in such highly nonlinear systems. Moreover, in some biological systems the interactive effect cannot be neglected even the interaction order is small. Therefore, learning should be focused on increasing the gap between the true and redundant interaction. In addition, a wide searching space is necessary because no prior information is provided. The used technologies should have the ability to achieve convergence enhancement and diversity preservation. Cockroaches live in nearly all habitats and survive for more than 300 million years. In this paper, we mimic cockroaches' competitive swarm behavior and integrated it with advanced evolutionary operations. The proposed cockroach genetic algorithm (CGA) possesses strong snatching-food ability to rush forward to a target and high migration ability to escape from local minimum. CGA was tested with three small-scale systems, a twenty-state medium-scale system and a thirty-state large-scale system. A wide search space ([0,100] for rate constants and [-100,100] for kinetic orders) with random or bad initial starts are used to show the high exploration performance.

  16. Calibrated peer review for computer-assisted learning of biological research competencies.

    PubMed

    Clase, Kari L; Gundlach, Ellen; Pelaez, Nancy J

    2010-09-01

    Recently, both science and technology faculty have been recognizing biological research competencies that are valued but rarely assessed. Some of these valued learning outcomes include scientific methods and thinking, critical assessment of primary papers, quantitative reasoning, communication, and putting biological research into a historical and broader social context. This article presents examples of Calibrated Peer Review (CPR) assignments that illustrate a computer-assisted method to help students achieve biological research competencies. A new release of CPR is appropriate for engaging students online in reading and writing about investigations. A participant perception inventory was designed for use as a repeated measure to discriminate among beginning, middle, and ending student perceptions. Examples are provided to demonstrate how to assess student perceptions of what they gain from instruction related to science research competencies. Results suggest that students in a large enrollment class consider CPR to be useful for helping them learn about quantitative and categorical research variables; the use of the experimental method to test ideas; the use of controls; analysis, interpretation, and presentation of data; and how to critically read primary papers.

  17. Delivering The Benefits of Chemical-Biological Integration in Computational Toxicology at the EPA (ACS Fall meeting)

    EPA Science Inventory

    Abstract: Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intent...

  18. More Ideas for Monitoring Biological Experiments with the BBC Computer: Absorption Spectra, Yeast Growth, Enzyme Reactions and Animal Behaviour.

    ERIC Educational Resources Information Center

    Openshaw, Peter

    1988-01-01

    Presented are five ideas for A-level biology experiments using a laboratory computer interface. Topics investigated include photosynthesis, yeast growth, animal movements, pulse rates, and oxygen consumption and production by organisms. Includes instructions specific to the BBC computer system. (CW)

  19. An introductory course in computation molecular biology: rationale, history, observations, and course description.

    PubMed

    Johns, S J; Thompson, S M; Dunker, A K

    1996-01-01

    A course called "Molecular Biology Computer Techniques" was implemented in 1987 and has been evolving ever since. Currently the semester-long three credit course consists of thirty hours of lecture (three hours/week for the first ten weeks of the semester) and a minimum of 45 hours of laboratory instruction (three hours/week). The lectures survey both bioinformatics and structure based methods. The laboratory has two tracks, one that can be described loosely as "sequence analysis" and the other as "molecular modelling." Most students choose one of the two laboratory tracks, although a small number have done both, either simultaneously or in successive years. For each student, the goal of the course is the completion of a student-initiated research project. The culmination of the course is the presentation of the completed projects at a "Poster Session Final." During this final, which is conducted like a poster session at a typical biological science meeting, students are examined, not only by the instructors in the course, but also by a diverse cross-section of the university community at large, including non-scientists (who are specially invited to attend). Questioning by non-scientists provides opportunity for the students to improve their communication skills with the lay public. In this manuscript we discuss our views regarding the rationale for the development of formal courses in computational molecular biology, relate our experiences in the development of our course, and describe the course as it stood the last time it was taught, which was in the Fall of 1994.

  20. FOREWORD: Third Nordic Symposium on Computer Simulation in Physics, Chemistry, Biology and Mathematics

    NASA Astrophysics Data System (ADS)

    Kaski, K.; Salomaa, M.

    1990-01-01

    These are Proceedings of the Third Nordic Symposium on Computer Simulation in Physics, Chemistry, Biology, and Mathematics, held August 25-26, 1989, at Lahti (Finland). The Symposium belongs to an annual series of Meetings, the first one of which was arranged in 1987 at Lund (Sweden) and the second one in 1988 at Kolle-Kolle near Copenhagen (Denmark). Although these Symposia have thus far been essentially Nordic events, their international character has increased significantly; the trend is vividly reflected through contributions in the present Topical Issue. The interdisciplinary nature of Computational Science is central to the activity; this fundamental aspect is also responsible, in an essential way, for its rapidly increasing impact. Crucially important to a wide spectrum of superficially disparate fields is the common need for extensive - and often quite demanding - computational modelling. For such theoretical models, no closed-form (analytical) solutions are available or they would be extremely difficult to find; hence one must rather resort to the Art of performing computational investigations. Among the unifying features in the computational research are the methods of simulation employed; methods which frequently are quite closely related with each other even for faculties of science that are quite unrelated. Computer simulation in Natural Sciences is presently apprehended as a discipline on its own right, occupying a broad region somewhere between the experimental and theoretical methods, but also partially overlapping with and complementing them. - Whichever its proper definition may be, the computational approach serves as a novel and an extremely versatile tool with which one can equally well perform "pure" experimental modelling and conduct "computational theory". Computational studies that have earlier been made possible only through supercomputers have opened unexpected, as well as exciting, novel frontiers equally in mathematics (e.g., fractals

  1. Functional significance of macrophages in pancreatic cancer biology.

    PubMed

    Hu, Hai; Jiao, Feng; Han, Ting; Wang, Li-Wei

    2015-12-01

    Pancreatic ductal adenocarcinoma (PDA) is a lethal disease that is usually diagnosed at late stage with few effective therapies. Despite the rapid progress on the genomics and proteomics of the neoplastic cells, therapies that targeted the pancreatic cancer cells proved to be inefficient, which promoted the researchers to turn their attentions to the microenvironment. Currently, various studies had proposed the microenvironment to be a contributing factor for PDA and pervasive researches showed that macrophages within the malignancy correlate with the malignant phenotype of the disease and were reported to a new therapeutic target. Generally, the pro-tumoral effects of macrophages can be summarized as angiogenesis promotion, immunosuppression, matrix remodeling and so on. Hence, a comprehensive understanding of the biologic behaviors of macrophages and their critical role in PDA development may provide new directions for the managements of the lethal disease. In this review, we will summarize the recent advancements on macrophages as pivotal players in PDA biology and the current knowledge about anti-macrophages as a novel strategy against cancer, with the expectation that more efficient therapies will be developed in the near future.

  2. Assessing executive function using a computer game: computational modeling of cognitive processes.

    PubMed

    Hagler, Stuart; Jimison, Holly Brugge; Pavel, Misha

    2014-07-01

    Early and reliable detection of cognitive decline is one of the most important challenges of current healthcare. In this project, we developed an approach whereby a frequently played computer game can be used to assess a variety of cognitive processes and estimate the results of the pen-and-paper trail making test (TMT)--known to measure executive function, as well as visual pattern recognition, speed of processing, working memory, and set-switching ability. We developed a computational model of the TMT based on a decomposition of the test into several independent processes, each characterized by a set of parameters that can be estimated from play of a computer game designed to resemble the TMT. An empirical evaluation of the model suggests that it is possible to use the game data to estimate the parameters of the underlying cognitive processes and using the values of the parameters to estimate the TMT performance. Cognitive measures and trends in these measures can be used to identify individuals for further assessment, to provide a mechanism for improving the early detection of neurological problems, and to provide feedback and monitoring for cognitive interventions in the home.

  3. Computer Modeling of Protocellular Functions: Peptide Insertion in Membranes

    NASA Technical Reports Server (NTRS)

    Rodriquez-Gomez, D.; Darve, E.; Pohorille, A.

    2006-01-01

    Lipid vesicles became the precursors to protocells by acquiring the capabilities needed to survive and reproduce. These include transport of ions, nutrients and waste products across cell walls and capture of energy and its conversion into a chemically usable form. In modem organisms these functions are carried out by membrane-bound proteins (about 30% of the genome codes for this kind of proteins). A number of properties of alpha-helical peptides suggest that their associations are excellent candidates for protobiological precursors of proteins. In particular, some simple a-helical peptides can aggregate spontaneously and form functional channels. This process can be described conceptually by a three-step thermodynamic cycle: 1 - folding of helices at the water-membrane interface, 2 - helix insertion into the lipid bilayer and 3 - specific interactions of these helices that result in functional tertiary structures. Although a crucial step, helix insertion has not been adequately studied because of the insolubility and aggregation of hydrophobic peptides. In this work, we use computer simulation methods (Molecular Dynamics) to characterize the energetics of helix insertion and we discuss its importance in an evolutionary context. Specifically, helices could self-assemble only if their interactions were sufficiently strong to compensate the unfavorable Free Energy of insertion of individual helices into membranes, providing a selection mechanism for protobiological evolution.

  4. An Evolutionary Computation Approach to Examine Functional Brain Plasticity

    PubMed Central

    Roy, Arnab; Campbell, Colin; Bernier, Rachel A.; Hillary, Frank G.

    2016-01-01

    One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs) evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC) based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair) such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN) and the executive control network (ECN) during recovery from traumatic brain injury (TBI); the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in the strength

  5. Computational Effective Fault Detection by Means of Signature Functions

    PubMed Central

    Baranski, Przemyslaw; Pietrzak, Piotr

    2016-01-01

    The paper presents a computationally effective method for fault detection. A system’s responses are measured under healthy and ill conditions. These signals are used to calculate so-called signature functions that create a signal space. The current system’s response is projected into this space. The signal location in this space easily allows to determine the fault. No classifier such as a neural network, hidden Markov models, etc. is required. The advantage of this proposed method is its efficiency, as computing projections amount to calculating dot products. Therefore, this method is suitable for real-time embedded systems due to its simplicity and undemanding processing capabilities which permit the use of low-cost hardware and allow rapid implementation. The approach performs well for systems that can be considered linear and stationary. The communication presents an application, whereby an industrial process of moulding is supervised. The machine is composed of forms (dies) whose alignment must be precisely set and maintained during the work. Typically, the process is stopped periodically to manually control the alignment. The applied algorithm allows on-line monitoring of the device by analysing the acceleration signal from a sensor mounted on a die. This enables to detect failures at an early stage thus prolonging the machine’s life. PMID:26949942

  6. Imaging local brain function with emission computed tomography

    SciTech Connect

    Kuhl, D.E.

    1984-03-01

    Positron emission tomography (PET) using /sup 18/F-fluorodeoxyglucose (FDG) was used to map local cerebral glucose utilization in the study of local cerebral function. This information differs fundamentally from structural assessment by means of computed tomography (CT). In normal human volunteers, the FDG scan was used to determine the cerebral metabolic response to conrolled sensory stimulation and the effects of aging. Cerebral metabolic patterns are distinctive among depressed and demented elderly patients. The FDG scan appears normal in the depressed patient, studded with multiple metabolic defects in patients with multiple infarct dementia, and in the patients with Alzheimer disease, metabolism is particularly reduced in the parietal cortex, but only slightly reduced in the caudate and thalamus. The interictal FDG scan effectively detects hypometabolic brain zones that are sites of onset for seizures in patients with partial epilepsy, even though these zones usually appear normal on CT scans. The future prospects of PET are discussed.

  7. Hydrocarbon stapled peptides as modulators of biological function.

    PubMed

    Cromm, Philipp M; Spiegel, Jochen; Grossmann, Tom N

    2015-06-19

    Peptide-based drug discovery has experienced a significant upturn within the past decade since the introduction of chemical modifications and unnatural amino acids has allowed for overcoming some of the drawbacks associated with peptide therapeutics. Strengthened by such features, modified peptides become capable of occupying a niche that emerges between the two major classes of today's therapeutics-small molecules (<500 Da) and biologics (>5000 Da). Stabilized α-helices have proven particularly successful at impairing disease-relevant PPIs previously considered "undruggable." Among those, hydrocarbon stapled α-helical peptides have emerged as a novel class of potential peptide therapeutics. This review provides a comprehensive overview of the development and applications of hydrocarbon stapled peptides discussing the benefits and limitations of this technique.

  8. Chemically-functionalized microcantilevers for detection of chemical, biological and explosive material

    SciTech Connect

    Pinnaduwage, Lal A; Thundat, Thomas G; Brown, Gilbert M; Hawk, John Eric; Boiadjiev, Vassil I

    2007-04-24

    A chemically functionalized cantilever system has a cantilever coated on one side thereof with a reagent or biological species which binds to an analyte. The system is of particular value when the analyte is a toxic chemical biological warfare agent or an explosive.

  9. Beyond Iron: Non-Classical Biological Functions of Bacterial Siderophores

    PubMed Central

    Johnstone, Timothy C.; Nolan, Elizabeth M.

    2015-01-01

    Bacteria secrete small molecules known as siderophores to acquire iron from their surroundings. For over 60 years, investigations into the bioinorganic chemistry of these molecules, including fundamental coordination chemistry studies, have provided insight into the crucial role that siderophores play in bacterial iron homeostasis. The importance of understanding the fundamental chemistry underlying bacterial life has been highlighted evermore in recent years because of the emergence of antibiotic-resistant bacteria and the need to prevent the global rise of these superbugs. Increasing reports of siderophores functioning in capacities other than iron transport have appeared recently, but reports of “non-classical” siderophore functions have long paralleled those of iron transport. One particular non-classical function of these iron chelators, namely antibiotic activity, was even documented before the role of siderophores in iron transport was established. In this Perspective, we present an exposition of past and current work into non-classical functions of siderophores and highlight the directions in which we anticipate that this research is headed. Examples include the ability of siderophores to function as zincophores, chalkophores, and metallophores for a variety of other metals, sequester heavy metal toxins, transport boron, act as signalling molecules, regulate oxidative stress, and provide antibacterial activity. PMID:25764171

  10. Beyond iron: non-classical biological functions of bacterial siderophores.

    PubMed

    Johnstone, Timothy C; Nolan, Elizabeth M

    2015-04-14

    Bacteria secrete small molecules known as siderophores to acquire iron from their surroundings. For over 60 years, investigations into the bioinorganic chemistry of these molecules, including fundamental coordination chemistry studies, have provided insight into the crucial role that siderophores play in bacterial iron homeostasis. The importance of understanding the fundamental chemistry underlying bacterial life has been highlighted evermore in recent years because of the emergence of antibiotic-resistant bacteria and the need to prevent the global rise of these superbugs. Increasing reports of siderophores functioning in capacities other than iron transport have appeared recently, but reports of "non-classical" siderophore functions have long paralleled those of iron transport. One particular non-classical function of these iron chelators, namely antibiotic activity, was documented before the role of siderophores in iron transport was established. In this Perspective, we present an exposition of past and current work into non-classical functions of siderophores and highlight the directions in which we anticipate that this research is headed. Examples include the ability of siderophores to function as zincophores, chalkophores, and metallophores for a variety of other metals, sequester heavy metal toxins, transport boron, act as signalling molecules, regulate oxidative stress, and provide antibacterial activity.

  11. Island biology and ecosystem functioning in epiphytic soil communities.

    PubMed

    Wardle, David A; Yeates, Gregor W; Barker, Gary M; Bellingham, Peter J; Bonner, Karen I; Williamson, Wendy M

    2003-09-19

    Although island attributes such as size and accessibility to colonizing organisms can influence community structure, the consequences of these for ecosystem functioning are little understood. A study of the suspended soils of spatially discrete epiphytes or treetop "islands" in the canopies of New Zealand rainforest trees revealed that different components of the decomposer community responded either positively or negatively to island size, as well as to the tree species that the islands occurred in. This in turn led to important differences between islands in the rates of ecosystem processes driven by the decomposer biota. This system serves as a model for better understanding how attributes of both real and habitat islands may affect key ecosystem functions through determining the community structure of organisms that drive these functions.

  12. Computation of correlation functions and wave function projections in the context of quantum trajectory dynamics.

    PubMed

    Garashchuk, Sophya

    2007-04-21

    The de Broglie-Bohm formulation of the Schrodinger equation implies conservation of the wave function probability density associated with each quantum trajectory in closed systems. This conservation property greatly simplifies numerical implementations of the quantum trajectory dynamics and increases its accuracy. The reconstruction of a wave function, however, becomes expensive or inaccurate as it requires fitting or interpolation procedures. In this paper we present a method of computing wave packet correlation functions and wave function projections, which typically contain all the desired information about dynamics, without the full knowledge of the wave function by making quadratic expansions of the wave function phase and amplitude near each trajectory similar to expansions used in semiclassical methods. Computation of the quantities of interest in this procedure is linear with respect to the number of trajectories. The introduced approximations are consistent with approximate quantum potential dynamics method. The projection technique is applied to model chemical systems and to the H+H(2) exchange reaction in three dimensions.

  13. Novel ESCRT functions in cell biology: spiraling out of control?

    PubMed

    Campsteijn, Coen; Vietri, Marina; Stenmark, Harald

    2016-08-01

    The endosomal sorting complex required for transport (ESCRT), originally identified for its role in endosomal protein sorting and biogenesis of multivesicular endosomes (MVEs), has proven to be a versatile machinery for involution and scission of narrow membrane invaginations filled with cytosol. Budding of enveloped viruses and cytokinetic abscission were early described functions for the ESCRT machinery, and recently a number of new ESCRT functions have emerged. These include cytokinetic abscission checkpoint control, plasma membrane repair, exovesicle release, quality control of nuclear pore complexes, neuron pruning, and sealing of the newly formed nuclear envelope. Here we review these novel ESCRT mechanisms and discuss similarities and differences between the various ESCRT-dependent activities.

  14. Does Sequence Conservation Provide Evidence for Biological Function?

    PubMed

    Omer, Seila; Harlow, Timothy J; Gogarten, Johann Peter

    2017-01-01

    Finding a signature of purifying selection in a gene is usually interpreted as evidence for the gene providing a function that is targeted by natural selection. This opinion offers a very different hypothesis: purifying selection may be due to removing harmful mutations from the population, that is, the gene and its encoded protein become harmful after a mutation occurred, possibly because the mutated protein interferes with the translation machinery, or because of toxicity of the misfolded protein. Finding a signature of purifying selection should not automatically be considered proof of the gene's selectable function.

  15. Chaste: An Open Source C++ Library for Computational Physiology and Biology

    PubMed Central

    Mirams, Gary R.; Arthurs, Christopher J.; Bernabeu, Miguel O.; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G.; Harvey, Daniel G.; Marsh, Megan E.; Osborne, James M.; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J.

    2013-01-01

    Chaste — Cancer, Heart And Soft Tissue Environment — is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to ‘re-invent the wheel’ with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials. PMID:23516352

  16. Exosome function: from tumor immunology to pathogen biology.

    PubMed

    Schorey, Jeffrey S; Bhatnagar, Sanchita

    2008-06-01

    Exosomes are the newest family member of 'bioactive vesicles' that function to promote intercellular communication. Exosomes are derived from the fusion of multivesicular bodies with the plasma membrane and extracellular release of the intraluminal vesicles. Recent studies have focused on the biogenesis and composition of exosomes as well as regulation of exosome release. Exosomes have been shown to be released by cells of hematopoietic and non-hematopoietic origin, yet their function remains enigmatic. Much of the prior work has focused on exosomes as a source of tumor antigens and in presentation of tumor antigens to T cells. However, new studies have shown that exosomes might also promote cell-to-cell spread of infectious agents. Moreover, exosomes isolated from cells infected with various intracellular pathogens, including Mycobacterium tuberculosis and Toxoplasma gondii, have been shown to contain microbial components and can promote antigen presentation and macrophage activation, suggesting that exosomes may function in immune surveillance. In this review, we summarize our understanding of exosome biogenesis but focus primarily on new insights into exosome function. We also discuss their possible use as disease biomarkers and vaccine candidates.

  17. Scalable Computational Methods for the Analysis of High-Throughput Biological Data

    SciTech Connect

    Langston, Michael A

    2012-09-06

    This primary focus of this research project is elucidating genetic regulatory mechanisms that control an organism's responses to low-dose ionizing radiation. Although low doses (at most ten centigrays) are not lethal to humans, they elicit a highly complex physiological response, with the ultimate outcome in terms of risk to human health unknown. The tools of molecular biology and computational science will be harnessed to study coordinated changes in gene expression that orchestrate the mechanisms a cell uses to manage the radiation stimulus. High performance implementations of novel algorithms that exploit the principles of fixed-parameter tractability will be used to extract gene sets suggestive of co-regulation. Genomic mining will be performed to scrutinize, winnow and highlight the most promising gene sets for more detailed investigation. The overall goal is to increase our understanding of the health risks associated with exposures to low levels of radiation.

  18. Micro-computed tomography imaging and analysis in developmental biology and toxicology.

    PubMed

    Wise, L David; Winkelmann, Christopher T; Dogdas, Belma; Bagchi, Ansuman

    2013-06-01

    Micro-computed tomography (micro-CT) is a high resolution imaging technique that has expanded and strengthened in use since it was last reviewed in this journal in 2004. The technology has expanded to include more detailed analysis of bone, as well as soft tissues, by use of various contrast agents. It is increasingly applied to questions in developmental biology and developmental toxicology. Relatively high-throughput protocols now provide a powerful and efficient means to evaluate embryos and fetuses subjected to genetic manipulations or chemical exposures. This review provides an overview of the technology, including scanning, reconstruction, visualization, segmentation, and analysis of micro-CT generated images. This is followed by a review of more recent applications of the technology in some common laboratory species that highlight the diverse issues that can be addressed.

  19. Experimental and computer modelling of vibrational spectra of heterogenous complexes of biological macromolecules

    NASA Astrophysics Data System (ADS)

    Belokour, Ye. L.; Dovbeshko, G. I.; Litvinov, G. S.

    1992-03-01

    Comparative analysis of experimental vibrational (5000-400 cm -1) spectra of nucleoproteins with different ratio between protein and nucleic acid was fulfilled. The spectra of DNA and RNA viruses (bacteriophages T4, Cg, λ E. coli spp, tobacco mosaic, carnation mottle, potatoe X and Y viruses, densonucleosis virus, enthomoiridoviruses) and model protein-DNA mixtures with relative content from 1:1 to 20:1 were investigated. Calculated spectra were obtained by computer summarring up of molecule component spectra. The differences between the vibrational spectra of the investigated viruses are determined by the protein/nucleic acid ratio as well as by their biological nature. It has been established that Amide 1,.Amide 2 - bands (1700-1500 cm -1) and bands corresponding to the stretching and assymetric nucleic acid phosphodiether bond vibrations (1000-1300cm -1) may be used to determine the content of protein and nucleic acid in nucleoproteins.

  20. Physical and Computational Modeling for Chemical and Biological Weapons Airflow Applications

    SciTech Connect

    McEligot, Donald Marinus; Mc Creery, Glenn Ernest; Pink, Robert John; Barringer, C.; Knight, K. J.

    2002-11-01

    There is a need for information on dispersion and infiltration of chemical and biological agents in complex building environments. A recent collaborative study conducted at the Idaho National Engineering and Environmental Laboratory (INEEL) and Bechtel Corporation Research and Development had the objective of assessing computational fluid dynamics (CFD) models for simulation of flow around complicated buildings through a comparison of experimental and numerical results. The test facility used in the experiments was INEEL’s unique large Matched-Index-of-Refraction (MIR) flow system. The CFD code used for modeling was Fluent, a widely available commercial flow simulation package. For the experiment, a building plan was selected to approximately represent an existing facility. It was found that predicted velocity profiles from above the building and in front of the building were in good agreement with the measurements.

  1. Motion as a source of environmental information: a fresh view on biological motion computation by insect brains

    PubMed Central

    Egelhaaf, Martin; Kern, Roland; Lindemann, Jens Peter

    2014-01-01

    Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around (“optic flow”) to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and—in many behavioral contexts—less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism. PMID:25389392

  2. Computing black hole partition functions from quasinormal modes

    SciTech Connect

    Arnold, Peter; Szepietowski, Phillip; Vaman, Diana

    2016-07-07

    We propose a method of computing one-loop determinants in black hole space-times (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A numerical evaluation must face the fact that the sum over the quasinormal modes, indexed by momentum and overtone numbers, is divergent. A necessary ingredient is then a regularization scheme to handle the divergent contributions of individual fixed-momentum sectors to the partition function. To this end, we formulate an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. Furthermore, we then discuss the application of such techniques to more complicated spacetimes.

  3. Computing black hole partition functions from quasinormal modes

    DOE PAGES

    Arnold, Peter; Szepietowski, Phillip; Vaman, Diana

    2016-07-07

    We propose a method of computing one-loop determinants in black hole space-times (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A numerical evaluation must face the fact that the sum over the quasinormal modes, indexed by momentum and overtone numbers, is divergent. A necessary ingredient is then a regularization scheme to handle the divergent contributions of individual fixed-momentum sectors to the partition function. To this end, we formulatemore » an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. Furthermore, we then discuss the application of such techniques to more complicated spacetimes.« less

  4. Chemical Visualization of Boolean Functions: A Simple Chemical Computer

    NASA Astrophysics Data System (ADS)

    Blittersdorf, R.; Müller, J.; Schneider, F. W.

    1995-08-01

    We present a chemical realization of the Boolean functions AND, OR, NAND, and NOR with a neutralization reaction carried out in three coupled continuous flow stirred tank reactors (CSTR). Two of these CSTR's are used as input reactors, the third reactor marks the output. The chemical reaction is the neutralization of hydrochloric acid (HCl) with sodium hydroxide (NaOH) in the presence of phenolphtalein as an indicator, which is red in alkaline solutions and colorless in acidic solutions representing the two binary states 1 and 0, respectively. The time required for a "chemical computation" is determined by the flow rate of reactant solutions into the reactors since the neutralization reaction itself is very fast. While the acid flow to all reactors is equal and constant, the flow rate of NaOH solution controls the states of the input reactors. The connectivities between the input and output reactors determine the flow rate of NaOH solution into the output reactor, according to the chosen Boolean function. Thus the state of the output reactor depends on the states of the input reactors.

  5. A computer vision based candidate for functional balance test.

    PubMed

    Nalci, Alican; Khodamoradi, Alireza; Balkan, Ozgur; Nahab, Fatta; Garudadri, Harinath

    2015-08-01

    Balance in humans is a motor skill based on complex multimodal sensing, processing and control. Ability to maintain balance in activities of daily living (ADL) is compromised due to aging, diseases, injuries and environmental factors. Center for Disease Control and Prevention (CDC) estimate of the costs of falls among older adults was $34 billion in 2013 and is expected to reach $54.9 billion in 2020. In this paper, we present a brief review of balance impairments followed by subjective and objective tools currently used in clinical settings for human balance assessment. We propose a novel computer vision (CV) based approach as a candidate for functional balance test. The test will take less than a minute to administer and expected to be objective, repeatable and highly discriminative in quantifying ability to maintain posture and balance. We present an informal study with preliminary data from 10 healthy volunteers, and compare performance with a balance assessment system called BTrackS Balance Assessment Board. Our results show high degree of correlation with BTrackS. The proposed system promises to be a good candidate for objective functional balance tests and warrants further investigations to assess validity in clinical settings, including acute care, long term care and assisted living care facilities. Our long term goals include non-intrusive approaches to assess balance competence during ADL in independent living environments.

  6. Computing black hole partition functions from quasinormal modes

    NASA Astrophysics Data System (ADS)

    Arnold, Peter; Szepietowski, Phillip; Vaman, Diana

    2016-07-01

    We propose a method of computing one-loop determinants in black hole space-times (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A numerical evaluation must face the fact that the sum over the quasinormal modes, indexed by momentum and overtone numbers, is divergent. A necessary ingredient is then a regularization scheme to handle the divergent contributions of individual fixed-momentum sectors to the partition function. To this end, we formulate an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. We then discuss the application of such techniques to more complicated spacetimes.

  7. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models

    PubMed Central

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article: WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.1270 PMID:24810243

  8. Tools for building a comprehensive modeling system for virtual screening under real biological conditions: The Computational Titration algorithm.

    PubMed

    Kellogg, Glen E; Fornabaio, Micaela; Chen, Deliang L; Abraham, Donald J; Spyrakis, Francesca; Cozzini, Pietro; Mozzarelli, Andrea

    2006-05-01

    Computational tools utilizing a unique empirical modeling system based on the hydrophobic effect and the measurement of logP(o/w) (the partition coefficient for solvent transfer between 1-octanol and water) are described. The associated force field, Hydropathic INTeractions (HINT), contains much rich information about non-covalent interactions in the biological environment because of its basis in an experiment that measures interactions in solution. HINT is shown to be the core of an evolving virtual screening system that is capable of taking into account a number of factors often ignored such as entropy, effects of solvent molecules at the active site, and the ionization states of acidic and basic residues and ligand functional groups. The outline of a comprehensive modeling system for virtual screening that incorporates these features is described. In addition, a detailed description of the Computational Titration algorithm is provided. As an example, three complexes of dihydrofolate reductase (DHFR) are analyzed with our system and these results are compared with the experimental free energies of binding.

  9. Social inclusion enhances biological motion processing: a functional near-infrared spectroscopy study.

    PubMed

    Bolling, Danielle Z; Pelphrey, Kevin A; Kaiser, Martha D

    2013-04-01

    Humans are especially tuned to the movements of other people. Neural correlates of this social attunement have been proposed to lie in and around the right posterior superior temporal sulcus (STS) region, which robustly responds to biological motion in contrast to a variety of non-biological motions. This response persists even when no form information is provided, as in point-light displays (PLDs). The aim of the current study was to assess the ability of functional near-infrared spectroscopy (fNIRS) to reliably measure brain responses to PLDs of biological motion, and determine the sensitivity of these responses to interpersonal contextual factors. To establish reliability, we measured brain activation to biological motion with fNIRS and functional magnetic resonance imaging (fMRI) during two separate sessions in an identical group of 12 participants. To establish sensitivity, brain responses to biological motion measured with fNIRS were subjected to an additional social manipulation where participants were either socially included or excluded before viewing PLDs of biological motion. Results revealed comparable brain responses to biological motion using fMRI and fNIRS in the right supramarginal gyrus. Further, social inclusion increased brain responses to biological motion in right supramarginal gyrus and posterior STS. Thus, fNIRS can reliably measure brain responses to biological motion and can detect social experience-dependent modulations of these brain responses.

  10. Structure, Biological Functions and Applications of the AB5 Toxins

    PubMed Central

    Beddoe, Travis; Paton, Adrienne W.; Le Nours, Jérôme; Rossjohn, Jamie; Paton, James C.

    2010-01-01

    AB5 toxins are important virulence factors for several major bacterial pathogens, including Bordetella pertussis, Vibrio cholerae, Shigella dysenteriae and at least two distinct pathotypes of Escherichia coli. The AB5 toxins are so termed because they comprise a catalytic A-subunit, which is responsible for disruption of essential host functions, and a pentameric B-subunit that binds to specific glycan receptors on the target cell surface. The molecular mechanisms by which these AB5 toxins cause disease have been largely unraveled, including recent insights into a novel AB5 toxin family, subtilase cytotoxin (SubAB). Furthermore, AB5 toxins have become a valuable tool for studying fundamental cellular functions, and are now being investigated for potential applications in the clinical treatment of human diseases. PMID:20202851

  11. Functional Nanostructured Platforms for Chemical and Biological Sensing

    SciTech Connect

    Letant, S E

    2006-03-20

    The central goal of our work is to combine semiconductor nanotechnology and surface functionalization in order to build platforms for the selective detection of bio-organisms ranging in size from bacteria (micron range) down to viruses, as well as for the detection of chemical agents (nanometer range). We will show on three porous silicon platforms how pore geometry and pore wall chemistry can be combined and optimized to capture and detect specific targets. We developed a synthetic route allowing to directly anchor proteins on silicon surfaces and illustrated the relevance of this technique by immobilizing live enzymes onto electrochemically etched luminescent nano-porous silicon. The powerful association of the specific enzymes with the transducing matrix led to a selective hybrid platform for chemical sensing. We also used light-assisted electrochemistry to produce periodic arrays of through pores on pre-patterned silicon membranes with controlled diameters ranging from many microns down to tens of nanometers. We demonstrated the first covalently functionalized silicon membranes and illustrated their selective capture abilities with antibody-coated micro-beads. These engineered membranes are extremely versatile and could be adapted to specifically recognize the external fingerprints (size and coat composition) of target bio-organisms. Finally, we fabricated locally functionalized single nanopores using a combination of focused ion beam drilling and ion beam assisted oxide deposition. We showed how a silicon oxide ring can be grown around a single nanopore and how it can be functionalized with DNA probes to detect single viral-sized beads. The next step for this platform is the detection of whole viruses and bacteria.

  12. Biology and Function of Fetal and Pediatric Skin

    PubMed Central

    Leung, Alice; Balaji, Swathi; Keswani, Sundeep G

    2013-01-01

    Synopsis The development of the integumentary system is a series of events, which start in utero and continue throughout life. Although at birth, skin in full-term infants is anatomically mature, functional maturity develops during the first year of life. Pediatric skin transitions again with the onset of puberty. At each stage, there are changes in transepidermal water loss, skin hydration, and skin acidity that define the specific period of development. PMID:23369584

  13. Functional nanostructured platforms for chemical and biological sensing

    NASA Astrophysics Data System (ADS)

    Létant, S. E.

    2006-05-01

    The central goal of our work is to combine semiconductor nanotechnology and surface functionalization in order to build platforms for the selective detection of bio-organisms ranging in size from bacteria (micron range) down to viruses, as well as for the detection of chemical agents (nanometer range). We will show on three porous silicon platforms how pore geometry and pore wall chemistry can be combined and optimized to capture and detect specific targets. We developed a synthetic route allowing to directly anchor proteins on silicon surfaces and illustrated the relevance of this technique by immobilizing live enzymes onto electrochemically etched luminescent nano-porous silicon. The powerful association of the specific enzymes with the transducing matrix led to a selective hybrid platform for chemical sensing. We also used light-assisted electrochemistry to produce periodic arrays of through pores on pre-patterned silicon membranes with controlled diameters ranging from many microns down to tens of nanometers. We demonstrated the first covalently functionalized silicon membranes and illustrated their selective capture abilities with antibody-coated micro-beads. These engineered membranes are extremely versatile and could be adapted to specifically recognize the external fingerprints (size and coat composition) of target bio-organisms. Finally, we fabricated locally functionalized single nanopores using a combination of focused ion beam drilling and ion beam assisted oxide deposition. We showed how a silicon oxide ring can be grown around a single nanopore and how it can be functionalized with DNA probes to detect single viral-sized beads. The next step for this platform is the detection of whole viruses and bacteria.

  14. STRIPAK complexes: structure, biological function, and involvement in human diseases.

    PubMed

    Hwang, Juyeon; Pallas, David C

    2014-02-01

    The mammalian striatin family consists of three proteins, striatin, S/G2 nuclear autoantigen, and zinedin. Striatin family members have no intrinsic catalytic activity, but rather function as scaffolding proteins. Remarkably, they organize multiple diverse, large signaling complexes that participate in a variety of cellular processes. Moreover, they appear to be regulatory/targeting subunits for the major eukaryotic serine/threonine protein phosphatase 2A. In addition, striatin family members associate with germinal center kinase III kinases as well as other novel components, earning these assemblies the name striatin-interacting phosphatase and kinase (STRIPAK) complexes. Recently, there has been a great increase in functional and mechanistic studies aimed at identifying and understanding the roles of STRIPAK and STRIPAK-like complexes in cellular processes of multiple organisms. These studies have identified novel STRIPAK and STRIPAK-like complexes and have explored their roles in specific signaling pathways. Together, the results of these studies have sparked increased interest in striatin family complexes because they have revealed roles in signaling, cell cycle control, apoptosis, vesicular trafficking, Golgi assembly, cell polarity, cell migration, neural and vascular development, and cardiac function. Moreover, STRIPAK complexes have been connected to clinical conditions, including cardiac disease, diabetes, autism, and cerebral cavernous malformation. In this review, we discuss the expression, localization, and protein domain structure of striatin family members. Then we consider the diverse complexes these proteins and their homologs form in various organisms, emphasizing what is known regarding function and regulation. Finally, we explore possible roles of striatin family complexes in disease, especially cerebral cavernous malformation.

  15. Hidden Markov models and other machine learning approaches in computational molecular biology

    SciTech Connect

    Baldi, P.

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In this tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.

  16. Systems biology in psychiatric research: from complex data sets over wiring diagrams to computer simulations.

    PubMed

    Tretter, Felix; Gebicke-Haerter, Peter J

    2012-01-01

    The classification of psychiatric disorders has always been a problem in clinical settings. The present debate about the major systems in clinical practice, DSM-IV and ICD-10, has resulted in attempts to improve and replace those schemes by some that include more endophenotypic and molecular features. However, these disorders not only require more precise diagnostic tools, but also have to be viewed more extensively in their dynamic behaviors, which require more precise data sets related to their origins and developments. This enormous challenge in brain research has to be approached on different levels of the biological system by new methods, including improvements in electroencephalography, brain imaging, and molecular biology. All these methods entail accumulations of large data sets that become more and more difficult to interpret. In particular, on the molecular level, there is an apparent need to use highly sophisticated computer programs to tackle these problems. Evidently, only interdisciplinary work among mathematicians, physicists, biologists, and clinicians can further improve our understanding of complex diseases of the brain.

  17. Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications.

    PubMed

    Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Maudsley, Stuart

    2013-01-01

    Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

  18. [Study on action mechanism of Danhong injection based on computational system biology approach].

    PubMed

    Lv, Yan-ni; Wei, Xiao-hua; Xiao, Pin

    2015-02-01

    Danhong injection is a compound preparation of traditional Chinese medicine Salvia miltiorrhiza and Carthamus tinctorius, and has been widely applied in treating coronary heart diseases and ischemic encephalopathy in clinic. Despite the complexity of its chemical compounds and the diversity of targets, especially in system biology, there have not a report for its action mechanism as a whole regulatory biological network. In this study, protein data of S. miltiorrhiza and C. tinctorius were searched in TCMGeneDIT database and agilent literature search (ALS) system to establish the multi-component protein network of S. miltiorrhiza, C. tinctorius and Danhong injection. Besides, the protein interaction network was built based on the protein-protein interaction in Genecards, BIND, BioGRID, IntAct, MINT and other databases. According to the findings, 10 compounds of S. miltiorrhiza and 14 compounds of C. tinctorius were correlated with proteins. The 24 common compounds had interactions with 81 proteins, and formed a protein interaction network with 60 none-isolated nodes. The Cluster ONE module was applied to make an enrichment analysis on the protein interaction network and extract one sub-network with significant difference P <0.05. The sub-network contains 23 key proteins, which involved five signaling pathways, namely Nod-like receptor signaling pathway, epithelial cell signaling in helicobacter pylori infection, Toll-like receptor signaling pathway, RIG-I-like receptor signaling pathway and neurotrophin signaling pathway through KEGG signaling pathway mapping. In this study, the computational system biology approach was adopted to preliminarily explain the molecular mechanism of main compounds of Danhong injection in preventing and treating diseases and provide reference for systematic studies on traditional Chinese medicine compounds.

  19. Discovering and validating biological hypotheses from coherent patterns in functional genomics data

    SciTech Connect

    Joachimiak, Marcin Pawel

    2008-08-12

    The area of transcriptomics analysis is among the more established in computational biology, having evolved in both technology and experimental design. Transcriptomics has a strong impetus to develop sophisticated computational methods due to the large amounts of available whole-genome datasets for many species and because of powerful applications in regulatory network reconstruction as well as elucidation and modeling of cellular transcriptional responses. While gene expression microarray data can be noisy and comparisons across experiments challenging, there are a number of sophisticated methods that aid in arriving at statistically and biologically significant conclusions. As such, computational transcriptomics analysis can provide guidance for analysis of results from newer experimental technologies. More recently, search methods have been developed to identify modules of genes, which exhibit coherent expression patterns in only a subset of experimental conditions. The latest advances in these methods allow to integrate multiple data types anddatasets, both experimental and computational, within a single statistical framework accounting for data confidence and relevance to specific biological questions. Such frameworks provide a unified environment for the exploration of specific biological hypothesis and for the discovery of coherent data patterns along with the evidence supporting them.

  20. High performance computing approaches for 3D reconstruction of complex biological specimens.

    PubMed

    da Silva, M Laura; Roca-Piera, Javier; Fernández, José-Jesús

    2010-01-01

    Knowledge of the structure of specimens is crucial to determine the role that they play in cellular and molecular biology. To yield the three-dimensional (3D) reconstruction by means of tomographic reconstruction algorithms, we need the use of large projection images and high processing time. Therefore, we propose the use of the high performance computing (HPC) to cope with the huge computational demands of this problem. We have implemented a HPC strategy where the distribution of tasks follows the master-slave paradigm. The master processor distributes a slab of slices, a piece of the final 3D structure to reconstruct, among the slave processors and receives reconstructed slices of the volume. We have evaluated the performance of our HPC approach using different sizes of the slab. We have observed that it is possible to find out an optimal size of the slab for the number of processor used that minimize communications time while maintaining a reasonable grain of parallelism to be exploited by the set of processors.