Science.gov

Sample records for computing biological functions

  1. 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. PMID:22492746

  2. 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

  3. 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

  4. Synthetic biology: insights into biological computation.

    PubMed

    Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

    2016-04-18

    Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and

  5. 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

  6. Integrating cell biology, image analysis, and computational mechanical modeling to analyze the contributions of cellulose and xyloglucan to stomatal function.

    PubMed

    Rui, Yue; Yi, Hojae; Kandemir, Baris; Wang, James Z; Puri, Virendra M; Anderson, Charles T

    2016-06-01

    Cell walls are likely to be essential determinants of the amazing strength and flexibility of the guard cells that surround each stomatal pore in plants, but surprisingly little is known about cell wall composition, organization, and dynamics in guard cells. Recent analyses of cell wall organization and stomatal function in the guard cells of Arabidopsis thaliana mutants with defects in cellulose and xyloglucan have allowed for the development of new hypotheses about the relative contributions of these components to guard cell function. Advanced image analysis methods can allow for the automated detection of key structures, such as microtubules (MTs) and Cellulose Synthesis Complexes (CSCs), in guard cells, to help determine their contributions to stomatal function. A major challenge in the mechanical modeling of dynamic biological structures, such as guard cell walls, is to connect nanoscale features (e.g., wall polymers and their molecular interactions) with cell-scale mechanics; this challenge can be addressed by applying multiscale computational modeling that spans multiple spatial scales and physical attributes for cell walls. PMID:27220916

  7. 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.

  8. 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.

  9. 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

  10. Computational representation of biological systems

    SciTech Connect

    Frazier, Zach; McDermott, Jason E.; Guerquin, Michal; Samudrala, Ram

    2009-04-20

    Integration of large and diverse biological data sets is a daunting problem facing systems biology researchers. Exploring the complex issues of data validation, integration, and representation, we present a systematic approach for the management and analysis of large biological data sets based on data warehouses. Our system has been implemented in the Bioverse, a framework combining diverse protein information from a variety of knowledge areas such as molecular interactions, pathway localization, protein structure, and protein function.

  11. 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

  12. 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…

  13. 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

  14. Deep learning for computational biology.

    PubMed

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

    2016-01-01

    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. PMID:27474269

  15. 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

  16. Computational Biology, Advanced Scientific Computing, and Emerging Computational Architectures

    SciTech Connect

    2007-06-27

    This CRADA was established at the start of FY02 with $200 K from IBM and matching funds from DOE to support post-doctoral fellows in collaborative research between International Business Machines and Oak Ridge National Laboratory to explore effective use of emerging petascale computational architectures for the solution of computational biology problems. 'No cost' extensions of the CRADA were negotiated with IBM for FY03 and FY04.

  17. 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. PMID:26449352

  18. 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)

  19. 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.

  20. 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

  1. 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)

  2. The applications of computers in biological research

    NASA Technical Reports Server (NTRS)

    Wei, Jennifer

    1988-01-01

    Research in many fields could not be done without computers. There is often a great deal of technical data, even in the biological fields, that need to be analyzed. These data, unfortunately, previously absorbed much of every researcher's time. Now, due to the steady increase in computer technology, biological researchers are able to make incredible advances in their work without the added worries of tedious and difficult tasks such as the many mathematical calculations involved in today's research and health care.

  3. Computational investigations of HNO in biology

    PubMed Central

    Zhang, Yong

    2013-01-01

    HNO (nitroxyl) has been found to have many physiological effects in numerous biological processes. Computational investigations have been employed to help understand the structural properties of HNO complexes and HNO reactivities in some interesting biologically relevant systems. The following computational aspects were reviewed in this work: 1) structural and energetic properties of HNO isomers; 2) interactions between HNO and non-metal molecules; 3) structural and spectroscopic properties of HNO metal complexes; 4) HNO reactions with biologically important non-metal systems; 5) involvement of HNO in reactions of metal complexes and metalloproteins. Results indicate that computational investigations are very helpful to elucidate interesting experimental phenomena and provide new insights into unique structural, spectroscopic, and mechanistic properties of HNO involvement in biology. PMID:23103077

  4. 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. PMID:25790483

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

    PubMed Central

    Fong, Stephen S.

    2014-01-01

    Metabolic engineering modifies cellular function to address various biochemical applications. Underlying metabolic engineering efforts are a host of tools and knowledge that are integrated to enable successful outcomes. Concurrent development of computational and experimental tools has enabled different approaches to metabolic engineering. One approach is to leverage knowledge and computational tools to prospectively predict designs to achieve the desired outcome. An alternative approach is to utilize combinatorial experimental tools to empirically explore the range of cellular function and to screen for desired traits. This mini-review focuses on computational systems biology and synthetic biology tools that can be used in combination for prospective in silico strain design. PMID:25379141

  6. 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

  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. 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.

  9. 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. PMID:27465042

  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. 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…

  13. Computational Biology and Bioinformatics in Nigeria

    PubMed Central

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

    2014-01-01

    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. PMID:24763310

  14. 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.

  15. 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. PMID:22711873

  16. 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

  17. 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. PMID:24921255

  18. 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

  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. PMID:14577383

  20. Biology under construction: in vitro reconstitution of cellular function

    PubMed Central

    Liu, Allen P.; Fletcher, Daniel A.

    2010-01-01

    We are much better at taking cells apart than putting them together. Reconstitution of biological processes from component molecules has been a powerful but difficult approach to studying functional organization in biology. Recently, the convergence of biochemical and cell biological advances with new experimental and computational tools is providing the opportunity to reconstitute increasingly complex processes. We predict that this bottom-up strategy will uncover basic processes that guide cellular assembly, advancing both basic and applied sciences. PMID:19672276

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Software agents in molecular computational biology.

    PubMed

    Keele, John W; Wray, James E

    2005-12-01

    Progress made in applying agent systems to molecular computational biology is reviewed and strategies by which to exploit agent technology to greater advantage are investigated. Communities of software agents could play an important role in helping genome scientists design reagents for future research. The advent of genome sequencing in cattle and swine increases the complexity of data analysis required to conduct research in livestock genomics. Databases are always expanding and semantic differences among data are common. Agent platforms have been developed to deal with generic issues such as agent communication, life cycle management and advertisement of services (white and yellow pages). This frees computational biologists from the drudgery of having to re-invent the wheel on these common chores, giving them more time to focus on biology and bioinformatics. Agent platforms that comply with the Foundation for Intelligent Physical Agents (FIPA) standards are able to interoperate. In other words, agents developed on different platforms can communicate and cooperate with one another if domain-specific higher-level communication protocol details are agreed upon between different agent developers. Many software agent platforms are peer-to-peer, which means that even if some of the agents and data repositories are temporarily unavailable, a subset of the goals of the system can still be met. Past use of software agents in bioinformatics indicates that an agent approach should prove fruitful. Examination of current problems in bioinformatics indicates that existing agent platforms should be adaptable to novel situations. PMID:16420735

  6. 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

  7. 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…

  8. Computational design of digital and memory biological devices.

    PubMed

    Rodrigo, Guillermo; Jaramillo, Alfonso

    2007-12-01

    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. PMID:19003443

  9. Toward Computational Cumulative Biology by Combining Models of Biological Datasets

    PubMed Central

    Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

    2014-01-01

    A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations—for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database. PMID:25427176

  10. 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.

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

    PubMed

    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. PMID:27494095

  12. Computational Laser Spectroscopy in a Biological Tissue

    PubMed Central

    Gantri, M.; Trabelsi, H.; Sediki, E.; Ben Salah, R.

    2010-01-01

    We present a numerical spectroscopic study of visible and infrared laser radiation in a biological tissue. We derive a solution of a general two-dimensional time dependent radiative transfer equation in a tissue-like medium. The used model is suitable for many situations especially when the external source is time-dependent or continuous. We use a control volume-discrete ordinate method associated with an implicit three-level second-order time differencing scheme. We consider a very thin rectangular biological-tissue-like medium submitted to a visible or a near infrared light sources. The RTE is solved for a set of different wavelength source. All sources are assumed to be monochromatic and collimated. The energetic fluence rate is computed at a set of detector points on the boundaries. According to the source type, we investigate either the steady-state or transient response of the medium. The used model is validated in the case of a heterogeneous tissue-like medium using referencing experimental results from the literature. Also, the developed model is used to study changes on transmitted light in a rat-liver tissue-like medium. Optical properties depend on the source wavelength and they are taken from the literature. In particular, light-transmission in the medium is studied for continuous wave and for short pulse. PMID:20396377

  13. Strategies for Introducing Computer Technologies into a Biology Laboratory Program

    ERIC Educational Resources Information Center

    Tillotson, Joanne Kivela

    2002-01-01

    Computers have been installed in the General Biology laboratory at Purchase College and incorporated into the laboratory curriculum for all biology majors at the introductory level. The goal is to ensure that all students become familiar with general computer applications in the biological sciences and are comfortable enough to use them regularly.…

  14. 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)

  15. 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…

  16. Functional Translational Readthrough: A Systems Biology Perspective.

    PubMed

    Schueren, Fabian; Thoms, Sven

    2016-08-01

    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

  17. 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

  18. Structural biology computing: Lessons for the biomedical research sciences.

    PubMed

    Morin, Andrew; Sliz, Piotr

    2013-11-01

    The field of structural biology, whose aim is to elucidate the molecular and atomic structures of biological macromolecules, has long been at the forefront of biomedical sciences in adopting and developing computational research methods. Operating at the intersection between biophysics, biochemistry, and molecular biology, structural biology's growth into a foundational framework on which many concepts and findings of molecular biology are interpreted1 has depended largely on parallel advancements in computational tools and techniques. Without these computing advances, modern structural biology would likely have remained an exclusive pursuit practiced by few, and not become the widely practiced, foundational field it is today. As other areas of biomedical research increasingly embrace research computing techniques, the successes, failures and lessons of structural biology computing can serve as a useful guide to progress in other biomedically related research fields. PMID:23828134

  19. 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. PMID:23451897

  20. Aluminium in Biological Environments: A Computational Approach

    PubMed Central

    Mujika, Jon I; Rezabal, Elixabete; Mercero, Jose M; Ruipérez, Fernando; Costa, Dominique; Ugalde, Jesus M; Lopez, Xabier

    2014-01-01

    The increased availability of aluminium in biological environments, due to human intervention in the last century, raises concerns on the effects that this so far “excluded from biology” metal might have on living organisms. Consequently, the bioinorganic chemistry of aluminium has emerged as a very active field of research. This review will focus on our contributions to this field, based on computational studies that can yield an understanding of the aluminum biochemistry at a molecular level. Aluminium can interact and be stabilized in biological environments by complexing with both low molecular mass chelants and high molecular mass peptides. The speciation of the metal is, nonetheless, dictated by the hydrolytic species dominant in each case and which vary according to the pH condition of the medium. In blood, citrate and serum transferrin are identified as the main low molecular mass and high molecular mass molecules interacting with aluminium. The complexation of aluminium to citrate and the subsequent changes exerted on the deprotonation pathways of its tritable groups will be discussed along with the mechanisms for the intake and release of aluminium in serum transferrin at two pH conditions, physiological neutral and endosomatic acidic. Aluminium can substitute other metals, in particular magnesium, in protein buried sites and trigger conformational disorder and alteration of the protonation states of the protein's sidechains. A detailed account of the interaction of aluminium with proteic sidechains will be given. Finally, it will be described how alumnium can exert oxidative stress by stabilizing superoxide radicals either as mononuclear aluminium or clustered in boehmite. The possibility of promotion of Fenton reaction, and production of hydroxyl radicals will also be discussed. PMID:24757505

  1. 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…

  2. Biologically inspired path to quantum computer

    NASA Astrophysics Data System (ADS)

    Ogryzko, Vasily; Ozhigov, Yuri

    2014-12-01

    We describe an approach to quantum computer inspired by the information processing at the molecular level in living cells. It is based on the separation of a small ensemble of qubits inside the living system (e.g., a bacterial cell), such that coherent quantum states of this ensemble remain practically unchanged for a long time. We use the notion of a quantum kernel to describe such an ensemble. Quantum kernel is not strictly connected with certain particles; it permanently exchanges atoms and molecules with the environment, which makes quantum kernel a virtual notion. There are many reasons to expect that the state of quantum kernel of a living system can be treated as the stationary state of some Hamiltonian. While the quantum kernel is responsible for the stability of dynamics at the time scale of cellular life, at the longer inter-generation time scale it can change, varying smoothly in the course of biological evolution. To the first level of approximation, quantum kernel can be described in the framework of qubit modification of Jaynes-Cummings-Hubbard model, in which the relaxation corresponds to the exchange of matter between quantum kernel and the rest of the cell and is represented as Lindblad super-operators.

  3. 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.

  4. Computational Biology for Drug Discovery and Characterization

    SciTech Connect

    Lightstone, F C; Bennion, B J

    2009-02-24

    We proposed to determine the underpinnings of a high-throughput computational infrastructure that would support future efforts in therapeutics against biothreat pathogens. Existing modeling capabilities focus on pathogen detection, but extending such capabilities to high-throughput molecular docking would lead to a proactive method to guide the development of therapeutics. This project will focus on determining the feasibility of extending current databases to accommodate molecular docking. We will also examine the feasibility of massive parallelization of docking algorithms and the utility of docking libraries. Transferring this new technique to a high-performance computing (HPC) platform at LLNL would result in a unique capability not available elsewhere in government or industry. We have accomplished the proposed work defined in this LDRD FS study. (1) We successfully defined the feasibility of using three different small-molecule databases for high-throughput docking, the NCI diversity set, ZINC and the ACD. (2) We analyzed the accuracy and parallelization capabilities of six separate docking programs: DOCK, AutoDock, FlexX, Glide, and eHiTS. Each program is completely amenable to parallel execution. The fastest code was eHiTS, and Glide was the most accurate. (3) Customizing large libraries was cumbersome without the proper software, making the databases a bit difficult to tailor. The ZINC database has some prefiltered versions. (4) Scripts were created for quality and job control functions. Further development is needed for analysis and visualization needs. The successful conclusion of this project enables LLNL to have a high-throughput computational docking capability where we have evaluated the codes to specific docking problems and utilized LLNL's HPC for significant gains in performance. We have established a CRADA with an industrial partner (funded by the National Institutes of Health) that will fully utilize this technology for biodefense therapeutic

  5. 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.

  6. 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.

  7. A First Attempt to Bring Computational Biology into Advanced High School Biology Classrooms

    PubMed Central

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

    2011-01-01

    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. PMID:22046118

  8. Deterministic Function Computation with Chemical Reaction Networks*

    PubMed Central

    Chen, Ho-Lin; Doty, David; Soloveichik, David

    2013-01-01

    Chemical reaction networks (CRNs) formally model chemistry in a well-mixed solution. CRNs are widely used to describe information processing occurring in natural cellular regulatory networks, and with upcoming advances in synthetic biology, CRNs are a promising language for the design of artificial molecular control circuitry. Nonetheless, despite the widespread use of CRNs in the natural sciences, the range of computational behaviors exhibited by CRNs is not well understood. CRNs have been shown to be efficiently Turing-universal (i.e., able to simulate arbitrary algorithms) when allowing for a small probability of error. CRNs that are guaranteed to converge on a correct answer, on the other hand, have been shown to decide only the semilinear predicates (a multi-dimensional generalization of “eventually periodic” sets). We introduce the notion of function, rather than predicate, computation by representing the output of a function f : ℕk → ℕl by a count of some molecular species, i.e., if the CRN starts with x1, …, xk molecules of some “input” species X1, …, Xk, the CRN is guaranteed to converge to having f(x1, …, xk) molecules of the “output” species Y1, …, Yl. We show that a function f : ℕk → ℕl is deterministically computed by a CRN if and only if its graph {(x, y) ∈ ℕk × ℕl ∣ f(x) = y} is a semilinear set. Finally, we show that each semilinear function f (a function whose graph is a semilinear set) can be computed by a CRN on input x in expected time O(polylog ∥x∥1). PMID:25383068

  9. 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…

  10. Structure and Associated Biological Functions of Viroids.

    PubMed

    Steger, Gerhard; Perreault, Jean-Pierre

    2016-01-01

    Mature viroids consist of a noncoding, covalently closed circular RNA that is able to autonomously infect respective host plants. Thus, they must utilize proteins of the host for most biological functions such as replication, processing, transport, and pathogenesis. Therefore, viroids can be regarded as minimal parasites of the host machinery. They have to present to the host machinery the appropriate signals based on either their sequence or their structure. Here, we summarize such sequence and structural features critical for the biological functions of viroids. PMID:26997592

  11. Low-energy dynamics and biological function

    NASA Astrophysics Data System (ADS)

    Lechner, R. E.; Fitter, J.; Dencher, N. A.; Hauß, T.

    2006-11-01

    Results from QENS experiments using a resolution of 93 μeV on a biological system are reported. The photocycle of the proton pump bacteriorhodopsin (BR) is known to slow down with decreasing temperature and humidity, a behaviour related to the ‘dynamic transition’. We have achieved a separation of the pure thermal activation effect involving the plasticizing action of hydration water, from effects due to the variation of the hydration level on the dynamics of purple membrane (PM) with its integral protein BR, and have correlated this with its ability to function. This demonstrates that the biological function of BR requires molecular dynamics in the ps range.

  12. 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. PMID:27558715

  13. MORT: a powerful foundational library for computational biology and CADD

    PubMed Central

    2014-01-01

    Background A foundational library called MORT (Molecular Objects and Relevant Templates) for the development of new software packages and tools employed in computational biology and computer-aided drug design (CADD) is described here. Results MORT contains several advantages compared with the other libraries. Firstly, MORT written in C++ natively supports the paradigm of object-oriented design, and thus it can be understood and extended easily. Secondly, MORT employs the relational model to represent a molecule, and it is more convenient and flexible than the traditional hierarchical model employed by many other libraries. Thirdly, a lot of functions have been included in this library, and a molecule can be manipulated easily at different levels. For example, it can parse a variety of popular molecular formats (MOL/SDF, MOL2, PDB/ENT, SMILES/SMARTS, etc.), create the topology and coordinate files for the simulations supported by AMBER, calculate the energy of a specific molecule based on the AMBER force fields, etc. Conclusions We believe that MORT can be used as a foundational library for programmers to develop new programs and applications for computational biology and CADD. Source code of MORT is available at http://cadd.suda.edu.cn/MORT/index.htm.

  14. 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

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

    PubMed

    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. Tutoring in School Biology by Computer Conference.

    ERIC Educational Resources Information Center

    Baggott, Linda; Wright, Bruce

    1997-01-01

    Describes an exploration of the use of digitized images in teaching biology to school students via the new digital communications channel, the Integrated Services Digital Network (ISDN). Contains 23 references. (DDR)

  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. 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, Micheal 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%5E16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m%5E3 and 3MW, giving the brain a 10%5E12 advantage in operations/s/W/cm%5E3. 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.

  19. 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...

  20. [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. PMID:27455812

  1. Biological cluster evaluation for gene function prediction.

    PubMed

    Klie, Sebastian; Nikoloski, Zoran; Selbig, Joachim

    2014-06-01

    Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set. PMID:20059365

  2. 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

  3. 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…

  4. 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

  5. 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

  6. 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

  7. 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. (Author/JRH)

  8. 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.

  9. 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.

  10. Deducing protein function by forensic integrative cell biology.

    PubMed

    Earnshaw, William C

    2013-12-01

    Our ability to sequence genomes has provided us with near-complete lists of the proteins that compose cells, tissues, and organisms, but this is only the beginning of the process to discover the functions of cellular components. In the future, it's going to be crucial to develop computational analyses that can predict the biological functions of uncharacterised proteins. At the same time, we must not forget those fundamental experimental skills needed to confirm the predictions or send the analysts back to the drawing board to devise new ones. PMID:24358025

  11. 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.

  12. 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…

  13. 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

  14. Flavonoids: biosynthesis, biological functions, and biotechnological applications

    PubMed Central

    Falcone Ferreyra, María L.; Rius, Sebastián P.; Casati, Paula

    2012-01-01

    Flavonoids are widely distributed secondary metabolites with different metabolic functions in plants. The elucidation of the biosynthetic pathways, as well as their regulation by MYB, basic helix-loop-helix (bHLH), and WD40-type transcription factors, has allowed metabolic engineering of plants through the manipulation of the different final products with valuable applications. The present review describes the regulation of flavonoid biosynthesis, as well as the biological functions of flavonoids in plants, such as in defense against UV-B radiation and pathogen infection, nodulation, and pollen fertility. In addition, we discuss different strategies and achievements through the genetic engineering of flavonoid biosynthesis with implication in the industry and the combinatorial biosynthesis in microorganisms by the reconstruction of the pathway to obtain high amounts of specific compounds. PMID:23060891

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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

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

    PubMed

    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. A first course in computing with applications to biology.

    PubMed

    Libeskind-Hadas, Ran; Bush, Eliot

    2013-09-01

    We believe that undergraduate biology students must acquire a foundational background in computing including how to formulate a computational problem; develop an algorithmic solution; implement their solution in software and then test, document and use their code to explore biological phenomena. Moreover, by learning these skills in the first year, students acquire a powerful tool set that they can use and build on throughout their studies. To address this need, we have developed a first-year undergraduate course that teaches students the foundations of computational thinking and programming in the context of problems in biology. This article describes the structure and content of the course and summarizes assessment data on both affective and learning outcomes. PMID:23449003

  2. 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.

  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. Recent Developments in the Application of Biologically Inspired Computation to Chemical Sensing

    NASA Astrophysics Data System (ADS)

    Marco, S.; Gutierrez-Gálvez, A.

    2009-05-01

    Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.

  5. 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.

  6. High-resolution network biology: connecting sequence with function

    PubMed Central

    Ryan, Colm J.; Cimermančič, Peter; Szpiech, Zachary A.; Sali, Andrej; Hernandez, Ryan D.; Krogan, Nevan J.

    2014-01-01

    Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein– protein, genetic and drug–gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies. PMID:24197012

  7. Density Functional Theory of Biologically Relevant Metal Centers

    NASA Astrophysics Data System (ADS)

    Siegbahn, Per E. M.; Blomberg, Margareta R. A.

    1999-10-01

    Recent applications of density functional theory to biologically relevant metal centers are reviewed. The emphasis is on reaction mechanisms, structures, and modeling. The accuracy of different functionals is discussed for standard benchmark tests of first- and second-row molecules and for transition metal systems. Modeling aspects of the protein metal complexes are discussed regarding both the size of the model being treated quantum mechanically and the treatment of the protein surrounding it. To illustrate the effects, structures computed without the effects of the protein are compared with experimental structures from enzymes, and results from simple dielectric models of the protein for electron transfer processes are described. The choice of spin state is discussed for multimetal complexes. Examples of mechanisms studied recently by density functional theory are described, such as O2 and methane activation in methane monooxygenase and O2 formation in photosystem II.

  8. Filling the gap between biology and computer science.

    PubMed

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

    2008-01-01

    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. PMID:18822148

  9. 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…

  10. 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,…

  11. 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

  12. 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.

  13. 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.

  14. 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…

  15. 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.

  16. 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. PMID:19623488

  17. 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…

  18. 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

  19. 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

  20. 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. PMID:20658333

  1. 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).

  2. 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.

  3. On computing special functions in marine engineering

    NASA Astrophysics Data System (ADS)

    Constantinescu, E.; Bogdan, M.

    2015-11-01

    Important modeling applications in marine engineering conduct us to a special class of solutions for difficult differential equations with variable coefficients. In order to be able to solve and implement such models (in wave theory, in acoustics, in hydrodynamics, in electromagnetic waves, but also in many other engineering fields), it is necessary to compute so called special functions: Bessel functions, modified Bessel functions, spherical Bessel functions, Hankel functions. The aim of this paper is to develop numerical solutions in Matlab for the above mentioned special functions. Taking into account the main properties for Bessel and modified Bessel functions, we shortly present analytically solutions (where possible) in the form of series. Especially it is studied the behavior of these special functions using Matlab facilities: numerical solutions and plotting. Finally, it will be compared the behavior of the special functions and point out other directions for investigating properties of Bessel and spherical Bessel functions. The asymptotic forms of Bessel functions and modified Bessel functions allow determination of important properties of these functions. The modified Bessel functions tend to look more like decaying and growing exponentials.

  4. Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

    PubMed Central

    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. PMID:24078906

  5. Fusicoccanes: diterpenes with surprising biological functions.

    PubMed

    de Boer, Albertus H; de Vries-van Leeuwen, Ingrid J

    2012-06-01

    Fusicoccin is the best-studied member of a class of diterpenes sharing a 5-8-5 ring structure, called fusicoccanes. Fusicoccin was and still is a 'tool in plant physiology', targeting the main engine of plasma membrane transport, the P-type H(+)-ATPase, assisted by members of the 14-3-3 family. The key position of 14-3-3 proteins in cell biology, combined with a broader specificity of other fusicoccanes as shown by crystallography studies, make fusicoccanes a versatile tool in plant and animal biology. In this review, we examine recent evidence that fusicoccanes act on animal cells, describe the discovery of the fungal biosynthetic pathway and emphasize that lower (liverworts) and higher plants produce fusicoccanes with intriguing biological activities. PMID:22465041

  6. 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,…

  7. 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

  8. Computational Fluid Dynamics Framework for Turbine Biological Performance Assessment

    SciTech Connect

    Richmond, Marshall C.; Serkowski, John A.; Carlson, Thomas J.; Ebner, Laurie L.; Sick, Mirjam; Cada, G. F.

    2011-05-04

    In this paper, a method for turbine biological performance assessment is introduced to bridge the gap between field and laboratory studies on fish injury and turbine design. Using this method, a suite of biological performance indicators is computed based on simulated data from a computational fluid dynamics (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. If the relationship between the dose of an injury mechanism and frequency of injury (dose-response) is known 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 various turbine designs, the engineer can identify the more-promising designs. Discussion here is focused on Kaplan-type turbines, although the method could be extended to other designs. Following the description of the general methodology, we will present sample risk assessment calculations based on CFD data from a model of the John Day Dam on the Columbia River in the USA.

  9. 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

  10. Biological Structures, Interactions, Function and Behavior: Research Opportunities for Physicists

    NASA Astrophysics Data System (ADS)

    Concepcion, Gisela P.

    2008-06-01

    Studies on marine biomolecules at the Marine Natural Products Laboratory (MNPL) and studies on biomedically relevant proteins at the Virtual Laboratory of Biomolecular Structures (VIRLS) of the University of the Philippines Marine Science Institute (UPMSI) are presented. These serve to illustrate some underlying principles of biological structures, interactions, function and behavior, and also to draw out some unresolved questions in biology of possible interest to non-biologists. The Biological Structures course offered at UPMSI, which aims to introduce underlying biological principles to non-biology majors and to promote trans-disciplinary research efforts, is also presented.

  11. 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.

  12. Fibroblast Growth Factors: Biology, Function, and Application for Tissue Regeneration

    PubMed Central

    Yun, Ye-Rang; Won, Jong Eun; Jeon, Eunyi; Lee, Sujin; Kang, Wonmo; Jo, Hyejin; Jang, Jun-Hyeog; Shin, Ueon Sang; Kim, Hae-Won

    2010-01-01

    Fibroblast growth factors (FGFs) that signal through FGF receptors (FGFRs) regulate a broad spectrum of biological functions, including cellular proliferation, survival, migration, and differentiation. The FGF signal pathways are the RAS/MAP kinase pathway, PI3 kinase/AKT pathway, and PLCγ pathway, among which the RAS/MAP kinase pathway is known to be predominant. Several studies have recently implicated the in vitro biological functions of FGFs for tissue regeneration. However, to obtain optimal outcomes in vivo, it is important to enhance the half-life of FGFs and their biological stability. Future applications of FGFs are expected when the biological functions of FGFs are potentiated through the appropriate use of delivery systems and scaffolds. This review will introduce the biology and cellular functions of FGFs and deal with the biomaterials based delivery systems and their current applications for the regeneration of tissues, including skin, blood vessel, muscle, adipose, tendon/ligament, cartilage, bone, tooth, and nerve tissues. PMID:21350642

  13. 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

  14. 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.

  15. BioFNet: biological functional network database for analysis and synthesis of biological systems.

    PubMed

    Kurata, Hiroyuki; Maeda, Kazuhiro; Onaka, Toshikazu; Takata, Takenori

    2014-09-01

    In synthetic biology and systems biology, a bottom-up approach can be used to construct a complex, modular, hierarchical structure of biological networks. To analyze or design such networks, it is critical to understand the relationship between network structure and function, the mechanism through which biological parts or biomolecules are assembled into building blocks or functional networks. A functional network is defined as a subnetwork of biomolecules that performs a particular function. Understanding the mechanism of building functional networks would help develop a methodology for analyzing the structure of large-scale networks and design a robust biological circuit to perform a target function. We propose a biological functional network database, named BioFNet, which can cover the whole cell at the level of molecular interactions. The BioFNet takes an advantage in implementing the simulation program for the mathematical models of the functional networks, visualizing the simulated results. It presents a sound basis for rational design of biochemical networks and for understanding how functional networks are assembled to create complex high-level functions, which would reveal design principles underlying molecular architectures. PMID:23894104

  16. 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.

  17. [The biologic functional surfaces and their applications in tissue engineering].

    PubMed

    Yao, Fanglian; Chen, Man; Zhang, Hong; Zhang, Haiyue; An, Xiaoyan; Yao, Kangde

    2007-10-01

    The construction of biologic functional surfaces of materials, from the visual angle of material science, is aimed to make the biomaterials adapted by tissues, and to endow them with dynamic conformity; moreover, from the view-point of clinical applications, it is the functional surface to join the environmental tissues with the implanted material, playing the role of artificial extracellular matrix (ECM). The architecture of biologic functional surface is very important in tissue engineering science. Here the primary concepts of biological surface science and the construction and application of biofunctional surfaces in tissue engineering are reviewed. PMID:18027721

  18. Tunable ultrasensitivity: functional decoupling and biological insights.

    PubMed

    Wang, Guanyu; Zhang, Mengshi

    2016-01-01

    Sensitivity has become a basic concept in biology, but much less is known about its tuning, probably because allosteric cooperativity, the best known mechanism of sensitivity, is determined by rigid conformations of interacting molecules and is thus difficult to tune. Reversible covalent modification (RCM), owing to its systems-level ingenuity, can generate concentration based, tunable sensitivity. Using a mathematical model of regulated RCM, we find sensitivity tuning can be decomposed into two orthogonal modes, which provide great insights into vital biological processes such as tissue development and cell cycle progression. We find that decoupling of the two modes of sensitivity tuning is critical to fidelity of cell fate decision; the decoupling is thus important in development. The decomposition also allows us to solve the 'wasteful degradation conundrum' in budding yeast cell cycle checkpoint, which further leads to discovery of a subtle but essential difference between positive feedback and double negative feedback. The latter guarantees revocability of stress-induced cell cycle arrest; while the former does not. By studying concentration conditions in the system, we extend applicability of ultrasensitivity and explain the ubiquity of reversible covalent modification. PMID:26847155

  19. Tunable ultrasensitivity: functional decoupling and biological insights

    PubMed Central

    Wang, Guanyu; Zhang, Mengshi

    2016-01-01

    Sensitivity has become a basic concept in biology, but much less is known about its tuning, probably because allosteric cooperativity, the best known mechanism of sensitivity, is determined by rigid conformations of interacting molecules and is thus difficult to tune. Reversible covalent modification (RCM), owing to its systems-level ingenuity, can generate concentration based, tunable sensitivity. Using a mathematical model of regulated RCM, we find sensitivity tuning can be decomposed into two orthogonal modes, which provide great insights into vital biological processes such as tissue development and cell cycle progression. We find that decoupling of the two modes of sensitivity tuning is critical to fidelity of cell fate decision; the decoupling is thus important in development. The decomposition also allows us to solve the ‘wasteful degradation conundrum’ in budding yeast cell cycle checkpoint, which further leads to discovery of a subtle but essential difference between positive feedback and double negative feedback. The latter guarantees revocability of stress-induced cell cycle arrest; while the former does not. By studying concentration conditions in the system, we extend applicability of ultrasensitivity and explain the ubiquity of reversible covalent modification. PMID:26847155

  20. 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 "case". The goal of the…

  1. 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

  2. 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.

  3. Efficient computation of Wigner-Eisenbud functions

    NASA Astrophysics Data System (ADS)

    Raffah, Bahaaudin M.; Abbott, Paul C.

    2013-06-01

    The R-matrix method, introduced by Wigner and Eisenbud (1947) [1], has been applied to a broad range of electron transport problems in nanoscale quantum devices. With the rapid increase in the development and modeling of nanodevices, efficient, accurate, and general computation of Wigner-Eisenbud functions is required. This paper presents the Mathematica package WignerEisenbud, which uses the Fourier discrete cosine transform to compute the Wigner-Eisenbud functions in dimensionless units for an arbitrary potential in one dimension, and two dimensions in cylindrical coordinates. Program summaryProgram title: WignerEisenbud Catalogue identifier: AEOU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOU_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html Distribution format: tar.gz Programming language: Mathematica Operating system: Any platform supporting Mathematica 7.0 and above Keywords: Wigner-Eisenbud functions, discrete cosine transform (DCT), cylindrical nanowires Classification: 7.3, 7.9, 4.6, 5 Nature of problem: Computing the 1D and 2D Wigner-Eisenbud functions for arbitrary potentials using the DCT. Solution method: The R-matrix method is applied to the physical problem. Separation of variables is used for eigenfunction expansion of the 2D Wigner-Eisenbud functions. Eigenfunction computation is performed using the DCT to convert the Schrödinger equation with Neumann boundary conditions to a generalized matrix eigenproblem. Limitations: Restricted to uniform (rectangular grid) sampling of the potential. In 1D the number of sample points, n, results in matrix computations involving n×n matrices. Unusual features: Eigenfunction expansion using the DCT is fast and accurate. Users can specify scattering potentials using functions, or interactively using mouse input. Use of dimensionless units permits application to a

  4. 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. PMID:26420480

  5. 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

  6. Neutron monitor yield function: New improved computations

    NASA Astrophysics Data System (ADS)

    Mishev, A. L.; Usoskin, I. G.; Kovaltsov, G. A.

    2013-06-01

    A ground-based neutron monitor (NM) is a standard tool to measure cosmic ray (CR) variability near Earth, and it is crucially important to know its yield function for primary CRs. Although there are several earlier theoretically calculated yield functions, none of them agrees with experimental data of latitude surveys of sea-level NMs, thus suggesting for an inconsistency. A newly computed yield function of the standard sea-level 6NM64 NM is presented here separately for primary CR protons and α-particles, the latter representing also heavier species of CRs. The computations have been done using the GEANT-4 PLANETOCOSMICS Monte-Carlo tool and a realistic curved atmospheric model. For the first time, an effect of the geometrical correction of the NM effective area, related to the finite lateral expansion of the CR induced atmospheric cascade, is considered, which was neglected in the previous studies. This correction slightly enhances the relative impact of higher-energy CRs (energy above 5-10 GeV/nucleon) in NM count rate. The new computation finally resolves the long-standing problem of disagreement between the theoretically calculated spatial variability of CRs over the globe and experimental latitude surveys. The newly calculated yield function, corrected for this geometrical factor, appears fully consistent with the experimental latitude surveys of NMs performed during three consecutive solar minima in 1976-1977, 1986-1987, and 1996-1997. Thus, we provide a new yield function of the standard sea-level NM 6NM64 that is validated against experimental data.

  7. Conduction pathways in microtubules, biological quantum computation, and consciousness.

    PubMed

    Hameroff, Stuart; Nip, Alex; Porter, Mitchell; Tuszynski, Jack

    2002-01-01

    Technological computation is entering the quantum realm, focusing attention on biomolecular information processing systems such as proteins, as presaged by the work of Michael Conrad. Protein conformational dynamics and pharmacological evidence suggest that protein conformational states-fundamental information units ('bits') in biological systems-are governed by quantum events, and are thus perhaps akin to quantum bits ('qubits') as utilized in quantum computation. 'Real time' dynamic activities within cells are regulated by the cell cytoskeleton, particularly microtubules (MTs) which are cylindrical lattice polymers of the protein tubulin. Recent evidence shows signaling, communication and conductivity in MTs, and theoretical models have predicted both classical and quantum information processing in MTs. In this paper we show conduction pathways for electron mobility and possible quantum tunneling and superconductivity among aromatic amino acids in tubulins. The pathways within tubulin match helical patterns in the microtubule lattice structure, which lend themselves to topological quantum effects resistant to decoherence. The Penrose-Hameroff 'Orch OR' model of consciousness is reviewed as an example of the possible utility of quantum computation in MTs. PMID:11755497

  8. 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

  9. 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.

  10. The evolutionary origin of biological function and complexity.

    PubMed

    Pross, Addy

    2013-04-01

    The identification of dynamic kinetic stability (DKS) as a stability kind that governs the evolutionary process for both chemical and biological replicators, opens up new avenues for uncovering the chemical basis of biological phenomena. In this paper, we utilize the DKS concept to explore the chemical roots of two of biology's central concepts--function and complexity. It is found that the selection rule in the world of persistent replicating systems--from DKS less stable to DKS more stable--is the operational law whose very existence leads to the creation of function from of a world initially devoid of function. The origin of biological complexity is found to be directly related to the origin of function through an underlying connection between the two phenomena. Thus the emergence of both function and complexity during abiogenesis, and their growing expression during biological evolution, are found to be governed by the same single driving force, the drive toward greater DKS. It is reaffirmed that the essence of biological phenomena can be best revealed by uncovering biology's chemical roots, by elucidating the physicochemical principles that governed the process by which life on earth emerged from inanimate matter. PMID:23512244

  11. Functional mapping in biology and medicine

    SciTech Connect

    McEachron, D.L.

    1986-01-01

    This book contains 10 selections. Some of the titles are: Two Views of Functional Mapping and Autoradiography; Quantitative Analysis of Autoradiographs; Hardware and Software Design Considerations in Engineering an Image Processing Workstation: Autoradiographic Analysis with DUMAS and the BRAIN Autoradiograph Analysis Software Package (with 1 color plate); and Quantitative Autoradiography and in vitro Radioligand Binding.

  12. Biological insertion of computationally designed short transmembrane segments.

    PubMed

    Baeza-Delgado, Carlos; von Heijne, Gunnar; Marti-Renom, Marc A; Mingarro, Ismael

    2016-01-01

    The great majority of helical membrane proteins are inserted co-translationally into the ER membrane through a continuous ribosome-translocon channel. The efficiency of membrane insertion depends on transmembrane (TM) helix amino acid composition, the helix length and the position of the amino acids within the helix. In this work, we conducted a computational analysis of the composition and location of amino acids in transmembrane helices found in membrane proteins of known structure to obtain an extensive set of designed polypeptide segments with naturally occurring amino acid distributions. Then, using an in vitro translation system in the presence of biological membranes, we experimentally validated our predictions by analyzing its membrane integration capacity. Coupled with known strategies to control membrane protein topology, these findings may pave the way to de novo membrane protein design. PMID:26987712

  13. Biological insertion of computationally designed short transmembrane segments

    PubMed Central

    Baeza-Delgado, Carlos; von Heijne, Gunnar; Marti-Renom, Marc A.; Mingarro, Ismael

    2016-01-01

    The great majority of helical membrane proteins are inserted co-translationally into the ER membrane through a continuous ribosome-translocon channel. The efficiency of membrane insertion depends on transmembrane (TM) helix amino acid composition, the helix length and the position of the amino acids within the helix. In this work, we conducted a computational analysis of the composition and location of amino acids in transmembrane helices found in membrane proteins of known structure to obtain an extensive set of designed polypeptide segments with naturally occurring amino acid distributions. Then, using an in vitro translation system in the presence of biological membranes, we experimentally validated our predictions by analyzing its membrane integration capacity. Coupled with known strategies to control membrane protein topology, these findings may pave the way to de novo membrane protein design. PMID:26987712

  14. Catch bonds: physical models and biological functions.

    PubMed

    Zhu, Cheng; McEver, Rodger P

    2005-09-01

    Force can shorten the lifetimes of receptor-ligand bonds by accelerating their dissociation. Perhaps paradoxical at first glance, bond lifetimes can also be prolonged by force. This counterintuitive behavior was named catch bonds, which is in contrast to the ordinary slip bonds that describe the intuitive behavior of lifetimes being shortened by force. Fifteen years after their theoretical proposal, catch bonds have finally been observed. In this article we review recently published data that have demonstrated catch bonds in the selectin system and suggested catch bonds in other systems, the theoretical models for their explanations, and their function as a mechanism for flow-enhanced adhesion. PMID:16708472

  15. Using computer algebra and SMT solvers in algebraic biology

    NASA Astrophysics Data System (ADS)

    Pineda Osorio, Mateo

    2014-05-01

    Biologic processes are represented as Boolean networks, in a discrete time. The dynamics within these networks are approached with the help of SMT Solvers and the use of computer algebra. Software such as Maple and Z3 was used in this case. The number of stationary states for each network was calculated. The network studied here corresponds to the immune system under the effects of drastic mood changes. Mood is considered as a Boolean variable that affects the entire dynamics of the immune system, changing the Boolean satisfiability and the number of stationary states of the immune network. Results obtained show Z3's great potential as a SMT Solver. Some of these results were verified in Maple, even though it showed not to be as suitable for the problem approach. The solving code was constructed using Z3-Python and Z3-SMT-LiB. Results obtained are important in biology systems and are expected to help in the design of immune therapies. As a future line of research, more complex Boolean network representations of the immune system as well as the whole psychological apparatus are suggested.

  16. Computational procedures for optimal experimental design in biological systems.

    PubMed

    Balsa-Canto, E; Alonso, A A; Banga, J R

    2008-07-01

    Mathematical models of complex biological systems, such as metabolic or cell-signalling pathways, usually consist of sets of nonlinear ordinary differential equations which depend on several non-measurable parameters that can be hopefully estimated by fitting the model to experimental data. However, the success of this fitting is largely conditioned by the quantity and quality of data. Optimal experimental design (OED) aims to design the scheme of actuations and measurements which will result in data sets with the maximum amount and/or quality of information for the subsequent model calibration. New methods and computational procedures for OED in the context of biological systems are presented. The OED problem is formulated as a general dynamic optimisation problem where the time-dependent stimuli profiles, the location of sampling times, the duration of the experiments and the initial conditions are regarded as design variables. Its solution is approached using the control vector parameterisation method. Since the resultant nonlinear optimisation problem is in most of the cases non-convex, the use of a robust global nonlinear programming solver is proposed. For the sake of comparing among different experimental schemes, a Monte-Carlo-based identifiability analysis is then suggested. The applicability and advantages of the proposed techniques are illustrated by considering an example related to a cell-signalling pathway. PMID:18681746

  17. 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

  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. PMID:26025527

  19. 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

  20. Discrete Wigner functions and quantum computational speedup

    SciTech Connect

    Galvao, Ernesto F.

    2005-04-01

    Gibbons et al. [Phys. Rev. A 70, 062101 (2004)] have recently defined a class of discrete Wigner functions W to represent quantum states in a finite Hilbert space dimension d. I characterize the set C{sub d} of states having non-negative W simultaneously in all definitions of W in this class. For d{<=}5 I show C{sub d} is the convex hull of stabilizer states. This supports the conjecture that negativity of W is necessary for exponential speedup in pure-state quantum computation.

  1. 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. PMID:24696186

  2. 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

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

    PubMed Central

    2011-01-01

    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. PMID:21861851

  4. 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'. PMID:27431524

  5. 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. PMID:26415843

  6. Connecting leptin signaling to biological function

    PubMed Central

    Allison, Margaret B.; Myers, Martin G.

    2014-01-01

    Hypothalamic leptin action promotes negative energy balance and modulates glucose homeostasis, as well as serving as a permissive signal to the neuroendocrine axes that control growth and reproduction. Since the initial discovery of leptin 20 years ago, we have learned a great deal about the molecular mechanisms of leptin action. An important aspect of this has been the dissection of the cellular mechanisms of leptin signaling, and how specific leptin signals influence physiology. Leptin acts via the long form of the leptin receptor, LepRb. LepRb activation and subsequent tyrosine phosphorylation recruits and activates multiple signaling pathways, including STAT transcription factors, SHP2 and ERK signaling, the IRS-protein/PI3Kinase pathway, and SH2B1. Each of these pathways controls specific aspects of leptin action and physiology. Important inhibitory pathways mediated by suppressor of cytokine signaling (SOCS) proteins and protein tyrosine phosphatases (PTPases) also limit physiologic leptin action. This review summarizes the signaling pathways engaged by LepRb and their effects on energy balance, glucose homeostasis, and reproduction. Particular emphasis is given to the multiple mouse models which have been used to elucidate these functions in vivo. PMID:25232147

  7. [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. PMID:23402139

  8. 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…

  9. Distinguishing between "function" and "effect" in genome biology.

    PubMed

    Doolittle, W Ford; Brunet, Tyler D P; Linquist, Stefan; Gregory, T Ryan

    2014-05-01

    Much confusion in genome biology results from conflation of possible meanings of the word "function." We suggest that, in this connection, attention should be paid to evolutionary biologists and philosophers who have previously dealt with this problem. We need only decide that although all genomic structures have effects, only some of them should be said to have functions. Although it will very often be difficult or impossible to establish function (strictly defined), it should not automatically be assumed. We enjoin genomicists in particular to pay greater attention to parsing biological effects. PMID:24814287

  10. Tip110: Physical properties, primary structure, and biological functions.

    PubMed

    Whitmill, Amanda; Timani, Khalid Amine; Liu, Ying; He, Johnny J

    2016-03-15

    HIV-1 Tat-interacting protein of 110kDa (Tip110), also referred to as squamous cell carcinoma antigen recognized by T cells 3 (Sart3), p110 or p110(nrb), was initially identified as a cDNA clone (KIAA0156) without annotated functions. Over the past twenty years, several functions have been attributed to this protein. The proposed biological functions include roles for Tip110 in pre-mRNA splicing, gene transcription, stem cell biology, and development. Dysregulation of Tip110 is also a contributing factor in the development of cancer and other human diseases. It is clear that our understanding of this protein is rapidly evolving. In this review, we aimed to provide a summary of all the existing literature on this gene/protein and its proposed biological functions. PMID:26896687

  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. PMID:24048833

  12. 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. PMID:26668171

  13. 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...

  14. 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. PMID:26141968

  15. Chaste: using agile programming techniques to develop computational biology software.

    PubMed

    Pitt-Francis, Joe; Bernabeu, Miguel O; Cooper, Jonathan; Garny, Alan; Momtahan, Lee; Osborne, James; Pathmanathan, Pras; Rodriguez, Blanca; Whiteley, Jonathan P; Gavaghan, David J

    2008-09-13

    Cardiac modelling is the area of physiome modelling where the available simulation software is perhaps most mature, and it therefore provides an excellent starting point for considering the software requirements for the wider physiome community. In this paper, we will begin by introducing some of the most advanced existing software packages for simulating cardiac electrical activity. We consider the software development methods used in producing codes of this type, and discuss their use of numerical algorithms, relative computational efficiency, usability, robustness and extensibility. We then go on to describe a class of software development methodologies known as test-driven agile methods and argue that such methods are more suitable for scientific software development than the traditional academic approaches. A case study is a project of our own, Cancer, Heart and Soft Tissue Environment, which is a library of computational biology software that began as an experiment in the use of agile programming methods. We present our experiences with a review of our progress thus far, focusing on the advantages and disadvantages of this new approach compared with the development methods used in some existing packages. We conclude by considering whether the likely wider needs of the cardiac modelling community are currently being met and suggest that, in order to respond effectively to changing requirements, it is essential that these codes should be more malleable. Such codes will allow for reliable extensions to include both detailed mathematical models--of the heart and other organs--and more efficient numerical techniques that are currently being developed by many research groups worldwide. PMID:18565813

  16. Infrared Structural Biology: Detect Functionally Important Structural Motions of Proteins

    NASA Astrophysics Data System (ADS)

    Xie, Aihua

    Proteins are dynamic. Lack of dynamic structures of proteins hampers our understanding of protein functions. Infrared structural biology (IRSB) is an emerging technology. There are several advantages of IRSB for mechanistic studies of proteins: (1) its excellent dynamic range (detecting structural motions from picoseconds to >= seconds); (2) its high structural sensitivity (detect tiny but functionally important structural motions such as proton transfer and changes in hydrogen bonding interaction); (3) its ability to detect different structural motions simultaneously. Successful development of infrared structural biology demands not only new experimental techniques (from infrared technologies to chemical synthesis and cell biology), but also new data processing (how to translate infrared signals into quantitative structural information of proteins). These topics will be discussed as well as examples of how to use IRSB to study structure-function relationship of proteins. This work was supported by NSF DBI1338097 and OCAST HR10-078.

  17. 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.

  18. Systematic Functional Annotation and Visualization of Biological Networks.

    PubMed

    Baryshnikova, Anastasia

    2016-06-22

    Large-scale biological networks represent relationships between genes, but our understanding of how networks are functionally organized is limited. Here, I describe spatial analysis of functional enrichment (SAFE), a systematic method for annotating biological networks and examining their functional organization. SAFE visualizes the network in 2D space and measures the continuous distribution of functional enrichment across local neighborhoods, producing a list of the associated functions and a map of their relative positioning. I applied SAFE to annotate the Saccharomyces cerevisiae genetic interaction similarity network and protein-protein interaction network with gene ontology terms. SAFE annotations of the genetic network matched manually derived annotations, while taking less than 1% of the time, and proved robust to noise and sensitive to biological signal. Integration of genetic interaction and chemical genomics data using SAFE revealed a link between vesicle-mediate transport and resistance to the anti-cancer drug bortezomib. These results demonstrate the utility of SAFE for examining biological networks and understanding their functional organization. PMID:27237738

  19. 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. PMID:26672917

  20. 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

  1. Computing distribution of scale independent motifs in biological sequences

    PubMed Central

    Almeida, Jonas S; Vinga, Susana

    2006-01-01

    The use of Chaos Game Representation (CGR) or its generalization, Universal Sequence Maps (USM), to describe the distribution of biological sequences has been found objectionable because of the fractal structure of that coordinate system. Consequently, the investigation of distribution of symbolic motifs at multiple scales is hampered by an inexact association between distance and sequence dissimilarity. A solution to this problem could unleash the use of iterative maps as phase-state representation of sequences where its statistical properties can be conveniently investigated. In this study a family of kernel density functions is described that accommodates the fractal nature of iterative function representations of symbolic sequences and, consequently, enables the exact investigation of sequence motifs of arbitrary lengths in that scale-independent representation. Furthermore, the proposed kernel density includes both Markovian succession and currently used alignment-free sequence dissimilarity metrics as special solutions. Therefore, the fractal kernel described is in fact a generalization that provides a common framework for a diverse suite of sequence analysis techniques. PMID:17049089

  2. 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

  3. 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

  4. 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

  5. Heme-nitrosyls: electronic structure implications for function in biology.

    PubMed

    Hunt, Andrew P; Lehnert, Nicolai

    2015-07-21

    The question of why mammalian systems use nitric oxide (NO), a potentially hazardous and toxic diatomic, as a signaling molecule to mediate important functions such as vasodilation (blood pressure control) and nerve signal transduction initially perplexed researchers when this discovery was made in the 1980s. Through extensive research over the past two decades, it is now well rationalized why NO is used in vivo for these signaling functions, and that heme proteins play a dominant role in NO signaling in mammals. Key insight into the properties of heme-nitrosyl complexes that make heme proteins so well poised to take full advantage of the unique properties of NO has come from in-depth structural, spectroscopic, and theoretical studies on ferrous and ferric heme-nitrosyls. This Account highlights recent findings that have led to greater understanding of the electronic structures of heme-nitrosyls, and the contributions that model complex studies have made to elucidate Fe-NO bonding are highlighted. These results are then discussed in the context of the biological functions of heme-nitrosyls, in particular in soluble guanylate cyclase (sGC; NO signaling), nitrophorins (NO transport), and NO-producing enzymes. Central to this Account is the thermodynamic σ-trans effect of NO, and how this relates to the activation of the universal mammalian NO sensor sGC, which uses a ferrous heme as the high affinity "NO detection unit". It is shown via detailed spectroscopic and computational studies that the strong and very covalent Fe(II)-NO σ-bond is at the heart of the strong thermodynamic σ-trans effect of NO, which greatly weakens the proximal Fe-NHis (or Fe-SCys) bond in six-coordinate ferrous heme-nitrosyls. In sGC, this causes the dissociation of the proximally bound histidine ligand upon NO binding to the ferrous heme, inducing a significant conformational change that activates the sGC catalytic domain for the production of cGMP. This, in turn, leads to vasodilation and

  6. Advanced Computer Simulations Of Nanomaterials And Stochastic Biological Processes

    NASA Astrophysics Data System (ADS)

    Minakova, Maria S.

    computational and theoretical studies compose a powerful and diverse set of physical approaches and both analytical and numerical methodologies, that can be successfully applied in the fields of biology, chemistry and biophysics.

  7. 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

  8. Functional requirements for gas characterization system computer software

    SciTech Connect

    Tate, D.D.

    1996-01-01

    This document provides the Functional Requirements for the Computer Software operating the Gas Characterization System (GCS), which monitors the combustible gasses in the vapor space of selected tanks. Necessary computer functions are defined to support design, testing, operation, and change control. The GCS requires several individual computers to address the control and data acquisition functions of instruments and sensors. These computers are networked for communication, and must multi-task to accommodate operation in parallel.

  9. Theoretical and computational models of biological ion channels

    NASA Astrophysics Data System (ADS)

    Roux, Benoit

    2004-03-01

    A theoretical framework for describing ion conduction through biological molecular pores is established and explored. The framework is based on a statistical mechanical formulation of the transmembrane potential (1) and of the equilibrium multi-ion potential of mean forces through selective ion channels (2). On the basis of these developments, it is possible to define computational schemes to address questions about the non-equilibrium flow of ions through ion channels. In the case of narrow channels (gramicidin or KcsA), it is possible to characterize the ion conduction in terms of the potential of mean force of the ions along the channel axis (i.e., integrating out the off-axis motions). This has been used for gramicidin (3) and for KcsA (4,5). In the case of wide pores (i.e., OmpF porin), this is no longer a good idea, but it is possible to use a continuum solvent approximations. In this case, a grand canonical monte carlo brownian dynamics algorithm was constructed for simulating the non-equilibrium flow of ions through wide pores. The results were compared with those from the Poisson-Nernst-Planck mean-field electrodiffusion theory (6-8). References; 1. B. Roux, Biophys. J. 73:2980-2989 (1997); 2. B. Roux, Biophys. J. 77, 139-153 (1999); 3. Allen, Andersen and Roux, PNAS (2004, in press); 4. Berneche and Roux. Nature, 414:73-77 (2001); 5. Berneche and Roux. PNAS, 100:8644-8648 (2003); 6. W. Im and S. Seefeld and B. Roux, Biophys. J. 79:788-801 (2000); 7. W. Im and B. Roux, J. Chem. Phys. 115:4850-4861 (2001); 8. W. Im and B. Roux, J. Mol. Biol. 322:851-869 (2002).

  10. Computational approaches to selecting and optimising targets for structural biology.

    PubMed

    Overton, Ian M; Barton, Geoffrey J

    2011-09-01

    Selection of protein targets for study is central to structural biology and may be influenced by numerous factors. A key aim is to maximise returns for effort invested by identifying proteins with the balance of biophysical properties that are conducive to success at all stages (e.g. solubility, crystallisation) in the route towards a high resolution structural model. Selected targets can be optimised through construct design (e.g. to minimise protein disorder), switching to a homologous protein, and selection of experimental methodology (e.g. choice of expression system) to prime for efficient progress through the structural proteomics pipeline. Here we discuss computational techniques in target selection and optimisation, with more detailed focus on tools developed within the Scottish Structural Proteomics Facility (SSPF); namely XANNpred, ParCrys, OB-Score (target selection) and TarO (target optimisation). TarO runs a large number of algorithms, searching for homologues and annotating the pool of possible alternative targets. This pool of putative homologues is presented in a ranked, tabulated format and results are also visualised as an automatically generated and annotated multiple sequence alignment. The target selection algorithms each predict the propensity of a selected protein target to progress through the experimental stages leading to diffracting crystals. This single predictor approach has advantages for target selection, when compared with an approach using two or more predictors that each predict for success at a single experimental stage. The tools described here helped SSPF achieve a high (21%) success rate in progressing cloned targets to diffraction-quality crystals. PMID:21906678

  11. Exploratory Analysis of Biological Networks through Visualization, Clustering, and Functional Annotation in Cytoscape.

    PubMed

    Baryshnikova, Anastasia

    2016-01-01

    Biological networks define how genes, proteins, and other cellular components interact with one another to carry out specific functions, providing a scaffold for understanding cellular organization. Although in-depth network analysis requires advanced mathematical and computational knowledge, a preliminary visual exploration of biological networks is accessible to anyone with basic computer skills. Visualization of biological networks is used primarily to examine network topology, identify functional modules, and predict gene functions based on gene connectivity within the network. Networks are excellent at providing a bird's-eye view of data sets and have the power of illustrating complex ideas in simple and intuitive terms. In addition, they enable exploratory analysis and generation of new hypotheses, which can then be tested using rigorous statistical and experimental tools. This protocol describes a simple procedure for visualizing a biological network using the genetic interaction similarity network for Saccharomyces cerevisiae as an example. The visualization procedure described here relies on the open-source network visualization software Cytoscape and includes detailed instructions on formatting and loading the data, clustering networks, and overlaying functional annotations. PMID:26988373

  12. 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. PMID:26542523

  13. Linking structural features of protein complexes and biological function.

    PubMed

    Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

    2015-09-01

    Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. PMID:26131659

  14. 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

  15. 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

  16. 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.

  17. 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").

  18. Carbon-Oxygen Hydrogen Bonding in Biological Structure and Function

    PubMed Central

    Horowitz, Scott; Trievel, Raymond C.

    2012-01-01

    Carbon-oxygen (CH···O) hydrogen bonding represents an unusual category of molecular interactions first documented in biological structures over 4 decades ago. Although CH···O hydrogen bonding has remained generally underappreciated in the biochemical literature, studies over the last 15 years have begun to yield direct evidence of these interactions in biological systems. In this minireview, we provide a historical context of biological CH···O hydrogen bonding and summarize some major advancements from experimental studies over the past several years that have elucidated the importance, prevalence, and functions of these interactions. In particular, we examine the impact of CH···O bonds on protein and nucleic acid structure, molecular recognition, and enzyme catalysis and conclude by exploring overarching themes and unresolved questions regarding unconventional interactions in biomolecular structure. PMID:23048026

  19. Experimental and Computational Characterization of Biological Liquid Crystals: A Review of Single-Molecule Bioassays

    PubMed Central

    Eom, Kilho; Yang, Jaemoon; Park, Jinsung; Yoon, Gwonchan; Soo Sohn, Young; Park, Shinsuk; Yoon, Dae Sung; Na, Sungsoo; Kwon, Taeyun

    2009-01-01

    Quantitative understanding of the mechanical behavior of biological liquid crystals such as proteins is essential for gaining insight into their biological functions, since some proteins perform notable mechanical functions. Recently, single-molecule experiments have allowed not only the quantitative characterization of the mechanical behavior of proteins such as protein unfolding mechanics, but also the exploration of the free energy landscape for protein folding. In this work, we have reviewed the current state-of-art in single-molecule bioassays that enable quantitative studies on protein unfolding mechanics and/or various molecular interactions. Specifically, single-molecule pulling experiments based on atomic force microscopy (AFM) have been overviewed. In addition, the computational simulations on single-molecule pulling experiments have been reviewed. We have also reviewed the AFM cantilever-based bioassay that provides insight into various molecular interactions. Our review highlights the AFM-based single-molecule bioassay for quantitative characterization of biological liquid crystals such as proteins. PMID:19865530

  20. 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. PMID:15724280

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. Algorithms in nature: the convergence of systems biology and computational thinking

    PubMed Central

    Navlakha, Saket; Bar-Joseph, Ziv

    2011-01-01

    Computer science and biology have enjoyed a long and fruitful relationship for decades. Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. Recently, these two directions have been converging. In this review, we argue that thinking computationally about biological processes may lead to more accurate models, which in turn can be used to improve the design of algorithms. We discuss the similar mechanisms and requirements shared by computational and biological processes and then present several recent studies that apply this joint analysis strategy to problems related to coordination, network analysis, and tracking and vision. We also discuss additional biological processes that can be studied in a similar manner and link them to potential computational problems. With the rapid accumulation of data detailing the inner workings of biological systems, we expect this direction of coupling biological and computational studies to greatly expand in the future. PMID:22068329

  7. Research advances on structure and biological functions of integrins.

    PubMed

    Pan, Li; Zhao, Yuan; Yuan, Zhijie; Qin, Guixin

    2016-01-01

    Integrins are an important family of adhesion molecules that were first discovered two decades ago. Integrins are transmembrane heterodimeric glycoprotein receptors consisting of α and β subunits, and are comprised of an extracellular domain, a transmembrane domain, and a cytoplasmic tail. Therein, integrin cytoplasmic domains may associate directly with numerous cytoskeletal proteins and intracellular signaling molecules, which are crucial for modulating fundamental cell processes and functions including cell adhesion, proliferation, migration, and survival. The purpose of this review is to describe the unique structure of each integrin subunit, primary cytoplasmic association proteins, and transduction signaling pathway of integrins, with an emphasis on their biological functions. PMID:27468395

  8. 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. PMID:25313296

  9. 5-methylcytosine in RNA: detection, enzymatic formation and biological functions

    PubMed Central

    Motorin, Yuri; Lyko, Frank; Helm, Mark

    2010-01-01

    The nucleobase modification 5-methylcytosine (m5C) is widespread both in DNA and different cellular RNAs. The functions and enzymatic mechanisms of DNA m5C-methylation were extensively studied during the last decades. However, the location, the mechanism of formation and the cellular function(s) of the same modified nucleobase in RNA still remain to be elucidated. The recent development of a bisulfite sequencing approach for efficient m5C localization in various RNA molecules puts ribo-m5C in a highly privileged position as one of the few RNA modifications whose detection is amenable to PCR-based amplification and sequencing methods. Additional progress in the field also includes the characterization of several specific RNA methyltransferase enzymes in various organisms, and the discovery of a new and unexpected link between DNA and RNA m5C-methylation. Numerous putative RNA:m5C-MTases have now been identified and are awaiting characterization, including the identification of their RNA substrates and their related cellular functions. In order to bring these recent exciting developments into perspective, this review provides an ordered overview of the detection methods for RNA methylation, of the biochemistry, enzymology and molecular biology of the corresponding modification enzymes, and discusses perspectives for the emerging biological functions of these enzymes. PMID:20007150

  10. 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…

  11. The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists

    PubMed Central

    Huang, Da Wei; Sherman, Brad T; Tan, Qina; Collins, Jack R; Alvord, W Gregory; Roayaei, Jean; Stephens, Robert; Baseler, Michael W; Lane, H Clifford; Lempicki, Richard A

    2007-01-01

    The DAVID Gene Functional Classification Tool uses a novel agglomeration algorithm to condense a list of genes or associated biological terms into organized classes of related genes or biology, called biological modules. This organization is accomplished by mining the complex biological co-occurrences found in multiple sources of functional annotation. It is a powerful method to group functionally related genes and terms into a manageable number of biological modules for efficient interpretation of gene lists in a network context. PMID:17784955

  12. 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.

  13. Computational modeling of in vitro biological responses on polymethacrylate surfaces

    PubMed Central

    Ghosh, Jayeeta; Lewitus, Dan Y; Chandra, Prafulla; Joy, Abraham; Bushman, Jared; Knight, Doyle; Kohn, Joachim

    2011-01-01

    The objective of this research was to examine the capabilities of QSPR (Quantitative Structure Property Relationship) modeling to predict specific biological responses (fibrinogen adsorption, cell attachment and cell proliferation index) on thin films of different polymethacrylates. Using 33 commercially available monomers it is theoretically possible to construct a library of over 40,000 distinct polymer compositions. A subset of these polymers were synthesized and solvent cast surfaces were prepared in 96 well plates for the measurement of fibrinogen adsorption. NIH 3T3 cell attachment and proliferation index were measured on spin coated thin films of these polymers. Based on the experimental results of these polymers, separate models were built for homo-, co-, and terpolymers in the library with good correlation between experiment and predicted values. The ability to predict biological responses by simple QSPR models for large numbers of polymers has important implications in designing biomaterials for specific biological or medical applications. PMID:21779132

  14. 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.

  15. 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.

  16. 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. PMID:26652417

  17. Systems analysis of biological networks in skeletal muscle function.

    PubMed

    Smith, Lucas R; Meyer, Gretchen; Lieber, Richard L

    2013-01-01

    Skeletal muscle function depends on the efficient coordination among subcellular systems. These systems are composed of proteins encoded by a subset of genes, all of which are tightly regulated. In the cases where regulation is altered because of disease or injury, dysfunction occurs. To enable objective analysis of muscle gene expression profiles, we have defined nine biological networks whose coordination is critical to muscle function. We begin by describing the expression of proteins necessary for optimal neuromuscular junction function that results in the muscle cell action potential. That action potential is transmitted to proteins involved in excitation-contraction coupling enabling Ca(2+) release. Ca(2+) then activates contractile proteins supporting actin and myosin cross-bridge cycling. Force generated by cross-bridges is transmitted via cytoskeletal proteins through the sarcolemma and out to critical proteins that support the muscle extracellular matrix. Muscle contraction is fueled through many proteins that regulate energy metabolism. Inflammation is a common response to injury that can result in alteration of many pathways within muscle. Muscle also has multiple pathways that regulate size through atrophy or hypertrophy. Finally, the isoforms associated with fast muscle fibers and their corresponding isoforms in slow muscle fibers are delineated. These nine networks represent important biological systems that affect skeletal muscle function. Combining high-throughput systems analysis with advanced networking software will allow researchers to use these networks to objectively study skeletal muscle systems. PMID:23188744

  18. Mnk kinase pathway: Cellular functions and biological outcomes.

    PubMed

    Joshi, Sonali; Platanias, Leonidas C

    2014-08-26

    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

  19. 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. PMID:25979354

  20. Systems analysis of biological networks in skeletal muscle function

    PubMed Central

    Smith, Lucas R.; Meyer, Gretchen; Lieber, Richard L.

    2014-01-01

    Skeletal muscle function depends on the efficient coordination among subcellular systems. These systems are composed of proteins encoded by a subset of genes, all of which are tightly regulated. In the cases where regulation is altered because of disease or injury, dysfunction occurs. To enable objective analysis of muscle gene expression profiles, we have defined nine biological networks whose coordination is critical to muscle function. We begin by describing the expression of proteins necessary for optimal neuromuscular junction function that results in the muscle cell action potential. That action potential is transmitted to proteins involved in excitation–contraction coupling enabling Ca2+ release. Ca2+ then activates contractile proteins supporting actin and myosin cross-bridge cycling. Force generated by cross-bridges is transmitted via cytoskeletal proteins through the sarcolemma and out to critical proteins that support the muscle extracellular matrix. Muscle contraction is fueled through many proteins that regulate energy metabolism. Inflammation is a common response to injury that can result in alteration of many pathways within muscle. Muscle also has multiple pathways that regulate size through atrophy or hypertrophy. Finally, the isoforms associated with fast muscle fibers and their corresponding isoforms in slow muscle fibers are delineated. These nine networks represent important biological systems that affect skeletal muscle function. Combining high-throughput systems analysis with advanced networking software will allow researchers to use these networks to objectively study skeletal muscle systems. PMID:23188744

  1. 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

  2. Probing the Xenopus laevis inner ear transcriptome for biological function

    PubMed Central

    2012-01-01

    Background The senses of hearing and balance depend upon mechanoreception, a process that originates in the inner ear and shares features across species. Amphibians have been widely used for physiological studies of mechanotransduction by sensory hair cells. In contrast, much less is known of the genetic basis of auditory and vestibular function in this class of animals. Among amphibians, the genus Xenopus is a well-characterized genetic and developmental model that offers unique opportunities for inner ear research because of the amphibian capacity for tissue and organ regeneration. For these reasons, we implemented a functional genomics approach as a means to undertake a large-scale analysis of the Xenopus laevis inner ear transcriptome through microarray analysis. Results Microarray analysis uncovered genes within the X. laevis inner ear transcriptome associated with inner ear function and impairment in other organisms, thereby supporting the inclusion of Xenopus in cross-species genetic studies of the inner ear. The use of gene categories (inner ear tissue; deafness; ion channels; ion transporters; transcription factors) facilitated the assignment of functional significance to probe set identifiers. We enhanced the biological relevance of our microarray data by using a variety of curation approaches to increase the annotation of the Affymetrix GeneChip® Xenopus laevis Genome array. In addition, annotation analysis revealed the prevalence of inner ear transcripts represented by probe set identifiers that lack functional characterization. Conclusions We identified an abundance of targets for genetic analysis of auditory and vestibular function. The orthologues to human genes with known inner ear function and the highly expressed transcripts that lack annotation are particularly interesting candidates for future analyses. We used informatics approaches to impart biologically relevant information to the Xenopus inner ear transcriptome, thereby addressing the

  3. 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…

  4. 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. PMID:26601641

  5. 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. PMID:26931804

  6. Diffusion and association processes in biological systems: theory, computation and experiment

    PubMed Central

    2011-01-01

    Macromolecular diffusion plays a fundamental role in biological processes. Here, we give an overview of recent methodological advances and some of the challenges for understanding how molecular diffusional properties influence biological function that were highlighted at a recent workshop, BDBDB2, the second Biological Diffusion and Brownian Dynamics Brainstorm. PMID:21595997

  7. 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. PMID:20050264

  8. RASSF tumor suppressor gene family: biological functions and regulation.

    PubMed

    Volodko, Natalia; Gordon, Marilyn; Salla, Mohamed; Ghazaleh, Haya Abu; Baksh, Shairaz

    2014-08-19

    Genetic changes through allelic loss and nucleic acid or protein modifications are the main contributors to loss of function of tumor suppressor proteins. In particular, epigenetic silencing of genes by promoter hypermethylation is associated with increased tumor severity and poor survival. The RASSF (Ras association domain family) family of proteins consists of 10 members, many of which are tumor suppressor proteins that undergo loss of expression through promoter methylation in numerous types of cancers such as leukemia, melanoma, breast, prostate, neck, lung, brain, colorectal and kidney cancers. In addition to their tumor suppressor function, RASSF proteins act as scaffolding agents in microtubule stability, regulate mitotic cell division, modulate apoptosis, control cell migration and cell adhesion, and modulate NFκB activity and the duration of inflammation. The ubiquitous functions of these proteins highlight their importance in numerous physiological pathways. In this review, we will focus on the biological roles of the RASSF family members and their regulation. PMID:24607545

  9. 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

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

    PubMed

    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. PELP1: Structure, biological function and clinical significance.

    PubMed

    Sareddy, Gangadhara Reddy; Vadlamudi, Ratna K

    2016-07-01

    Proline-, glutamic acid-, and leucine-rich protein 1 (PELP1) is a scaffolding protein that functions as a coregulator of several transcription factors and nuclear receptors. Notably, the PELP1 protein has a histone-binding domain, recognizes histone modifications and interacts with several chromatin-modifying complexes. PELP1 serves as a substrate of multitude of kinases, and phosphorylation regulates its functions in various complexes. Further, PELP1 plays essential roles in several pathways including hormonal signaling, cell cycle progression, ribosomal biogenesis, and the DNA damage response. PELP1 expression is upregulated in several cancers, its deregulation contributes to therapy resistance, and it is a prognostic biomarker for breast cancer survival. Recent evidence suggests that PELP1 represents a novel therapeutic target for many hormonal cancers. In this review, we summarized the emerging biological properties and functions of PELP1. PMID:26997260

  12. 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.

  13. Some computational techniques for estimating human operator describing functions

    NASA Technical Reports Server (NTRS)

    Levison, W. H.

    1986-01-01

    Computational procedures for improving the reliability of human operator describing functions are described. Special attention is given to the estimation of standard errors associated with mean operator gain and phase shift as computed from an ensemble of experimental trials. This analysis pertains to experiments using sum-of-sines forcing functions. Both open-loop and closed-loop measurement environments are considered.

  14. 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…

  15. The Impact of Collective Molecular Dynamics on Physiological and Biological Functionalities of Artificial and Biological Membranes

    NASA Astrophysics Data System (ADS)

    Rheinstadter, Maikel

    2008-03-01

    We use neutron, X-ray and light scattering techniques to determine dynamical and structural properties of artificial and biological membranes. The combination of various techniques enlarges the window to length scales from the nearest-neighbor distances of lipid molecules to more than 10-6m, covering time scales from about 0.1 ps to 1 s. The main research objective is to quantify collective molecular fluctuations in these systems and to establish relationships to physiological and biological functions of the bilayers, such as transmembrane transport. The motivation for this project is twofold: 1) By understanding fundamental properties of bilayers at the microscopic and mesoscopic level, we aim to tailor membranes with specific properties such as permeability and elasticity. 2) By relating dynamical fluctuations to physiological and biological functions, we can gain a deeper understanding of the bilayers on a molecular scale that may help optimizing the transmembrane transport of certain drugs. We show how bilayer permeability, elasticity and inter protein excitations can be determined from the experiments. M.C. Rheinstädter et al., Phys. Rev. Lett. 93, 108107 (2004); Phys. Rev. Lett. 97, 048103 (2006); Phys. Rev. E 75, 011907 (2007);J. Vac. Soc. Technol. A 24, 1191 (2006).

  16. COMPUTER-ASSISTED STUDIES OF MOLECULAR STRUCTURE-BIOLOGICAL ACTIVITY RELATIONSHIPS

    EPA Science Inventory

    Computer-assisted methods can be used to investigate the relationships between the molecular structures of compounds and their biological activity. A number of approaches have been reported in the literature, including correlations of activity with substituent constants, conforma...

  17. Tubulin acetylation: responsible enzymes, biological functions and human diseases.

    PubMed

    Li, Lin; Yang, Xiang-Jiao

    2015-11-01

    Microtubules have important functions ranging from maintenance of cell morphology to subcellular transport, cellular signaling, cell migration, and formation of cell polarity. At the organismal level, microtubules are crucial for various biological processes, such as viral entry, inflammation, immunity, learning and memory in mammals. Microtubules are subject to various covalent modifications. One such modification is tubulin acetylation, which is associated with stable microtubules and conserved from protists to humans. In the past three decades, this reversible modification has been studied extensively. In mammals, its level is mainly governed by opposing actions of α-tubulin acetyltransferase 1 (ATAT1) and histone deacetylase 6 (HDAC6). Knockout studies of the mouse enzymes have yielded new insights into biological functions of tubulin acetylation. Abnormal levels of this modification are linked to neurological disorders, cancer, heart diseases and other pathological conditions, thereby yielding important therapeutic implications. This review summarizes related studies and concludes that tubulin acetylation is important for regulating microtubule architecture and maintaining microtubule integrity. Together with detyrosination, glutamylation and other modifications, tubulin acetylation may form a unique 'language' to regulate microtubule structure and function. PMID:26227334

  18. 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.

  19. Density functional theory across chemistry, physics and biology

    PubMed Central

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

    2014-01-01

    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. PMID:24516181

  20. 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. PMID:24516181

  1. Virtual Cell: computational tools for modeling in cell biology

    PubMed Central

    Resasco, Diana C.; Gao, Fei; Morgan, Frank; Novak, Igor L.; Schaff, James C.; Slepchenko, Boris M.

    2011-01-01

    The Virtual Cell (VCell) is a general computational framework for modeling physico-chemical and electrophysiological processes in living cells. Developed by the National Resource for Cell Analysis and Modeling at the University of Connecticut Health Center, it provides automated tools for simulating a wide range of cellular phenomena in space and time, both deterministically and stochastically. These computational tools allow one to couple electrophysiology and reaction kinetics with transport mechanisms, such as diffusion and directed transport, and map them onto spatial domains of various shapes, including irregular three-dimensional geometries derived from experimental images. In this article, we review new robust computational tools recently deployed in VCell for treating spatially resolved models. PMID:22139996

  2. 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.

  3. 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

  4. 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.

  5. Computational molecular biology approaches to ligand-target interactions

    PubMed Central

    Lupieri, Paola; Nguyen, Chuong Ha Hung; Bafghi, Zhaleh Ghaemi; Giorgetti, Alejandro; Carloni, Paolo

    2009-01-01

    Binding of small molecules to their targets triggers complex pathways. Computational approaches are keys for predictions of the molecular events involved in such cascades. Here we review current efforts at characterizing the molecular determinants in the largest membrane-bound receptor family, the G-protein-coupled receptors (GPCRs). We focus on odorant receptors, which constitute more than half GPCRs. The work presented in this review uncovers structural and energetic aspects of components of the cellular cascade. Finally, a computational approach in the context of radioactive boron-based antitumoral therapies is briefly described. PMID:20119480

  6. Develop Infrared Structural Biology for Probing Structural Dynamics of Protein Functions

    NASA Astrophysics Data System (ADS)

    Xie, Aihua; Kang, Zhouyang; Causey, Oliver; Liu, Charle

    2015-03-01

    Protein functions are carried out through a series of structural transitions. Lack of knowledge on functionally important structural motions of proteins impedes our understanding of protein functions. Infrared structural biology is an emerging technology with powerful applications for protein structural dynamics. One key element of infrared structural biology is the development of vibrational structural marker (VSM) database library that translates infrared spectroscopic signals into specific structural information. We report the development of VSM for probing the type, geometry and strength of hydrogen bonding interactions of buried COO- side chains of Asp and Glu in proteins. Quantum theory based first principle computational studies combined with bioinformatic hydrogen bond analysis are employed in this study. We will discuss the applications of VSM in mechanistic studies of protein functions. Infrared structural biology is expected to emerge as a powerful technique for elucidating the functional mechanism of a broad range of proteins, including water soluble and membrane proteins. This work is supported by OCAST HR10-078 and NSF DBI1338097.

  7. 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,…

  8. A Contribution of the Computer to Biology Education at the University.

    ERIC Educational Resources Information Center

    Anxolabehere, D.; And Others

    1980-01-01

    Described is part of the O.P.E. laboratory computer-based biology program designed for undergraduate medical and biology students. Described is an embryology dialogue in which the student proceeds through three stages in the knowledge and understanding of the concept of competence. (Author/DS)

  9. Functional magnetic resonance imaging for defining the biological target volume

    PubMed Central

    Kauczor, Hans-Ulrich; Zechmann, Christian; Stieltjes, Bram; Weber, Marc-Andre

    2006-01-01

    Morphology as demonstrated by CT is the basis for radiotherapy planning. Intensity-modulated and adaptive radiotherapy techniques would greatly benefit from additional functional information allowing for definition of the biological target volume. MRI techniques include several which can characterize and quantify different tissue properties and their tumour-related changes. Results of perfusion MRI represent microvascular density and permeability; MR spectroscopy depicts particular metabolites; diffusion weighted imaging shows tissue at risk and tumour cellularity; while dynamic 3D acquisition (4D MRI) shows organ motion and the mobility of tumours within them. PMID:16766269

  10. Structure and Biological Functions of β-Hairpin Antimicrobial Peptides

    PubMed Central

    Panteleev, P. V.; Bolosov, I. A.; Balandin, S. V.; Ovchinnikova, T. V.

    2015-01-01

    Antimicrobial peptides (AMPs) are evolutionarily ancient factors of the innate immune system that serve as a crucial first line of defense for humans, animals, and plants against infection. This review focuses on the structural organization, biosynthesis, and biological functions of AMPs that possess a β-hairpin spatial structure. Representatives of this class of AMPs are among the most active antibiotic molecules of animal origin. Due to their wide spectrum of activity and resistance to internal environmental factors, natural β-hairpin AMPbased compounds might become the most promising drug candidates. PMID:25927000