Science.gov

Sample records for computing biological functions

  1. Metacognition: computation, biology and function

    PubMed Central

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

    2012-01-01

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

  2. Metacognition: computation, biology and function.

    PubMed

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

    2012-05-19

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

  19. 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

  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. 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.

  11. 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

  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

    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 Central

    Moe-Behrens, Gerd HG

    2013-01-01

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

  16. 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. 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.

  11. 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

  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. 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.

  15. 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

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

    PubMed Central

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

    2013-01-01

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

  17. 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

  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. 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.

  5. 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.

  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. 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,…

  9. 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

  10. Biology Students Building Computer Simulations Using StarLogo TNG

    ERIC Educational Resources Information Center

    Smith, V. Anne; Duncan, Ishbel

    2011-01-01

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

  11. 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. 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

  12. 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.

  13. 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

  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. 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…

  18. [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

  19. 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

  20. 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

  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. 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

  5. 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

  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. 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

  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. 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

  17. 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

  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. 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

  2. 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

  3. 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

  4. 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

  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. 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.

  6. 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

  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. 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).

  9. 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

  10. 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.

  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. 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

  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. 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

  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. 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

  5. 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

  6. 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.

  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. 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…

  10. 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

  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. 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.

  15. 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.

  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. 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

  18. 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

  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

    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

  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. 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…

  3. 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

  4. 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

  5. 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

  6. 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

  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. 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

  9. 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

  10. Biomarkers of Aging: From Function to Molecular Biology

    PubMed Central

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

    2016-01-01

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

  11. 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. 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...

  16. 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).

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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)

  6. 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,…

  7. 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

  8. 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.

  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

  11. Functionalization of polydopamine coated magnetic nanoparticles with biological entities

    NASA Astrophysics Data System (ADS)

    Mǎgeruşan, Lidia; Mrówczyński, Radosław; Turcu, Rodica

    2015-12-01

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

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

    PubMed Central

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

    2015-01-01

    Speed is of the essence in combating Ebola; thus, computational approaches should form a significant component of Ebola research. As for the development of any modern drug, computational biology is uniquely positioned to contribute through comparative analysis of the genome sequences of Ebola strains as well as 3-D protein modeling. Other computational approaches to Ebola may include large-scale docking studies of Ebola proteins with human proteins and with small-molecule libraries, computational modeling of the spread of the virus, computational mining of the Ebola literature, and creation of a curated Ebola database. Taken together, such computational efforts could significantly accelerate traditional scientific approaches. In recognition of the need for important and immediate solutions from the field of computational biology against Ebola, the International Society for Computational Biology (ISCB) announces a prize for an important computational advance in fighting the Ebola virus. ISCB will confer the ISCB Fight against Ebola Award, along with a prize of US$2,000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology (ISMB) 2016, Orlando, Florida). PMID:26097686

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

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

    PubMed

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

    2015-11-01

    In the last two decades, computational tools for mass spectrometry-based proteomics data analysis have evolved from a few stand-alone software solutions serving specific goals, such as the identification of amino acid sequences based on mass spectrometry spectra, to large-scale complex pipelines integrating multiple computer programs to solve a collection of problems. This software evolution has been mostly driven by the appearance of novel technologies that allowed the community to tackle complex biological problems, such as the identification of proteins that are differentially expressed in two samples under different conditions. The achievement of such objectives requires a large suite of programs to analyze the intricate mass spectrometry data. Our laboratory addresses complex proteomics questions by producing and using algorithms and software packages. Our current computational pipeline includes, among other things, tools for mass spectrometry raw data processing, peptide and protein identification and quantification, post-translational modification analysis, and protein functional enrichment analysis. In this paper, we describe a suite of software packages we have developed to process mass spectrometry-based proteomics data and we highlight some of the new features of previously published programs as well as tools currently under development. Graphical Abstract ᅟ. PMID:26002791

  16. PrOnto database : GO term functional dissimilarity inferred from biological data

    PubMed Central

    Chapple, Charles E.; Herrmann, Carl; Brun, Christine

    2015-01-01

    Moonlighting proteins are defined by their involvement in multiple, unrelated functions. The computational prediction of such proteins requires a formal method of assessing the similarity of cellular processes, for example, by identifying dissimilar Gene Ontology terms. While many measures of Gene Ontology term similarity exist, most depend on abstract mathematical analyses of the structure of the GO tree and do not necessarily represent the underlying biology. Here, we propose two metrics of GO term functional dissimilarity derived from biological information, one based on the protein annotations and the other on the interactions between proteins. They have been collected in the PrOnto database, a novel tool which can be of particular use for the identification of moonlighting proteins. The database can be queried via an web-based interface which is freely available at http://tagc.univ-mrs.fr/pronto. PMID:26089836

  17. DEVELOPMENT OF COMPUTATIONAL TOOLS FOR OPTIMAL IDENTIFICATION OF BIOLOGICAL NETWORKS

    EPA Science Inventory

    Following the theoretical analysis and computer simulations, the next step for the development of SNIP will be a proof-of-principle laboratory application. Specifically, we have obtained a synthetic transcriptional cascade (harbored in Escherichia coli...

  18. An Introduction to Computer Assisted Analysis in the Biological Sciences.

    ERIC Educational Resources Information Center

    Banaugh, R. P.

    This set of notes is designed to introduce the student to the development and use of computer-based models, and to analyze quantitative phenomena in the life sciences. Only BASIC programming language is used. The ten chapter titles are: The Growth of a Single Species; The Association of Two Species; Parameter Determination; Automated Parameter…

  19. Suboptimal geometrical implantation of biological aortic valves provokes functional deficits.

    PubMed

    Kuehnel, Ralf-Uwe; Wendt, Max O; Jainski, Ute; Hartrumpf, Martin; Pohl, Manfred; Albes, Johannes M

    2010-06-01

    Endovascular valves have become a valid option for patients not qualifying for conventional surgery. Biological valves mounted in a stent are currently used. After implantation, however, geometrical distortion of the valve can occur. We tested whether biological valves suitable for transcatheter implantation exhibit hemodynamic deficits after deployment in a distorted position. Two types of valves [bovine pericardium (BP) and porcine cusps], of 21 and 23 mm diameter, respectively were investigated. Mean transvalvular gradient (TVG), effective orifice area (EOA), and regurgitation fraction (REG) were measured prior to and after the 20% distortion of the original diameter. All valves exhibited an increase of TVG and reduction of EOA whereas REG increased only in BP valves after distortion. The 21 mm valves demonstrated a more pronounced alteration than the 23 mm valves. Even moderately distorted implantation of a biological valve results in a marked functional alteration. The susceptibility of pericardial valves is higher than that of porcine valves probably owing to better coaptation properties of native cusps even under deformed conditions when compared to valves constructed with pericardium. Care should therefore be taken during implantation of endovascular valves in order to avoid fixed hemodynamic deficits. Native valves may preferably be used as they demonstrate a more robust behavior regarding suboptimal implantation. PMID:20233809

  20. Computer Center: 2 HyperCard Stacks for Biology.

    ERIC Educational Resources Information Center

    Duhrkopf, Richard, Ed.

    1989-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  2. Computational full electron structure study of biological activity in Cyclophilin A.

    PubMed

    Zhou, Wenjin; Rossetto, Allison M; Pang, Xiaodong; Zhou, Linxiang

    2016-01-01

    Cyclosporine (CsA) is widely used in organ transplant patients to help prevent the patient's body from rejecting the organ. CsA has been shown to be a safe and highly effective immunosuppressive drug that binds with the protein Cyclophilin A (CypA) at active sites. However, the exact mechanism of this binding at the molecular level remains unknown. In this project, we elucidate the binding of CsA to CypA at the molecular level by computing their electron structures and revealing their interactions. We employ a novel technique called electron Computer-Aided Drug Design (eCADD) on the protein's full electron structure along with its hydrophobic pocket and the perturbation theory of the interaction between two wave functions. We have identified the wave function of CypA, the biological active residues and active atoms of CypA and CsA, the interaction site between CypA and CsA, and the hydrogen bonds in the ligand CsA binding site. All these calculated active residues, active atoms, and hydrogen bonds are in good agreement with recorded laboratory experiments and provide guidelines for designing new ligands of CypA. We believe that our eCADD framework can provide researchers with a cost-efficient new method of drug design based on the full electron structure of proteins. PMID:26264861

  3. Towards human-computer synergetic analysis of large-scale biological data

    PubMed Central

    2013-01-01

    Background Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. Results In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user

  4. Basic mathematical function libraries for scientific computation

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1989-01-01

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

  5. The Computer and Its Functions; How to Communicate with the Computer.

    ERIC Educational Resources Information Center

    Ward, Peggy M.

    A brief discussion of why it is important for students to be familiar with computers and their functions and a list of some practical applications introduce this two-part paper. Focusing on how the computer works, the first part explains the various components of the computer, different kinds of memory storage devices, disk operating systems, and…

  6. Functions of microRNAs in cardiovascular biology and disease.

    PubMed

    Hata, Akiko

    2013-01-01

    In 1993, lin-4 was discovered as a critical modulator of temporal development in Caenorhabditis elegans and, most notably, as the first in the class of small, single-stranded noncoding RNAs now defined as microRNAs (miRNAs). Another eight years elapsed before miRNA expression was detected in mammalian cells. Since then, explosive advancements in the field of miRNA biology have elucidated the basic mechanism of miRNA biogenesis, regulation, and gene-regulatory function. The discovery of this new class of small RNAs has augmented the complexity of gene-regulatory programs as well as the understanding of developmental and pathological processes in the cardiovascular system. Indeed, the contributions of miRNAs in cardiovascular development and function have been widely explored, revealing the extensive role of these small regulatory RNAs in cardiovascular physiology. PMID:23157557

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

    NASA Astrophysics Data System (ADS)

    Guseo, Renato

    2016-12-01

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

  8. Current studies on physiological functions and biological production of lactosucrose.

    PubMed

    Mu, Wanmeng; Chen, Qiuming; Wang, Xiao; Zhang, Tao; Jiang, Bo

    2013-08-01

    Lactosucrose (O-β-D-galactopyranosyl-(1,4)-O-α-D-glucopyranosyl-(1,2)-β-D-fructofuranoside) is a trisaccharide formed from lactose and sucrose by enzymatic transglycosylation. This rare trisaccharide is a kind of indigestible carbohydrate, has good prebiotic effect, and promotes intestinal mineral absorption. It has been used as a functional ingredient in a range of food products which are approved as foods for specified health uses in Japan. Using lactose and sucrose as substrates, lactosucrose can be produced through transfructosylation by β-fructofuranosidase from Arthrobacter sp. K-1 or a range of levansucrases, or through transgalactosylation by β-galactosidase from Bacillus circulans. This article presented a review of recent studies on the physiological functions of lactosucrose and the biological production from lactose and sucrose by different enzymes. PMID:23828605

  9. Gold nanoparticles in model biological membranes: A computational perspective.

    PubMed

    Rossi, Giulia; Monticelli, Luca

    2016-10-01

    The electronic, optical, catalytic, and magnetic properties of metal nanoparticles (NPs) make them extremely interesting for biomedical applications. In this rapidly moving field, monolayer-protected gold nanoparticles emerge both as a reference system and as promising candidates for drug and gene delivery, photothermal treatment, and imaging applications. Despite the technological relevance, there is still poor understanding of the molecular processes driving the interactions of metal nanoparticles with cells, and with cell membranes in particular. In this paper we review molecular-level computational studies of the interaction between monolayer-protected gold NPs and model lipid membranes. Our review comprises a brief description of the most relevant experimental results in this field and of the questions they raised, followed by a description of the computational achievements reported so far. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg. PMID:27060434

  10. Computing the structural influence matrix for biological systems.

    PubMed

    Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

    2016-06-01

    We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics. PMID:26395779

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

    PubMed

    Sommer, Christoph; Gerlich, Daniel W

    2013-12-15

    Recent advances in microscope automation provide new opportunities for high-throughput cell biology, such as image-based screening. High-complex image analysis tasks often make the implementation of static and predefined processing rules a cumbersome effort. Machine-learning methods, instead, seek to use intrinsic data structure, as well as the expert annotations of biologists to infer models that can be used to solve versatile data analysis tasks. Here, we explain how machine-learning methods work and what needs to be considered for their successful application in cell biology. We outline how microscopy images can be converted into a data representation suitable for machine learning, and then introduce various state-of-the-art machine-learning algorithms, highlighting recent applications in image-based screening. Our Commentary aims to provide the biologist with a guide to the application of machine learning to microscopy assays and we therefore include extensive discussion on how to optimize experimental workflow as well as the data analysis pipeline. PMID:24259662

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

    PubMed

    Ananiadou, Sophia; Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B

    2015-05-01

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

  13. Sucrose metabolism gene families and their biological functions

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  15. A Descriptive Analysis of Computer-Assisted Teaching and Learning in Molecular Biological Education

    ERIC Educational Resources Information Center

    Li, Guangxing; Yin, Jiechao; Ren, Yudong; Wang, Binjie; Ren, Xiaofeng

    2006-01-01

    The role and importance of computer-assisted teaching and learning in molecular biological-related education and research has been emphasized and pinpointed. In this study, some benefit viewpoints and discussion are provided for applying the computer-assisted teaching and learning more efficiently in the process of knowledge acquisition and…

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

    ERIC Educational Resources Information Center

    Smolinski, Tomasz G.

    2010-01-01

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

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    ERIC Educational Resources Information Center

    Leiblum, M. D.; And Others

    1994-01-01

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

  19. Using Mathematics to Bridge the Gap between Biology and Computer Science

    ERIC Educational Resources Information Center

    Hammerman, Natalie; Tolvo, Anthony; Goldberg, Robert

    2004-01-01

    The rapid rate of expansion of the disciplines of biotechnology, genomics, and bioinformatics emphasizes the increased interdependency between computer science and biology, with mathematics serving as the bridge between these disciplines. This paper demonstrates this inter-relationship within the context of a computational model for a biological…

  20. Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)

    PubMed Central

    Waltemath, Dagmar; Bergmann, Frank T.; Chaouiya, Claudine; Czauderna, Tobias; Gleeson, Padraig; Goble, Carole; Golebiewski, Martin; Hucka, Michael; Juty, Nick; Krebs, Olga; Le Novère, Nicolas; Mi, Huaiyu; Moraru, Ion I.; Myers, Chris J.; Nickerson, David; Olivier, Brett G.; Rodriguez, Nicolas; Schreiber, Falk; Smith, Lucian; Zhang, Fengkai; Bonnet, Eric

    2014-01-01

    The Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of community standards and formats in computational systems biology and related fields. This report summarizes the topics and activities of the fourth edition of the annual COMBINE meeting, held in Paris during September 16-20 2013, and attended by a total of 96 people. This edition pioneered a first day devoted to modeling approaches in biology, which attracted a broad audience of scientists thanks to a panel of renowned speakers. During subsequent days, discussions were held on many subjects including the introduction of new features in the various COMBINE standards, new software tools that use the standards, and outreach efforts. Significant emphasis went into work on extensions of the SBML format, and also into community-building. This year’s edition once again demonstrated that the COMBINE community is thriving, and still manages to help coordinate activities between different standards in computational systems biology.

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

    PubMed

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

    2002-06-01

    The increase of information in biology makes it difficult for researchers in any field to keep current with the literature. The MEDLINE database of scientific abstracts can be quickly scanned using electronic mechanisms. Potentially interesting abstracts can be selected by matching words joined by Boolean operators. However this means of selecting documents is not optimal. Nonspecific queries have to be effected, resulting in large numbers of irrelevant abstracts that have to be manually scanned To facilitate this analysis, we have developed a system that compiles a summary of subjects and related documents on the results of a MEDLINE query. For this, we have applied a fuzzy binary relation formalism that deduces relations between words present in a set of abstracts preprocessed with a standard grammatical tagger. Those relations are used to derive ensembles of related words and their associated subsets of abstracts. The algorithm can be used publicly at http:// www.bork.embl-heidelberg.de/xplormed/. PMID:12074170

  2. Activation of PPARδ: from computer modelling to biological effects.

    PubMed

    Kahremany, Shirin; Livne, Ariela; Gruzman, Arie; Senderowitz, Hanoch; Sasson, Shlomo

    2015-02-01

    PPARδ is a ligand-activated receptor that dimerizes with another nuclear receptor of the retinoic acid receptor family. The dimers interact with other co-activator proteins and form active complexes that bind to PPAR response elements and promote transcription of genes involved in lipid metabolism. It appears that various natural fatty acids and their metabolites serve as endogenous activators of PPARδ; however, there is no consensus in the literature on the nature of the prime activators of the receptor. In vitro and cell-based assays of PPARδ activation by fatty acids and their derivatives often produce conflicting results. The search for synthetic and selective PPARδ agonists, which may be pharmacologically useful, is intense. Current rational modelling used to obtain such compounds relies mostly on crystal structures of synthetic PPARδ ligands with the recombinant ligand binding domain (LBD) of the receptor. Here, we introduce an original computational prediction model for ligand binding to PPARδ LBD. The model was built based on EC50 data of 16 ligands with available crystal structures and validated by calculating binding probabilities of 82 different natural and synthetic compounds from the literature. These compounds were independently tested in cell-free and cell-based assays for their capacity to bind or activate PPARδ, leading to prediction accuracy of between 70% and 93% (depending on ligand type). This new computational tool could therefore be used in the search for natural and synthetic agonists of the receptor. PMID:25255770

  3. Biological master games: using biologists' reasoning to guide algorithm development for integrated functional genomics.

    PubMed

    Breitling, Rainer; Herzyk, Pawel

    2005-01-01

    We review some powerful new algorithms that build on the intuitive biological interpretation techniques for statistical analysis of functional genomics experiments. Although they were originally designed for transcriptomics, we argue that these algorithms are applicable to any type of -omics study (transcriptomics, proteomics, metabolomics). Rank Products (RP), a strictly non-parametric test statistic to detect differentially regulated elements (genes, proteins, metabolites) in genome-wide screens. RP is particularly powerful for noisy data and low numbers of replicates and makes full use of the availability of a large number of parallel measurements that is typical of modern large-scale experiments. Iterative Group Analysis (iGA), a statistical method that makes the transition from regulated single elements to significant classes of elements, and thus provides an automatic functional annotation of an experiment. Graph-based iGA (GiGA), an extension of iGA that combines experimental data with a broad variety of biological annotations to highlight physiologically relevant regions in a given "evidence graph" (e.g., metabolic networks, signaling pathway diagrams, protein interaction maps). The sequential application of these techniques yields an increasingly abstract interpretation of experimental data that is at the same time quantitative, statistically rigorous, and biologically significant. The results can be used either as helpful tools to guide data visualization and exploration, or as the input for downstream computational applications in a systems biology framework. PMID:16209637

  4. Computational simulation of a new system modelling ions electromigration through biological membranes

    PubMed Central

    2013-01-01

    Background The interest in cell membrane has grown drastically for their important role as controllers of biological functions in health and illness. In fact most important physiological processes are intimately related to the transport ability of the membrane, such as cell adhesion, cell signaling and immune defense. Furthermore, ion migration is connected with life-threatening pathologies such as metastases and atherosclerosis. Consequently, a large amount of research is consecrated to this topic. To better understand cell membranes, more accurate models of ionic flux are required and also their computational simulations. Results This paper is presenting the numerical simulation of a more general system modelling ion migration through biological membranes. The model includes both the effects of biochemical reaction between ions and fixed charges. The model is a nonlinear coupled system. In the first we describe the mathematical model. To realize the numerical simulation of our model, we proceed by a finite element discretisation and then by choosing an appropriate resolution algorithm to the nonlinearities. Conclusions We give numerical simulations obtained for different popular models of enzymatic reaction which were compared to those obtained in literature on systems of ordinary differential equations. The results obtained show a complete agreement between the two modellings. Furthermore, various numerical experiments are presented to confirm the accuracy, efficiency and stability of the proposed method. In particular, we show that the scheme is unconditionally stable and second-order accurate in space. PMID:24010551

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

    PubMed

    Geurts, Pierre; Irrthum, Alexandre; Wehenkel, Louis

    2009-12-01

    At the intersection between artificial intelligence and statistics, supervised learning allows algorithms to automatically build predictive models from just observations of a system. During the last twenty years, supervised learning has been a tool of choice to analyze the always increasing and complexifying data generated in the context of molecular biology, with successful applications in genome annotation, function prediction, or biomarker discovery. Among supervised learning methods, decision tree-based methods stand out as non parametric methods that have the unique feature of combining interpretability, efficiency, and, when used in ensembles of trees, excellent accuracy. The goal of this paper is to provide an accessible and comprehensive introduction to this class of methods. The first part of the review is devoted to an intuitive but complete description of decision tree-based methods and a discussion of their strengths and limitations with respect to other supervised learning methods. The second part of the review provides a survey of their applications in the context of computational and systems biology. PMID:20023720

  6. Inaccuracies of trigonometric functions in computer mathematical libraries

    NASA Astrophysics Data System (ADS)

    Ito, Takashi; Kojima, Sadamu

    Recent progress in the development of high speed computers has enabled us to perform larger and faster numerical experiments in astronomy. However, sometimes the high speed of numerical computation is achieved at the cost of accuracy. In this paper we show an example of accuracy loss by some mathematical functions on certain computer platforms in Astronomical Data Analysis Center, National Astronomical Observatory of Japan. We focus in particular on the numerical inaccuracy in sine and cosine functions, demonstrating how accuracy deterioration emerges. We also describe the measures that we have so far taken against these numerical inaccuracies. In general, computer vendors are not eager to improve the numerical accuracy in the mathematical libraries that they are supposed to be responsible for. Therefore scientists have to be aware of the existence of numerical inaccuracies, and protect their computational results from contamination by the potential errors that many computer platforms inherently contain.

  7. Computational biology in anti-tuberculosis drug discovery.

    PubMed

    Murphy, Dennis J; Brown, James R

    2009-06-01

    The resurgence of drug resistant tuberculosis (TB) is a major global healthcare problem. Mycobacterium tuberculosis (MTB), TB's causative agent, evades the host immune system and drug regimes by entering prolonged periods of nonproliferation or dormancy. The identification of genes essential to the bacterium in its dormancy phase infections is a key strategy in the development of new anti-TB therapeutics. The rapid expansion of TB-related genomic data sources including DNA sequences, transcriptomic and proteomic profiles, and genome-wide essentiality data, present considerable opportunities to apply advanced computational analyses to predict potential drug targets. However, the translation of in silico predictions to effective clinical therapies remains a significant challenge. PMID:19519485

  8. Examining Functions in Mathematics and Science Using Computer Interfacing.

    ERIC Educational Resources Information Center

    Walton, Karen Doyle

    1988-01-01

    Introduces microcomputer interfacing as a method for explaining and demonstrating various aspects of the concept of function. Provides three experiments with illustrations and typical computer graphic displays: pendulum motion, pendulum study using two pendulums, and heat absorption and radiation. (YP)

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

    PubMed Central

    Davey, Rachel A; Grossmann, Mathis

    2016-01-01

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

  10. AFM imaging of functionalized carbon nanotubes on biological membranes

    NASA Astrophysics Data System (ADS)

    Lamprecht, C.; Liashkovich, I.; Neves, V.; Danzberger, J.; Heister, E.; Rangl, M.; Coley, H. M.; McFadden, J.; Flahaut, E.; Gruber, H. J.; Hinterdorfer, P.; Kienberger, F.; Ebner, A.

    2009-10-01

    Multifunctional carbon nanotubes are promising for biomedical applications as their nano-size, together with their physical stability, gives access into the cell and various cellular compartments including the nucleus. However, the direct and label-free detection of carbon nanotube uptake into cells is a challenging task. The atomic force microscope (AFM) is capable of resolving details of cellular surfaces at the nanometer scale and thus allows following of the docking of carbon nanotubes to biological membranes. Here we present topographical AFM images of non-covalently functionalized single walled (SWNT) and double walled carbon nanotubes (DWNT) immobilized on different biological membranes, such as plasma membranes and nuclear envelopes, as well as on a monolayer of avidin molecules. We were able to visualize DWNT on the nuclear membrane while at the same time resolving individual nuclear pore complexes. Furthermore, we succeeded in localizing individual SWNT at the border of incubated cells and in identifying bundles of DWNT on cell surfaces by AFM imaging.

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

    SciTech Connect

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

    2005-01-01

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

  12. Linking biological soil crust diversity to ecological functions

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Genome-wide survey for biologically functional pseudogenes.

    PubMed

    Svensson, Orjan; Arvestad, Lars; Lagergren, Jens

    2006-05-01

    According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human-mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i.e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human-mouse species split, and also a larger group of primate-specific ones found from human-chimpanzee searches. Two processed sequences are notable, their conservation since the human-mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7-like 3 (ATX7NL3), and one from the Spinocerebellar ataxia type 1 protein (ATX1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in-frame disablements, as well as a probabilistic filter based on Ka/Ks ratios. PMID:16680195

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

    PubMed Central

    de Souza, Amancio José; Pauly, Markus

    2015-01-01

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

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

    PubMed

    de Souza, Amancio José; Pauly, Markus

    2015-01-01

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

  16. Update on the functional biology of Lrrk2.

    PubMed

    Melrose, Heather

    2008-01-01

    The etiology of Parkinson's disease (PD) was long thought to be due to environmental factors. Following the discovery of autosomal-dominant mutations in the α-synuclein gene, and later recessive mutations in the DJ-1, Parkin and PINK-1 genes, the field of PD genetics exploded. In 2004, it was discovered that mutations in the PARK8 locus - leucine-rich repeat kinase 2 (LRRK2, Lrrk2) - are the most important genetic cause of autosomal-dominant PD. Lrrk2 substitutions also account for sporadic PD in certain ethnic populations and have been shown to increase the risk of PD in Asian populations. Drug therapies targeting Lrrk2 activity may therefore be beneficial to both familial and sporadic PD patients, hence understanding the role of Lrrk2 in health and disease is critical. This review aims to highlight the research effort concentrated on elucidating the functional biological role of Lrrk2, and to provide some future therapeutic perspectives. PMID:19225574

  17. Biochemical Properties and Biological Functions of FET Proteins.

    PubMed

    Schwartz, Jacob C; Cech, Thomas R; Parker, Roy R

    2015-01-01

    Members of the FET protein family, consisting of FUS, EWSR1, and TAF15, bind to RNA and contribute to the control of transcription, RNA processing, and the cytoplasmic fates of messenger RNAs in metazoa. FET proteins can also bind DNA, which may be important in transcription and DNA damage responses. FET proteins are of medical interest because chromosomal rearrangements of their genes promote various sarcomas and because point mutations in FUS or TAF15 can cause neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal lobar dementia. Recent results suggest that both the normal and pathological effects of FET proteins are modulated by low-complexity or prion-like domains, which can form higher-order assemblies with novel interaction properties. Herein, we review FET proteins with an emphasis on how the biochemical properties of FET proteins may relate to their biological functions and to pathogenesis. PMID:25494299

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

    NASA Technical Reports Server (NTRS)

    Ross, Muriel D.

    1991-01-01

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

  19. Persistence and Availability of Web Services in Computational Biology

    PubMed Central

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

    2011-01-01

    We have conducted a study on the long-term availability of bioinformatics Web services: an observation of 927 Web services published in the annual Nucleic Acids Research Web Server Issues between 2003 and 2009. We found that 72% of Web sites are still available at the published addresses, only 9% of services are completely unavailable. Older addresses often redirect to new pages. We checked the functionality of all available services: for 33%, we could not test functionality because there was no example data or a related problem; 13% were truly no longer working as expected; we could positively confirm functionality only for 45% of all services. Additionally, we conducted a survey among 872 Web Server Issue corresponding authors; 274 replied. 78% of all respondents indicate their services have been developed solely by students and researchers without a permanent position. Consequently, these services are in danger of falling into disrepair after the original developers move to another institution, and indeed, for 24% of services, there is no plan for maintenance, according to the respondents. We introduce a Web service quality scoring system that correlates with the number of citations: services with a high score are cited 1.8 times more often than low-scoring services. We have identified key characteristics that are predictive of a service's survival, providing reviewers, editors, and Web service developers with the means to assess or improve Web services. A Web service conforming to these criteria receives more citations and provides more reliable service for its users. The most effective way of ensuring continued access to a service is a persistent Web address, offered either by the publishing journal, or created on the authors' own initiative, for example at http://bioweb.me. The community would benefit the most from a policy requiring any source code needed to reproduce results to be deposited in a public repository. PMID:21966383

  20. Integration of multiscale dendritic spine structure and function data into systems biology models

    PubMed Central

    Mancuso, James J.; Cheng, Jie; Yin, Zheng; Gilliam, Jared C.; Xia, Xiaofeng; Li, Xuping; Wong, Stephen T. C.

    2014-01-01

    Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement. PMID:25429262

  1. Multiscale computational models in physical systems biology of intracellular trafficking

    PubMed Central

    Tourdot, Richard W.; Bradley, Ryan P.; Ramakrishnan, Natesan

    2015-01-01

    In intracellular trafficking, a definitive understanding of the interplay between protein binding and membrane morphology remains incomplete. The authors describe a computational approach by integrating coarse-grained molecular dynamics (CGMD) simulations with continuum Monte Carlo (CM) simulations of the membrane to study protein–membrane interactions and the ensuing membrane curvature. They relate the curvature field strength discerned from the molecular level to its effect at the cellular length-scale. They perform thermodynamic integration on the CM model to describe the free energy landscape of vesiculation in clathrin-mediated endocytosis. The method presented here delineates membrane morphologies and maps out the free energy changes associated with membrane remodeling due to varying coat sizes, coat curvature strengths, membrane bending rigidities, and tensions; furthermore several constraints on mechanisms underlying clathrin-mediated endocytosis have also been identified, Their CGMD simulations have revealed the importance of PIP2 for stable binding of proteins essential for curvature induction in the bilayer and have provided a molecular basis for the positive curvature induction by the epsin N-terminal homology (EIMTH) domain. Calculation of the free energy landscape for vesicle budding has identified the critical size and curvature strength of a clathrin coat required for nucleation and stabilisation of a mature vesicle. PMID:25257021

  2. Functionalized nanoparticles for biological imaging and detection applications

    NASA Astrophysics Data System (ADS)

    Mei, Bing C.

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

  3. Computing Health Quality Measures Using Informatics for Integrating Biology and the Bedside

    PubMed Central

    Murphy, Shawn N

    2013-01-01

    Background The Health Quality Measures Format (HQMF) is a Health Level 7 (HL7) standard for expressing computable Clinical Quality Measures (CQMs). Creating tools to process HQMF queries in clinical databases will become increasingly important as the United States moves forward with its Health Information Technology Strategic Plan to Stages 2 and 3 of the Meaningful Use incentive program (MU2 and MU3). Informatics for Integrating Biology and the Bedside (i2b2) is one of the analytical databases used as part of the Office of the National Coordinator (ONC)’s Query Health platform to move toward this goal. Objective Our goal is to integrate i2b2 with the Query Health HQMF architecture, to prepare for other HQMF use-cases (such as MU2 and MU3), and to articulate the functional overlap between i2b2 and HQMF. Therefore, we analyze the structure of HQMF, and then we apply this understanding to HQMF computation on the i2b2 clinical analytical database platform. Specifically, we develop a translator between two query languages, HQMF and i2b2, so that the i2b2 platform can compute HQMF queries. Methods We use the HQMF structure of queries for aggregate reporting, which define clinical data elements and the temporal and logical relationships between them. We use the i2b2 XML format, which allows flexible querying of a complex clinical data repository in an easy-to-understand domain-specific language. Results The translator can represent nearly any i2b2-XML query as HQMF and execute in i2b2 nearly any HQMF query expressible in i2b2-XML. This translator is part of the freely available reference implementation of the QueryHealth initiative. We analyze limitations of the conversion and find it covers many, but not all, of the complex temporal and logical operators required by quality measures. Conclusions HQMF is an expressive language for defining quality measures, and it will be important to understand and implement for CQM computation, in both meaningful use and population

  4. Functional Skeletal Muscle Formation with a Biologic Scaffold

    PubMed Central

    Valentin, Jolene E.; Turner, Neill J.; Gilbert, Thomas W.; Badylak, Stephen F.

    2010-01-01

    Biologic scaffolds composed of extracellular matrix (ECM) have been used to reinforce or replace damaged or missing musculotendinous tissues in both preclinical studies and in human clinical applications. However, most studies have focused upon morphologic endpoints and few studies have assessed the in-situ functionality of newly formed tissue; especially new skeletal muscle tissue. The objective of the present study was to determine both the in-situ tetanic contractile response and histomorphologic characteristics of skeletal muscle tissue reconstructed using one of four test articles in a rodent abdominal wall model: 1) porcine small intestinal submucosa (SIS)-ECM; 2) carbodiimide-crosslinked porcine SIS-ECM; 3) autologous tissue; or 4) polypropylene mesh. Six months after surgery, the remodeled SIS-ECM showed almost complete replacement by islands and sheets of skeletal muscle, which generated a similar maximal contractile force to native tissue but with greater resistance to fatigue. The autologous tissue graft was replaced by a mixture of collagenous connective tissue, adipose tissue with fewer islands of skeletal muscle compared to SIS-ECM and a similar fatigue resistance to native muscle. Carbodiimide-crosslinked SIS-ECM and polypropylene mesh were characterized by a chronic inflammatory response and produced little or no measureable tetanic force. The findings of this study show that non-crosslinked xenogeneic SIS scaffolds and autologous tissue are associated with the restoration of functional skeletal muscle with histomorphologic characteristics that resemble native muscle. PMID:20638716

  5. Steroid receptor RNA activator: Biologic function and role in disease.

    PubMed

    Liu, Chan; Wu, Hong-Tao; Zhu, Neng; Shi, Ya-Ning; Liu, Zheng; Ao, Bao-Xue; Liao, Duan-Fang; Zheng, Xi-Long; Qin, Li

    2016-08-01

    Steroid receptor RNA activator (SRA) is a type of long noncoding RNA (lncRNA) which coordinates the functions of various transcription factors, enhances steroid receptor-dependent gene expression, and also serves as a distinct scaffold. The novel, profound and expanded roles of SRA are emerging in critical aspects of coactivation of nuclear receptors (NRs). As a nuclear receptor coactivator, SRA can coactivate androgen receptor (AR), estrogen receptor α (ERα), ERβ, progesterone receptor (PR), glucocorticoid receptor (GR), thyroid hormone receptor and retinoic acid receptor (RAR). Although SRA is one of the least well-understood molecules, increasing studies have revealed that SRA plays a key role in both biological processes, such as myogenesis and steroidogenesis, and pathological changes, including obesity, cardiomyopathy, and tumorigenesis. Furthermore, the SRA-related signaling pathways, such as the mitogen-activated protein kinase (p38 MAPK), Notch and tumor necrosis factor α (TNFα) pathways, play critical roles in the pathogenesis of estrogen-dependent breast cancers. In addition, the most recent data demonstrates that SRA expression may serve as a new prognostic marker in patients with ER-positive breast cancer. Thus, elucidating the molecular mechanisms underlying SRA-mediated functions is important to develop proper novel strategies to target SRA in the diagnosis and treatment of human diseases. PMID:27282881

  6. Polysaccharide Immunomodulators as Therapeutic Agents: Structural Aspects and Biologic Function

    PubMed Central

    Tzianabos, Arthur O.

    2000-01-01

    Polysaccharide immunomodulators were first discovered over 40 years ago. Although very few have been rigorously studied, recent reports have revealed the mechanism of action and structure-function attributes of some of these molecules. Certain polysaccharide immunomodulators have been identified that have profound effects in the regulation of immune responses during the progression of infectious diseases, and studies have begun to define structural aspects of these molecules that govern their function and interaction with cells of the host immune system. These polymers can influence innate and cell-mediated immunity through interactions with T cells, monocytes, macrophages, and polymorphonuclear lymphocytes. The ability to modulate the immune response in an appropriate way can enhance the host's immune response to certain infections. In addition, this strategy can be utilized to augment current treatment regimens such as antimicrobial therapy that are becoming less efficacious with the advent of antibiotic resistance. This review focuses on recent studies that illustrate the structural and biologic activities of specific polysaccharide immunomodulators and outlines their potential for clinical use. PMID:11023954

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

    ERIC Educational Resources Information Center

    O'Callaghan, Brian R.

    1998-01-01

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

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

    SciTech Connect

    Wallace, Susan S.

    2008-02-21

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

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

    PubMed Central

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

    2008-01-01

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

  10. Optical scattering by biological aerosols: experimental and computational results on spore simulants

    NASA Astrophysics Data System (ADS)

    Sindoni, Orazio I.; Saija, Rosalba; Iatì, Maria Antonia; Borghese, Ferdinando; Denti, Paolo; Fernandes, Gustavo E.; Pan, Yong-Le; Chang, Richard K.

    2006-07-01

    We present both a computational and an experimental approach to the problem of biological aerosol characterization, joining the expertises reached in the field of theoretical optical scattering by complex, arbitrary shaped particles (multipole expansion of the electromagnetic fields and Transition Matrix), and a novel experimental technique based on two-dimensional angular optical scattering (TAOS). The good agreement between experimental and computational results, together with the possibility for a laboratory single-particle angle-resolved investigation, opens a new scenario in biological particle modelling, and might have major implications for a rapid discrimination of airborne particles.

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

    PubMed

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

    2004-06-01

    Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today. PMID:17052114

  12. Convergence rate for numerical computation of the lattice Green's function.

    PubMed

    Ghazisaeidi, M; Trinkle, D R

    2009-03-01

    Flexible boundary-condition methods couple an isolated defect to bulk through the bulk lattice Green's function. Direct computation of the lattice Green's function requires projecting out the singular subspace of uniform displacements and forces for the infinite lattice. We calculate the convergence rates for elastically isotropic and anisotropic cases for three different techniques: relative displacement, elastic Green's function correction, and discontinuity correction. The discontinuity correction has the most rapid convergence for the general case. PMID:19392089

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

    PubMed

    Lace, Beatrice; Prandi, Cristina

    2016-08-01

    Modern biology overlaps with chemistry in explaining the structure and function of all cellular processes at the molecular level. Plant hormone research is perfectly located at the interface between these two disciplines, taking advantage of synthetic and computational chemistry as a tool to decipher the complex biological mechanisms regulating the action of plant hormones. These small signaling molecules regulate a wide range of developmental processes, adapting plant growth to ever changing environmental conditions. The synthesis of small bioactive molecules mimicking the activity of endogenous hormones allows us to unveil many molecular features of their functioning, giving rise to a new field, plant chemical biology. In this framework, fluorescence labeling of plant hormones is emerging as a successful strategy to track the fate of these challenging molecules inside living organisms. Thanks to the increasing availability of new fluorescent probes as well as advanced and innovative imaging technologies, we are now in a position to investigate many of the dynamic mechanisms through which plant hormones exert their action. Such a deep and detailed comprehension is mandatory for the development of new green technologies for practical applications. In this review, we summarize the results obtained so far concerning the fluorescent labeling of plant hormones, highlighting the basic steps leading to the design and synthesis of these compelling molecular tools and their applications. PMID:27378726

  14. The Lung Physiome: merging imaging-based measures with predictive computational models of structure and function

    PubMed Central

    Tawhai, Merryn H; Hoffman, Eric A; Lin, Ching-Long

    2009-01-01

    Global measurements of the lung provided by standard pulmonary function tests do not give insight into the regional basis of lung function and lung disease. Advances in imaging methodologies, computer technologies, and subject-specific simulations are creating new opportunities for studying structure-function relationships in the lung through multi-disciplinary research. The digital Human Lung Atlas is an imaging-based resource compiled from male and female subjects spanning several decades of age. The Atlas comprises both structural and functional measures, and includes computational models derived to match individual subjects for personalized prediction of function. The computational models in the Atlas form part of the Lung Physiome project, which is an international effort to develop integrative models of lung function at all levels of biological organization. The computational models provide mechanistic interpretation of imaging measures; the Atlas provides structural data upon which to base model geometry, and functional data against which to test hypotheses. The example of simulating air flow on a subject-specific basis is considered. Methods for deriving multi-scale models of the airway geometry for individual subjects in the Atlas are outlined, and methods for modeling turbulent flows in the airway are reviewed. PMID:20835982

  15. Functional Analysis beyond Enrichment: Non-Redundant Reciprocal Linkage of Genes and Biological Terms

    PubMed Central

    Pascual-Montano, Alberto; De Las Rivas, Javier

    2011-01-01

    Functional analysis of large sets of genes and proteins is becoming more and more necessary with the increase of experimental biomolecular data at omic-scale. Enrichment analysis is by far the most popular available methodology to derive functional implications of sets of cooperating genes. The problem with these techniques relies in the redundancy of resulting information, that in most cases generate lots of trivial results with high risk to mask the reality of key biological events. We present and describe a computational method, called GeneTerm Linker, that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. The algorithm is tested with a small set of well known interacting proteins from yeast and with a large collection of reference sets from three heterogeneous resources: multiprotein complexes (CORUM), cellular pathways (SGD) and human diseases (OMIM). Statistical Precision, Recall and balanced F-score are calculated showing robust results, even when different levels of random noise are included in the test sets. Although we could not find an equivalent method, we present a comparative analysis with a widely used method that combines enrichment and functional annotation clustering. A web application to use the method here proposed is provided at http://gtlinker.cnb.csic.es. PMID:21949701

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

    NASA Astrophysics Data System (ADS)

    Meng, Linghui

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

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

    ERIC Educational Resources Information Center

    Nayark, Ajitha K.; Barker, Miles

    2014-01-01

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

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

    EPA Science Inventory

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

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

    ERIC Educational Resources Information Center

    Duffy, Maryellen; Barowy, William

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

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

    ERIC Educational Resources Information Center

    Yusuf, Mudasiru Olalere; Afolabi, Adedeji Olufemi

    2010-01-01

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

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

    SciTech Connect

    Hansmann, Ulrich H.E.

    2012-07-02

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

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  3. RESEARCH STRATEGIES FOR THE APPLICATION OF THE TECHNIQUES OF COMPUTATIONAL BIOLOGICAL CHEMISTRY TO ENVIRONMENTAL PROBLEMS

    EPA Science Inventory

    On October 25 and 26, 1984, the U.S. EPA sponsored a workshop to consider the potential applications of the techniques of computational biological chemistry to problems in environmental health. Eleven extramural scientists from the various related disciplines and a similar number...

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

    ERIC Educational Resources Information Center

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

    2002-01-01

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

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

    PubMed Central

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

    2000-01-01

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

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

    PubMed

    November, Joseph

    2011-06-01

    This article shows how the USA's National Institutes of Health (NIH) helped to bring about a major shift in the way computers are used to produce knowledge and in the design of computers themselves as a consequence of its early 1960s efforts to introduce information technology to biologists. Starting in 1960 the NIH sought to reform the life sciences by encouraging researchers to make use of digital electronic computers, but despite generous federal support biologists generally did not embrace the new technology. Initially the blame fell on biologists' lack of appropriate (i.e. digital) data for computers to process. However, when the NIH consulted MIT computer architect Wesley Clark about this problem, he argued that the computer's quality as a device that was centralized posed an even greater challenge to potential biologist users than did the computer's need for digital data. Clark convinced the NIH that if the agency hoped to effectively computerize biology, it would need to satisfy biologists' experimental and institutional needs by providing them the means to use a computer without going to a computing center. With NIH support, Clark developed the 1963 Laboratory Instrument Computer (LINC), a small, real-time interactive computer intended to be used inside the laboratory and controlled entirely by its biologist users. Once built, the LINC provided a viable alternative to the 1960s norm of large computers housed in computing centers. As such, the LINC not only became popular among biologists, but also served in later decades as an important precursor of today's computing norm in the sciences and far beyond, the personal computer. PMID:21879517

  7. Applications of the Aurora parallel Prolog system to computational molecular biology

    SciTech Connect

    Lusk, E.L.; Overbeek, R.; Mudambi, S.; Szeredi, P.

    1993-09-01

    We describe an investigation into the use of the Aurora parallel Prolog system in two applications within the area of computational molecular biology. The computational requirements were large, due to the nature of the applications, and were large, due to the nature of the applications, and were carried out on a scalable parallel computer the BBN ``Butterfly`` TC-2000. Results include both a demonstration that logic programming can be effective in the context of demanding applications on large-scale parallel machines, and some insights into parallel programming in Prolog.

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

    PubMed

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

    2016-01-01

    The ascent of polypharmacology in drug development has many implications for disease therapy, most notably in the efforts of drug discovery, drug repositioning, precision medicine and combination therapy. The single- target approach to drug development has encountered difficulties in predicting drugs that are both clinically efficacious and avoid toxicity. By contrast, polypharmacology offers the possibility of a controlled distribution of effects on a biological system. This review addresses possibilities and bottlenecks in the efficient computational application of polypharmacology. The two major areas we address are the discovery and prediction of multiple protein targets using the tools of computer-aided drug design, and the use of these protein targets in predicting therapeutic potential in the context of biological networks. The successful application of polypharmacology to systems biology and pharmacology has the potential to markedly accelerate the pace of development of novel therapies for multiple diseases, and has implications for the intellectual property landscape, likely requiring targeted changes in patent law. PMID:26907947

  9. Wigner Function Negativity and Contextuality in Quantum Computation on Rebits

    NASA Astrophysics Data System (ADS)

    Delfosse, Nicolas; Allard Guerin, Philippe; Bian, Jacob; Raussendorf, Robert

    2015-04-01

    We describe a universal scheme of quantum computation by state injection on rebits (states with real density matrices). For this scheme, we establish contextuality and Wigner function negativity as computational resources, extending results of M. Howard et al. [Nature (London) 510, 351 (2014), 10.1038/nature13460] to two-level systems. For this purpose, we define a Wigner function suited to systems of n rebits and prove a corresponding discrete Hudson's theorem. We introduce contextuality witnesses for rebit states and discuss the compatibility of our result with state-independent contextuality.

  10. Computer method for identification of boiler transfer functions

    NASA Technical Reports Server (NTRS)

    Miles, J. H.

    1971-01-01

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

  11. A primer on molecular biology for imagers: III. Proteins: structure and function.

    PubMed

    Pandit, Sunil D; Li, King C P

    2004-04-01

    This article along with the first 2 in this series (4,12) completes the discussion on the key molecules and process inside the cell namely, DNA, RNA, and proteins. These 3 articles provide a very basic foundation for understanding molecular biology concepts and summarize some of the work of numerous scientists over the past century. We understand these processes far better now than we did in the past, but clearly this knowledge is by no means complete and a number of basic scientists are working hard to elucidate and understand the fundamental mechanisms that operate within a cell. Genes and gene products work with each other in complex, interconnected pathways, and in perfect harmony to make a functional cell, tissue, and an organism as a whole. There is a lot of cross-talk that happens between different proteins that interact with various other proteins, DNA, and RNA to establish pathways, networks, and molecular systems as a team working to perfection. The past 15 years have seen the rapid development of systems biology approaches. We live in an era that emphasizes multi-disciplinary, cross-functional teams to perform science rather than individual researchers working on the bench on a very specific problem. Global approaches have become more common and the amount of data generated must be managed by trained bioinformatics personnel and large computers. In our subsequent articles, we will discuss these global approaches and the areas of genomics, functional genomics, and proteomics that have revolutionized the way we perform science. PMID:15109017

  12. Phytochrome from Green Plants: Properties and biological Function

    SciTech Connect

    Quail, Peter H.

    2014-07-25

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

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

    PubMed

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

    2013-05-23

    As computing devices, which process data and interconvert information, transducers can encode new information and use their output for subsequent computing, offering high computational power that may be equivalent to a universal Turing machine. We report on an experimental DNA-based molecular transducer that computes iteratively and produces biologically relevant outputs. As a proof of concept, the transducer accomplished division of numbers by 3. The iterative power was demonstrated by a recursive application on an obtained output. This device reads plasmids as input and processes the information according to a predetermined algorithm, which is represented by molecular software. The device writes new information on the plasmid using hardware that comprises DNA-manipulating enzymes. The computation produces dual output: a quotient, represented by newly encoded DNA, and a remainder, represented by E. coli phenotypes. This device algorithmically manipulates genetic codes. PMID:23706637

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

    PubMed Central

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

    2013-01-01

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

  15. The flight telerobotic servicer: From functional architecture to computer architecture

    NASA Technical Reports Server (NTRS)

    Lumia, Ronald; Fiala, John

    1989-01-01

    After a brief tutorial on the NASA/National Bureau of Standards Standard Reference Model for Telerobot Control System Architecture (NASREM) functional architecture, the approach to its implementation is shown. First, interfaces must be defined which are capable of supporting the known algorithms. This is illustrated by considering the interfaces required for the SERVO level of the NASREM functional architecture. After interface definition, the specific computer architecture for the implementation must be determined. This choice is obviously technology dependent. An example illustrating one possible mapping of the NASREM functional architecture to a particular set of computers which implements it is shown. The result of choosing the NASREM functional architecture is that it provides a technology independent paradigm which can be mapped into a technology dependent implementation capable of evolving with technology in the laboratory and in space.

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

    PubMed

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

    2013-03-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools. PMID:23353650

  17. Quantum Computing Without Wavefunctions: Time-Dependent Density Functional Theory for Universal Quantum Computation

    PubMed Central

    Tempel, David G.; Aspuru-Guzik, Alán

    2012-01-01

    We prove that the theorems of TDDFT can be extended to a class of qubit Hamiltonians that are universal for quantum computation. The theorems of TDDFT applied to universal Hamiltonians imply that single-qubit expectation values can be used as the basic variables in quantum computation and information theory, rather than wavefunctions. From a practical standpoint this opens the possibility of approximating observables of interest in quantum computations directly in terms of single-qubit quantities (i.e. as density functionals). Additionally, we also demonstrate that TDDFT provides an exact prescription for simulating universal Hamiltonians with other universal Hamiltonians that have different, and possibly easier-to-realize two-qubit interactions. This establishes the foundations of TDDFT for quantum computation and opens the possibility of developing density functionals for use in quantum algorithms. PMID:22553483

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

    PubMed

    Tempel, David G; Aspuru-Guzik, Alán

    2012-01-01

    We prove that the theorems of TDDFT can be extended to a class of qubit Hamiltonians that are universal for quantum computation. The theorems of TDDFT applied to universal Hamiltonians imply that single-qubit expectation values can be used as the basic variables in quantum computation and information theory, rather than wavefunctions. From a practical standpoint this opens the possibility of approximating observables of interest in quantum computations directly in terms of single-qubit quantities (i.e. as density functionals). Additionally, we also demonstrate that TDDFT provides an exact prescription for simulating universal Hamiltonians with other universal Hamiltonians that have different, and possibly easier-to-realize two-qubit interactions. This establishes the foundations of TDDFT for quantum computation and opens the possibility of developing density functionals for use in quantum algorithms. PMID:22553483

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

    NASA Technical Reports Server (NTRS)

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

    1970-01-01

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

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

    SciTech Connect

    Norgard, G; Bremer, P T

    2010-11-30

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

  1. A general framework for application of prestrain to computational models of biological materials.

    PubMed

    Maas, Steve A; Erdemir, Ahmet; Halloran, Jason P; Weiss, Jeffrey A

    2016-08-01

    It is often important to include prestress in computational models of biological tissues. The prestress can represent residual stresses (stresses that exist after the tissue is excised from the body) or in situ stresses (stresses that exist in vivo, in the absence of loading). A prestressed reference configuration may also be needed when modeling the reference geometry of biological tissues in vivo. This research developed a general framework for representing prestress in finite element models of biological materials. It is assumed that the material is elastic, allowing the prestress to be represented via a prestrain. For prestrain fields that are not compatible with the reference geometry, the computational framework provides an iterative algorithm for updating the prestrain until equilibrium is satisfied. The iterative framework allows for enforcement of two different constraints: elimination of distortion in order to address the incompatibility issue, and enforcing a specified in situ fiber strain field while allowing for distortion. The framework was implemented as a plugin in FEBio (www.febio.org), making it easy to maintain the software and to extend the framework if needed. Several examples illustrate the application and effectiveness of the approach, including the application of in situ strains to ligaments in the Open Knee model (simtk.org/home/openknee). A novel method for recovering the stress-free configuration from the prestrain deformation gradient is also presented. This general purpose theoretical and computational framework for applying prestrain will allow analysts to overcome the challenges in modeling this important aspect of biological tissue mechanics. PMID:27131609

  2. Computer program for calculating and fitting thermodynamic functions

    NASA Technical Reports Server (NTRS)

    Mcbride, Bonnie J.; Gordon, Sanford

    1992-01-01

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

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

    PubMed Central

    2013-01-01

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

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

    PubMed Central

    Caetano-Anollés, Gustavo; Caetano-Anollés, Derek

    2015-01-01

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

  5. Discovery of biological networks from diverse functional genomic data

    PubMed Central

    Myers, Chad L; Robson, Drew; Wible, Adam; Hibbs, Matthew A; Chiriac, Camelia; Theesfeld, Chandra L; Dolinski, Kara; Troyanskaya, Olga G

    2005-01-01

    We have developed a general probabilistic system for query-based discovery of pathway-specific networks through integration of diverse genome-wide data. This framework was validated by accurately recovering known networks for 31 biological processes in Saccharomyces cerevisiae and experimentally verifying predictions for the process of chromosomal segregation. Our system, bioPIXIE, a public, comprehensive system for integration, analysis, and visualization of biological network predictions for S. cerevisiae, is freely accessible over the worldwide web. PMID:16420673

  6. Computing the hadronic vacuum polarization function by analytic continuation

    DOE PAGESBeta

    Feng, Xu; Hashimoto, Shoji; Hotzel, Grit; Jansen, Karl; Petschlies, Marcus; Renner, Dru B.

    2013-08-29

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

  7. Adaptive, associative, and self-organizing functions in neural computing.

    PubMed

    Kohonen, T

    1987-12-01

    This paper contains an attempt to describe certain adaptive and cooperative functions encountered in neural networks. The approach is a compromise between biological accuracy and mathematical clarity. two types of differential equation seem to describe the basic effects underlying the information of these functions: the equation for the electrical activity of the neuron and the adaptation equation that describes changes in its input connectivities. Various phenomena and operations are derivable from them: clustering of activity in a laterally interconnected nework; adaptive formation of feature detectors; the autoassociative memory function; and self-organized formation of ordered sensory maps. The discussion tends to reason what functions are readily amenable to analytical modeling and which phenomena seem to ensue from the more complex interactions that take place in the brain. PMID:20523469

  8. A Survey of Computational Intelligence Techniques in Protein Function Prediction

    PubMed Central

    Tiwari, Arvind Kumar; Srivastava, Rajeev

    2014-01-01

    During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction. PMID:25574395

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

    NASA Technical Reports Server (NTRS)

    Greywall, Mahesh S.

    1991-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  11. Integrated command, control, communications and computation system functional architecture

    NASA Technical Reports Server (NTRS)

    Cooley, C. G.; Gilbert, L. E.

    1981-01-01

    The functional architecture for an integrated command, control, communications, and computation system applicable to the command and control portion of the NASA End-to-End Data. System is described including the downlink data processing and analysis functions required to support the uplink processes. The functional architecture is composed of four elements: (1) the functional hierarchy which provides the decomposition and allocation of the command and control functions to the system elements; (2) the key system features which summarize the major system capabilities; (3) the operational activity threads which illustrate the interrelationahip between the system elements; and (4) the interfaces which illustrate those elements that originate or generate data and those elements that use the data. The interfaces also provide a description of the data and the data utilization and access techniques.

  12. 3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  13. Seeing Is Believing: Quantifying Is Convincing: Computational Image Analysis in Biology.

    PubMed

    Sbalzarini, Ivo F

    2016-01-01

    Imaging is center stage in biology. Advances in microscopy and labeling techniques have enabled unprecedented observations and continue to inspire new developments. Efficient and accurate quantification and computational analysis of the acquired images, however, are becoming the bottleneck. We review different paradigms of computational image analysis for intracellular, single-cell, and tissue-level imaging, providing pointers to the specialized literature and listing available software tools. We place particular emphasis on clear categorization of image-analysis frameworks and on identifying current trends and challenges in the field. We further outline some of the methodological advances that are required in order to use images as quantitative scientific measurements. PMID:27207361

  14. A biologically consistent hierarchical framework for self-referencing survivalist computation

    NASA Astrophysics Data System (ADS)

    Cottam, Ron; Ranson, Willy; Vounckx, Roger

    2000-05-01

    Extensively scaled formally rational hardware and software are indirectly fallible, at the very least through temporal restrictions on the evaluation of their correctness. In addition, the apparent inability of formal rationality to successfully describe living systems as anything other than inanimate structures suggests that the development of self-referencing computational machines will require a different approach. There is currently a strong movement towards the adoption of semiotics as a descriptive medium in theoretical biology. We present a related computational semiosic construction (1, 2) consistent with evolutionary hierarchical emergence (3), which may serve as a framework for implementing anticipatory-oriented survivalist processing in real environments.

  15. Application of comparative biology in GO functional annotation: the mouse model.

    PubMed

    Drabkin, Harold J; Christie, Karen R; Dolan, Mary E; Hill, David P; Ni, Li; Sitnikov, Dmitry; Blake, Judith A

    2015-10-01

    The Gene Ontology (GO) is an important component of modern biological knowledge representation with great utility for computational analysis of genomic and genetic data. The Gene Ontology Consortium (GOC) consists of a large team of contributors including curation teams from most model organism database groups as well as curation teams focused on representation of data relevant to specific human diseases. Key to the generation of consistent and comprehensive annotations is the development and use of shared standards and measures of curation quality. The GOC engages all contributors to work to a defined standard of curation that is presented here in the context of annotation of genes in the laboratory mouse. Comprehensive understanding of the origin, epistemology, and coverage of GO annotations is essential for most effective use of GO resources. Here the application of comparative approaches to capturing functional data in the mouse system is described. PMID:26141960

  16. Ab Initio Calculations of the Electronic Structures and Biological Functions of Protein Molecules

    NASA Astrophysics Data System (ADS)

    Zheng, Haoping

    The self-consistent cluster-embedding (SCCE) calculation method reduces the computational effort from M3 to about M1 (M is the number of atoms in the system) with precise calculations. Thus the ab initio, all-electron calculation of the electronic structure and biological function of protein molecule has become a reality, which will promote new proteomics considerably. The calculated results of two real protein molecules, the trypsin inhibitor from the seeds of squash Cucurbita maxima (CMTI-I, 436 atoms) and the ascaris trypsin inhibitor (912 atoms, two three-dimensional structures), will be presented in this paper. The reactive sites of the inhibitors are determined and explained. The accuracy of structure determination of the inhibitors are tested theoretically.

  17. Ab Initio Calculations of the Electronic Structures and Biological Functions of Protein Molecules

    NASA Astrophysics Data System (ADS)

    Zheng, Haoping

    2003-04-01

    The self-consistent cluster-embedding (SCCE) calculation method reduces the computational effort from M3 to about M1 (M is the number of atoms in the system) with unchanged calculation precision. So the ab initio, all-electron calculation of the electronic structure and biological function of protein molecule becomes a reality, which will promote new proteomics considerably. The calculated results of two real protein molecules, the trypsin inhibitor from the seeds of squash Cucurbita maxima (CMTI-I, 436 atoms) and the Ascaris trypsin inhibitor (912 atoms, two three-dimensional structures), are presented. The reactive sites of the inhibitors are determined and explained. The precision of structure determination of inhibitors are tested theoretically.

  18. Distinguishing Pattern Formation Phenotypes: Applying Minkowski Functionals to Cell Biology Systems

    NASA Astrophysics Data System (ADS)

    Rericha, Erin; Guven, Can; Parent, Carole; Losert, Wolfgang

    2011-03-01

    Spatial Clustering of proteins within cells or cells themselves frequently occur in cell biology systems. However quantifying the underlying order and determining the regulators of these cluster patterns have proved difficult due to the inherent high noise levels in the systems. For instance the patterns formed by wild type and cyclic-AMP regulatory mutant Dictyostelium cells are visually distinctive, yet the large error bars in measurements of the fractal number, area, Euler number, eccentricity, and wavelength making it difficult to quantitatively distinguish between the patterns. We apply a spatial analysis technique based on Minkowski functionals and develop metrics which clearly separate wild type and mutant cell lines into distinct categories. Having such a metric facilitated the development of a computational model for cellular aggregation and its regulators. Supported by NIH-NGHS Nanotechnology (R01GM085574) and the Burroughs Wellcome Fund.

  19. Optimization of removal function in computer controlled optical surfacing

    NASA Astrophysics Data System (ADS)

    Chen, Xi; Guo, Peiji; Ren, Jianfeng

    2010-10-01

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

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

    PubMed Central

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

    2011-01-01

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

  1. The IWOP Technique and Wigner-Function Approach to Quantum Effect of Mesoscopic Biological Cell

    NASA Astrophysics Data System (ADS)

    Wang, Xiu-Xia

    2014-09-01

    Using the IWOP technique, Wigner function theory and TFD theory, the quantization of a mesoscopic biological cell equivalent circuit is proposed, The quantum fluctuations of the mesoscopic biological cell are researched in thermal vacuum state and vacuum state. It is shown that the IWOP technique, Wigner function theory and Umezawa-Takahashi's TFD theory play the key role in quantizing a mesoscopic biological cell at finite temperature and the fluctuations and uncertainty increase with increasing temperature and decrease with prolonged time.

  2. Time-Dependent Density Functional Theory for Universal Quantum Computation

    NASA Astrophysics Data System (ADS)

    Tempel, David

    2015-03-01

    In this talk, I will discuss how the theorems of TDDFT can be applied to a class of qubit Hamiltonians that are universal for quantum computation. The theorems of TDDFT applied to universal Hamiltonians imply that single-qubit expectation values can be used as the basic variables in quantum computation and information theory, rather than wavefunctions. From a practical standpoint this opens the possibility of approximating observables of interest in quantum computations directly in terms of single-qubit quantities (i.e. as density functionals). Additionally, I will discuss how TDDFT provides an exact prescription for simulating universal Hamiltonians with other universal Hamiltonians that have different, and possibly easier-to-realize two-qubit interactions.

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

    SciTech Connect

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

    2009-09-30

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

  4. Computer literacy for life sciences: helping the digital-era biology undergraduates face today's research.

    PubMed

    Smolinski, Tomasz G

    2010-01-01

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

  5. High performance computing in biology: multimillion atom simulations of nanoscale systems.

    PubMed

    Sanbonmatsu, K Y; Tung, C-S

    2007-03-01

    Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nano-scale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

  6. Computational adaptive optics for broadband optical interferometric tomography of biological tissue

    NASA Astrophysics Data System (ADS)

    Boppart, Stephen A.

    2015-03-01

    High-resolution real-time tomography of biological tissues is important for many areas of biological investigations and medical applications. Cellular level optical tomography, however, has been challenging because of the compromise between transverse imaging resolution and depth-of-field, the system and sample aberrations that may be present, and the low imaging sensitivity deep in scattering tissues. The use of computed optical imaging techniques has the potential to address several of these long-standing limitations and challenges. Two related techniques are interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO). Through three-dimensional Fourierdomain resampling, in combination with high-speed OCT, ISAM can be used to achieve high-resolution in vivo tomography with enhanced depth sensitivity over a depth-of-field extended by more than an order-of-magnitude, in realtime. Subsequently, aberration correction with CAO can be performed in a tomogram, rather than to the optical beam of a broadband optical interferometry system. Based on principles of Fourier optics, aberration correction with CAO is performed on a virtual pupil using Zernike polynomials, offering the potential to augment or even replace the more complicated and expensive adaptive optics hardware with algorithms implemented on a standard desktop computer. Interferometric tomographic reconstructions are characterized with tissue phantoms containing sub-resolution scattering particles, and in both ex vivo and in vivo biological tissue. This review will collectively establish the foundation for high-speed volumetric cellular-level optical interferometric tomography in living tissues.

  7. [Biological functions and the practical use of chitin].

    PubMed

    Feofilova, E P

    1984-01-01

    The review is dedicated to chitin--a wide-spread in nature polyaminosaccharide. Its main physico-chemical properties and biological role in the cell are analyzed. The review centres round the practical use of chitin and its derivatives. Natural resources, modern modes for production and application of chitin and its derivatives in industry, medicine, biotechnology and agriculture are discussed. PMID:6371781

  8. Oxidative metabolites of lycopene and their biological functions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To gain a better understanding of the beneficial biological activities of lycopene on cancer prevention, a greater knowledge of the metabolism of lycopene is needed. In particular, the identification of lycopene metabolites and oxidation products in vivo; the importance of tissue specific lycopene c...

  9. Computational predictions of energy materials using density functional theory

    NASA Astrophysics Data System (ADS)

    Jain, Anubhav; Shin, Yongwoo; Persson, Kristin A.

    2016-01-01

    In the search for new functional materials, quantum mechanics is an exciting starting point. The fundamental laws that govern the behaviour of electrons have the possibility, at the other end of the scale, to predict the performance of a material for a targeted application. In some cases, this is achievable using density functional theory (DFT). In this Review, we highlight DFT studies predicting energy-related materials that were subsequently confirmed experimentally. The attributes and limitations of DFT for the computational design of materials for lithium-ion batteries, hydrogen production and storage materials, superconductors, photovoltaics and thermoelectric materials are discussed. In the future, we expect that the accuracy of DFT-based methods will continue to improve and that growth in computing power will enable millions of materials to be virtually screened for specific applications. Thus, these examples represent a first glimpse of what may become a routine and integral step in materials discovery.

  10. Optimized Kaiser-Bessel Window Functions for Computed Tomography.

    PubMed

    Nilchian, Masih; Ward, John Paul; Vonesch, Cedric; Unser, Michael

    2015-11-01

    Kaiser-Bessel window functions are frequently used to discretize tomographic problems because they have two desirable properties: 1) their short support leads to a low computational cost and 2) their rotational symmetry makes their imaging transform independent of the direction. In this paper, we aim at optimizing the parameters of these basis functions. We present a formalism based on the theory of approximation and point out the importance of the partition-of-unity condition. While we prove that, for compact-support functions, this condition is incompatible with isotropy, we show that minimizing the deviation from the partition of unity condition is highly beneficial. The numerical results confirm that the proposed tuning of the Kaiser-Bessel window functions yields the best performance. PMID:26151939

  11. Computer Code For Calculation Of The Mutual Coherence Function

    NASA Astrophysics Data System (ADS)

    Bugnolo, Dimitri S.

    1986-05-01

    We present a computer code in FORTRAN 77 for the calculation of the mutual coherence function (MCF) of a plane wave normally incident on a stochastic half-space. This is an exact result. The user need only input the path length, the wavelength, the outer scale size, and the structure constant. This program may be used to calculate the MCF of a well-collimated laser beam in the atmosphere.

  12. Computations involving differential operators and their actions on functions

    NASA Technical Reports Server (NTRS)

    Crouch, Peter E.; Grossman, Robert; Larson, Richard

    1991-01-01

    The algorithms derived by Grossmann and Larson (1989) are further developed for rewriting expressions involving differential operators. The differential operators involved arise in the local analysis of nonlinear dynamical systems. These algorithms are extended in two different directions: the algorithms are generalized so that they apply to differential operators on groups and the data structures and algorithms are developed to compute symbolically the action of differential operators on functions. Both of these generalizations are needed for applications.

  13. Functional imaging of the brain using computed tomography.

    PubMed

    Berninger, W H; Axel, L; Norman, D; Napel, S; Redington, R W

    1981-03-01

    Data from rapid-sequence CT scans of the same cross section, obtained following bolus injection of contrast material, were analyzed by functional imaging. The information contained in a large number of images can be compressed into one or two gray-scale images which can be evaluated both qualitatively and quantitatively. The computational techniques are described and applied to the generation of images depicting bolus transit time, arrival time, peak time, and effective width. PMID:7465851

  14. Computational aspects of the continuum quaternionic wave functions for hydrogen

    SciTech Connect

    Morais, J.

    2014-10-15

    Over the past few years considerable attention has been given to the role played by the Hydrogen Continuum Wave Functions (HCWFs) in quantum theory. The HCWFs arise via the method of separation of variables for the time-independent Schrödinger equation in spherical coordinates. The HCWFs are composed of products of a radial part involving associated Laguerre polynomials multiplied by exponential factors and an angular part that is the spherical harmonics. In the present paper we introduce the continuum wave functions for hydrogen within quaternionic analysis ((R)QHCWFs), a result which is not available in the existing literature. In particular, the underlying functions are of three real variables and take on either values in the reduced and full quaternions (identified, respectively, with R{sup 3} and R{sup 4}). We prove that the (R)QHCWFs are orthonormal to one another. The representation of these functions in terms of the HCWFs are explicitly given, from which several recurrence formulae for fast computer implementations can be derived. A summary of fundamental properties and further computation of the hydrogen-like atom transforms of the (R)QHCWFs are also discussed. We address all the above and explore some basic facts of the arising quaternionic function theory. As an application, we provide the reader with plot simulations that demonstrate the effectiveness of our approach. (R)QHCWFs are new in the literature and have some consequences that are now under investigation.

  15. INTEGRATING COMPUTATIONAL PROTEIN FUNCTION PREDICTION INTO DRUG DISCOVERY INITIATIVES

    PubMed Central

    Grant, Marianne A.

    2014-01-01

    Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes. PMID:25530654

  16. Preprocessing functions for computed radiography images in a PACS environment

    NASA Astrophysics Data System (ADS)

    McNitt-Gray, Michael F.; Pietka, Ewa; Huang, H. K.

    1992-05-01

    In a picture archiving and communications system (PACS), images are acquired from several modalities including computed radiography (CR). This modality has unique image characteristics and presents several problems that need to be resolved before the image is available for viewing at a display workstation. A set of preprocessing functions have been applied to all CR images in a PACS environment to enhance the display of images. The first function reformats CR images that are acquired with different plate sizes to a standard size for display. Another function removes the distracting white background caused by the collimation used at the time of exposure. A third function determines the orientation of each image and rotates those images that are in nonstandard positions into a standard viewing position. Another function creates a default look-up table based on the gray levels actually used by the image (instead of allocated gray levels). Finally, there is a function which creates (for chest images only) the piece-wise linear look-up tables that can be applied to enhance different tissue densities. These functions have all been implemented in a PACS environment. Each of these functions have been very successful in improving the viewing conditions of CR images and contribute to the clinical acceptance of PACS by reducing the effort required to display CR images.

  17. Computational modeling of chemo-bio-mechanical coupling: a systems-biology approach toward wound healing.

    PubMed

    Buganza Tepole, A; Kuhl, E

    2016-01-01

    Wound healing is a synchronized cascade of chemical, biological, and mechanical phenomena, which act in concert to restore the damaged tissue. An imbalance between these events can induce painful scarring. Despite intense efforts to decipher the mechanisms of wound healing, the role of mechanics remains poorly understood. Here, we establish a computational systems biology model to identify the chemical, biological, and mechanical mechanisms of scar formation. First, we introduce the generic problem of coupled chemo-bio-mechanics. Then, we introduce the model problem of wound healing in terms of a particular chemical signal, inflammation, a particular biological cell type, fibroblasts, and a particular mechanical model, isotropic hyperelasticity. We explore the cross-talk between chemical, biological, and mechanical signals and show that all three fields have a significant impact on scar formation. Our model is the first step toward rigorous multiscale, multifield modeling in wound healing. Our formulation has the potential to improve effective wound management and optimize treatment on an individualized patient-specific basis. PMID:25421487

  18. COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

    PubMed Central

    Kapetanovic, I.M.

    2008-01-01

    It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

  19. Path-Integration Computation of the Transport Properties of Polymers Nanoparticles and Complex Biological Structures

    NASA Astrophysics Data System (ADS)

    Douglas, Jack

    2014-03-01

    One of the things that puzzled me when I was a PhD student working under Karl Freed was the curious unity between the theoretical descriptions of excluded volume interactions in polymers, the hydrodynamic properties of polymers in solution, and the critical properties of fluid mixtures, gases and diverse other materials (magnets, superfluids,etc.) when these problems were formally expressed in terms of Wiener path integration and the interactions treated through a combination of epsilon expansion and renormalization group (RG) theory. It seemed that only the interaction labels changed from one problem to the other. What do these problems have in common? Essential clues to these interrelations became apparent when Karl Freed, myself and Shi-Qing Wang together began to study polymers interacting with hyper-surfaces of continuously variable dimension where the Feynman perturbation expansions could be performed through infinite order so that we could really understand what the RG theory was doing. It is evidently simply a particular method for resuming perturbation theory, and former ambiguities no longer existed. An integral equation extension of this type of exact calculation to ``surfaces'' of arbitrary fixed shape finally revealed the central mathematical object that links these diverse physical models- the capacity of polymer chains, whose value vanishes at the critical dimension of 4 and whose magnitude is linked to the friction coefficient of polymer chains, the virial coefficient of polymers and the 4-point function of the phi-4 field theory,...Once this central object was recognized, it then became possible solve diverse problems in material science through the calculation of capacity, and related ``virials'' properties, through Monte Carlo sampling of random walk paths. The essential ideas of this computational method are discussed and some applications given to non-trivial problems: nanotubes treated as either rigid rods or ensembles worm-like chains having

  20. Prioritizing drug targets in Clostridium botulinum with a computational systems biology approach.

    PubMed

    Muhammad, Syed Aun; Ahmed, Safia; Ali, Amjad; Huang, Hui; Wu, Xiaogang; Yang, X Frank; Naz, Anam; Chen, Jake

    2014-07-01

    A computational and in silico system level framework was developed to identify and prioritize the antibacterial drug targets in Clostridium botulinum (Clb), the causative agent of flaccid paralysis in humans that can be fatal in 5 to 10% of cases. This disease is difficult to control due to the emergence of drug-resistant pathogenic strains and the only available treatment antitoxin which can target the neurotoxin at the extracellular level and cannot reverse the paralysis. This study framework is based on comprehensive systems-scale analysis of genomic sequence homology and phylogenetic relationships among Clostridium, other infectious bacteria, host and human gut flora. First, the entire 2628-annotated genes of this bacterial genome were categorized into essential, non-essential and virulence genes. The results obtained showed that 39% of essential proteins that functionally interact with virulence proteins were identified, which could be a key to new interventions that may kill the bacteria and minimize the host damage caused by the virulence factors. Second, a comprehensive comparative COGs and blast sequence analysis of these proteins and host proteins to minimize the risks of side effects was carried out. This revealed that 47% of a set of C. botulinum proteins were evolutionary related with Homo sapiens proteins to sort out the non-human homologs. Third, orthology analysis with other infectious bacteria to assess broad-spectrum effects was executed and COGs were mostly found in Clostridia, Bacilli (Firmicutes), and in alpha and beta Proteobacteria. Fourth, a comparative phylogenetic analysis was performed with human microbiota to filter out drug targets that may also affect human gut flora. This reduced the list of candidate proteins down to 131. Finally, the role of these putative drug targets in clostridial biological pathways was studied while subcellular localization of these candidate proteins in bacterial cellular system exhibited that 68% of the

  1. Computational enzyme design approaches with significant biological outcomes: progress and challenges

    PubMed Central

    Li, Xiaoman; Zhang, Ziding; Song, Jiangning

    2012-01-01

    Enzymes are powerful biocatalysts, however, so far there is still a large gap between the number of enzyme-based practical applications and that of naturally occurring enzymes. Multiple experimental approaches have been applied to generate nearly all possible mutations of target enzymes, allowing the identification of desirable variants with improved properties to meet the practical needs. Meanwhile, an increasing number of computational methods have been developed to assist in the modification of enzymes during the past few decades. With the development of bioinformatic algorithms, computational approaches are now able to provide more precise guidance for enzyme engineering and make it more efficient and less laborious. In this review, we summarize the recent advances of method development with significant biological outcomes to provide important insights into successful computational protein designs. We also discuss the limitations and challenges of existing methods and the future directions that should improve them. PMID:24688648

  2. Cerenkov Radiation: A Multi-functional Approach for Biological Sciences

    NASA Astrophysics Data System (ADS)

    Ma, Xiaowei; Wang, Jing; Cheng, Zhen

    2014-02-01

    Cerenkov radiation (CR) has been used in various biological research fields, which has aroused lots of attention in recent years. Combining optical imaging instruments and most of nuclear medicine imaging or radiotherapy probes, the CR was developed as a new imaging modality for biology studies, called Cerenkov luminescence imaging (CLI). On the other hand, it was novelly used as an internal excitation source to activate some fluorophores for energy transfer imaging. However, it also has some shortages such as relatively weak luminescence intensity and low penetration in tissue. Thus some scientific groups demonstrated to optimize the CLI and demonstrated it to three-dimension tomography. In this article, we elaborate on its principle, history, and applications and discuss a number of directions for technical improvements. Then concluded some advantages and shortages of CR and discuss some prospects of it.

  3. Structural and Computational Biology in the Design of Immunogenic Vaccine Antigens

    PubMed Central

    Liljeroos, Lassi; Malito, Enrico; Ferlenghi, Ilaria; Bottomley, Matthew James

    2015-01-01

    Vaccination is historically one of the most important medical interventions for the prevention of infectious disease. Previously, vaccines were typically made of rather crude mixtures of inactivated or attenuated causative agents. However, over the last 10–20 years, several important technological and computational advances have enabled major progress in the discovery and design of potently immunogenic recombinant protein vaccine antigens. Here we discuss three key breakthrough approaches that have potentiated structural and computational vaccine design. Firstly, genomic sciences gave birth to the field of reverse vaccinology, which has enabled the rapid computational identification of potential vaccine antigens. Secondly, major advances in structural biology, experimental epitope mapping, and computational epitope prediction have yielded molecular insights into the immunogenic determinants defining protective antigens, enabling their rational optimization. Thirdly, and most recently, computational approaches have been used to convert this wealth of structural and immunological information into the design of improved vaccine antigens. This review aims to illustrate the growing power of combining sequencing, structural and computational approaches, and we discuss how this may drive the design of novel immunogens suitable for future vaccines urgently needed to increase the global prevention of infectious disease. PMID:26526043

  4. Multiscale Modeling of Biological Functions: From Enzymes to Molecular Machines (Nobel Lecture)

    PubMed Central

    Warshel, Arieh

    2016-01-01

    Adetailed understanding of the action of biological molecules is a pre-requisite for rational advances in health sciences and related fields. Here, the challenge is to move from available structural information to a clear understanding of the underlying function of the system. In light of the complexity of macromolecular complexes, it is essential to use computer simulations to describe how the molecular forces are related to a given function. However, using a full and reliable quantum mechanical representation of large molecular systems has been practically impossible. The solution to this (and related) problems has emerged from the realization that large systems can be spatially divided into a region where the quantum mechanical description is essential (e.g. a region where bonds are being broken), with the remainder of the system being represented on a simpler level by empirical force fields. This idea has been particularly effective in the development of the combined quantum mechanics/molecular mechanics (QM/MM) models. Here, the coupling between the electrostatic effects of the quantum and classical subsystems has been a key to the advances in describing the functions of enzymes and other biological molecules. The same idea of representing complex systems in different resolutions in both time and length scales has been found to be very useful in modeling the action of complex systems. In such cases, starting with coarse grained (CG) representations that were originally found to be very useful in simulating protein folding, and augmenting them with a focus on electrostatic energies, has led to models that are particularly effective in probing the action of molecular machines. The same multiscale idea is likely to play a major role in modeling of even more complex systems, including cells and collections of cells. PMID:25060243

  5. The role of ontologies in biological and biomedical research: a functional perspective.

    PubMed

    Hoehndorf, Robert; Schofield, Paul N; Gkoutos, Georgios V

    2015-11-01

    Ontologies are widely used in biological and biomedical research. Their success lies in their combination of four main features present in almost all ontologies: provision of standard identifiers for classes and relations that represent the phenomena within a domain; provision of a vocabulary for a domain; provision of metadata that describes the intended meaning of the classes and relations in ontologies; and the provision of machine-readable axioms and definitions that enable computational access to some aspects of the meaning of classes and relations. While each of these features enables applications that facilitate data integration, data access and analysis, a great potential lies in the possibility of combining these four features to support integrative analysis and interpretation of multimodal data. Here, we provide a functional perspective on ontologies in biology and biomedicine, focusing on what ontologies can do and describing how they can be used in support of integrative research. We also outline perspectives for using ontologies in data-driven science, in particular their application in structured data mining and machine learning applications. PMID:25863278

  6. The role of ontologies in biological and biomedical research: a functional perspective

    PubMed Central

    Schofield, Paul N.; Gkoutos, Georgios V.

    2015-01-01

    Ontologies are widely used in biological and biomedical research. Their success lies in their combination of four main features present in almost all ontologies: provision of standard identifiers for classes and relations that represent the phenomena within a domain; provision of a vocabulary for a domain; provision of metadata that describes the intended meaning of the classes and relations in ontologies; and the provision of machine-readable axioms and definitions that enable computational access to some aspects of the meaning of classes and relations. While each of these features enables applications that facilitate data integration, data access and analysis, a great potential lies in the possibility of combining these four features to support integrative analysis and interpretation of multimodal data. Here, we provide a functional perspective on ontologies in biology and biomedicine, focusing on what ontologies can do and describing how they can be used in support of integrative research. We also outline perspectives for using ontologies in data-driven science, in particular their application in structured data mining and machine learning applications. PMID:25863278

  7. Computational modeling of STED microscopy through multiple biological cells under one- and two-photon excitation

    NASA Astrophysics Data System (ADS)

    Mark, Andrew E.; Davis, Mitchell A.; Starosta, Matthew S.; Dunn, Andrew K.

    2015-03-01

    While superresolution optical microscopy techniques afford enhanced resolution for biological applications, they have largely been used to study structures in isolated cells. We use the FDTD method to simulate the propagation of focused beams for STED microscopy through multiple biological cells. We model depletion beams that provide 2D and 3D confinement of the fluorescence spot and assess the effective PSF of the system as a function of focal depth. We compare the relative size of the STED effective PSF under one- and two-photon excitation. PSF calculations suggest that imaging is possible up to the maximum simulation depth if the fluorescence emission remains detectable.

  8. Green's Function Analysis of Periodic Structures in Computational Electromagnetics

    NASA Astrophysics Data System (ADS)

    Van Orden, Derek

    2011-12-01

    Periodic structures are used widely in electromagnetic devices, including filters, waveguiding structures, and antennas. Their electromagnetic properties may be analyzed computationally by solving an integral equation, in which an unknown equivalent current distribution in a single unit cell is convolved with a periodic Green's function that accounts for the system's boundary conditions. Fast computation of the periodic Green's function is therefore essential to achieve high accuracy solutions of complicated periodic structures, including analysis of modal wave propagation and scattering from external sources. This dissertation first presents alternative spectral representations of the periodic Green's function of the Helmholtz equation for cases of linear periodic systems in 2D and 3D free space and near planarly layered media. Although there exist multiple representations of the periodic Green's function, most are not efficient in the important case where the fields are observed near the array axis. We present spectral-spatial representations for rapid calculation of the periodic Green's functions for linear periodic arrays of current sources residing in free space as well as near a planarly layered medium. They are based on the integral expansion of the periodic Green's functions in terms of the spectral parameters transverse to the array axis. These schemes are important for the rapid computation of the interaction among unit cells of a periodic array, and, by extension, the complex dispersion relations of guided waves. Extensions of this approach to planar periodic structures are discussed. With these computation tools established, we study the traveling wave properties of linear resonant arrays placed near surfaces, and examine the coupling mechanisms that lead to radiation into guided waves supported by the surface. This behavior is especially important to understand the properties of periodic structures printed on dielectric substrates, such as periodic

  9. Marine organism cell biology and regulatory sequence discoveryin comparative functional genomics.

    PubMed

    Barnes, David W; Mattingly, Carolyn J; Parton, Angela; Dowell, Lori M; Bayne, Christopher J; Forrest, John N

    2004-10-01

    The use of bioinformatics to integrate phenotypic and genomic data from mammalian models is well established as a means of understanding human biology and disease. Beyond direct biomedical applications of these approaches in predicting structure-function relationships between coding sequences and protein activities, comparative studies also promote understanding of molecular evolution and the relationship between genomic sequence and morphological and physiological specialization. Recently recognized is the potential of comparative studies to identify functionally significant regulatory regions and to generate experimentally testable hypotheses that contribute to understanding mechanisms that regulate gene expression, including transcriptional activity, alternative splicing and transcript stability. Functional tests of hypotheses generated by computational approaches require experimentally tractable in vitro systems, including cell cultures. Comparative sequence analysis strategies that use genomic sequences from a variety of evolutionarily diverse organisms are critical for identifying conserved regulatory motifs in the 5'-upstream, 3'-downstream and introns of genes. Genomic sequences and gene orthologues in the first aquatic vertebrate and protovertebrate organisms to be fully sequenced (Fugu rubripes, Ciona intestinalis, Tetraodon nigroviridis, Danio rerio) as well as in the elasmobranchs, spiny dogfish shark (Squalus acanthias) and little skate (Raja erinacea), and marine invertebrate models such as the sea urchin (Strongylocentrotus purpuratus) are valuable in the prediction of putative genomic regulatory regions. Cell cultures have been derived for these and other model species. Data and tools resulting from these kinds of studies will contribute to understanding transcriptional regulation of biomedically important genes and provide new avenues for medical therapeutics and disease prevention. PMID:19003267

  10. On the Hydrodynamic Function of Sharkskin: A Computational Investigation

    NASA Astrophysics Data System (ADS)

    Boomsma, Aaron; Sotiropoulos, Fotis

    2014-11-01

    Denticles (placoid scales) are small structures that cover the epidermis of some sharks. The hydrodynamic function of denticles is unclear. Because they resemble riblets, they have been thought to passively reduce skin-friction-for which there is some experimental evidence. Others have experimentally shown that denticles increase skin-friction and have hypothesized that denticles act as vortex generators to delay separation. To help clarify their function, we use high-resolution large eddy and direct numerical simulations, with an immersed boundary method, to simulate flow patterns past and calculate the drag force on Mako Short Fin denticles. Simulations are carried out for the denticles placed in a canonical turbulent boundary layer as well as in the vicinity of a separation bubble. The computed results elucidate the three-dimensional structure of the flow around denticles and provide insights into the hydrodynamic function of sharkskin.

  11. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

    PubMed

    Li, Jun; Zhao, Patrick X

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/. PMID:27446133

  12. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach

    PubMed Central

    Li, Jun; Zhao, Patrick X.

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/. PMID:27446133

  13. A Riemannian framework for orientation distribution function computing.

    PubMed

    Cheng, Jian; Ghosh, Aurobrata; Jiang, Tianzi; Deriche, Rachid

    2009-01-01

    Compared with Diffusion Tensor Imaging (DTI), High Angular Resolution Imaging (HARDI) can better explore the complex microstructure of white matter. Orientation Distribution Function (ODF) is used to describe the probability of the fiber direction. Fisher information metric has been constructed for probability density family in Information Geometry theory and it has been successfully applied for tensor computing in DTI. In this paper, we present a state of the art Riemannian framework for ODF computing based on Information Geometry and sparse representation of orthonormal bases. In this Riemannian framework, the exponential map, logarithmic map and geodesic have closed forms. And the weighted Frechet mean exists uniquely on this manifold. We also propose a novel scalar measurement, named Geometric Anisotropy (GA), which is the Riemannian geodesic distance between the ODF and the isotropic ODF. The Renyi entropy H1/2 of the ODF can be computed from the GA. Moreover, we present an Affine-Euclidean framework and a Log-Euclidean framework so that we can work in an Euclidean space. As an application, Lagrange interpolation on ODF field is proposed based on weighted Frechet mean. We validate our methods on synthetic and real data experiments. Compared with existing Riemannian frameworks on ODF, our framework is model-free. The estimation of the parameters, i.e. Riemannian coordinates, is robust and linear. Moreover it should be noted that our theoretical results can be used for any probability density function (PDF) under an orthonormal basis representation. PMID:20426075

  14. Heterogeneous processes at the intersection of chemistry and biology: A computational approach

    SciTech Connect

    Kuo, I W; Mundy, C J

    2008-02-11

    Heterogeneous processes hold the key to understanding many problems in biology and atmospheric science. In particular, recent experiments have shown that heterogeneous chemistry at the surface of sea-salt aerosols plays a large role in important atmospheric processes with far reaching implications towards understanding of the fate and transport of aerosolized chemical weapons (i.e. organophosphates such as sarin and VX). Unfortunately, the precise mechanistic details of the simplest surface enhanced chemical reactions remain unknown. Understanding heterogeneous processes also has implications in the biological sciences. Traditionally, it is accepted that enzymes catalyze reactions by stabilizing the transition state, thereby lowering the free energy barrier. However, recent findings have shown that a multitude of phenomena likely contribute to the efficiency of enzymes, such as coupled protein motion, quantum mechanical tunneling, or strong electrostatic binding. The objective of this project was to develop and validate a single computational framework based on first principles simulations using tera-scale computational resources to answer fundamental scientific questions about heterogeneous chemical processes relevant to atmospheric chemistry and biological sciences.

  15. Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy

    PubMed Central

    Schroll, Henning; Hamker, Fred H.

    2013-01-01

    Over the past 15 years, computational models have had a considerable impact on basal-ganglia research. Most of these models implement multiple distinct basal-ganglia pathways and assume them to fulfill different functions. As there is now a multitude of different models, it has become complex to keep track of their various, sometimes just marginally different assumptions on pathway functions. Moreover, it has become a challenge to oversee to what extent individual assumptions are corroborated or challenged by empirical data. Focusing on computational, but also considering non-computational models, we review influential concepts of pathway functions and show to what extent they are compatible with or contradict each other. Moreover, we outline how empirical evidence favors or challenges specific model assumptions and propose experiments that allow testing assumptions against each other. PMID:24416002

  16. Analog computation of auto and cross-correlation functions

    NASA Technical Reports Server (NTRS)

    1974-01-01

    For analysis of the data obtained from the cross beam systems it was deemed desirable to compute the auto- and cross-correlation functions by both digital and analog methods to provide a cross-check of the analysis methods and an indication as to which of the two methods would be most suitable for routine use in the analysis of such data. It is the purpose of this appendix to provide a concise description of the equipment and procedures used for the electronic analog analysis of the cross beam data. A block diagram showing the signal processing and computation set-up used for most of the analog data analysis is provided. The data obtained at the field test sites were recorded on magnetic tape using wide-band FM recording techniques. The data as recorded were band-pass filtered by electronic signal processing in the data acquisition systems.

  17. Non-coding RNAs: Classification, Biology and Functioning.

    PubMed

    Hombach, Sonja; Kretz, Markus

    2016-01-01

    One of the long-standing principles of molecular biology is that DNA acts as a template for transcription of messenger RNAs, which serve as blueprints for protein translation. A rapidly growing number of exceptions to this rule have been reported over the past decades: they include long known classes of RNAs involved in translation such as transfer RNAs and ribosomal RNAs, small nuclear RNAs involved in splicing events, and small nucleolar RNAs mainly involved in the modification of other small RNAs, such as ribosomal RNAs and transfer RNAs. More recently, several classes of short regulatory non-coding RNAs, including piwi-associated RNAs, endogenous short-interfering RNAs and microRNAs have been discovered in mammals, which act as key regulators of gene expression in many different cellular pathways and systems. Additionally, the human genome encodes several thousand long non-protein coding RNAs >200 nucleotides in length, some of which play crucial roles in a variety of biological processes such as epigenetic control of chromatin, promoter-specific gene regulation, mRNA stability, X-chromosome inactivation and imprinting. In this chapter, we will introduce several classes of short and long non-coding RNAs, describe their diverse roles in mammalian gene regulation and give examples for known modes of action. PMID:27573892

  18. Computer Modeling of the Earliest Cellular Structures and Functions

    NASA Astrophysics Data System (ADS)

    Pohorille, Andrew

    2000-03-01

    In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells), the most direct way to test ourunderstanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform protocellular functions. Many of these functions, such as import of nutrients, capture and storage of energy, and response to changes in the environment are carried out by proteins bound to membranes. We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides)organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (e.g. channels), and (c) by what mechanisms such aggregates perform essential protocellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each atom in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10^6-10^8 time steps.

  19. Computer Modeling of the Earliest Cellular Structures and Functions

    NASA Technical Reports Server (NTRS)

    Pohorille, Andrew; Chipot, Christophe; Schweighofer, Karl

    2000-01-01

    In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.

  20. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  1. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  2. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  3. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  4. 21 CFR 870.1435 - Single-function, preprogrammed diagnostic computer.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Single-function, preprogrammed diagnostic computer... Single-function, preprogrammed diagnostic computer. (a) Identification. A single-function, preprogrammed diagnostic computer is a hard-wired computer that calculates a specific physiological or blood-flow...

  5. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions.

    PubMed

    Laraia, Luca; McKenzie, Grahame; Spring, David R; Venkitaraman, Ashok R; Huggins, David J

    2015-06-18

    Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs. PMID:26091166

  6. Fuzzy Logic as a Computational Tool for Quantitative Modelling of Biological Systems with Uncertain Kinetic Data.

    PubMed

    Bordon, Jure; Moskon, Miha; Zimic, Nikolaj; Mraz, Miha

    2015-01-01

    Quantitative modelling of biological systems has become an indispensable computational approach in the design of novel and analysis of existing biological systems. However, kinetic data that describe the system's dynamics need to be known in order to obtain relevant results with the conventional modelling techniques. These data are often hard or even impossible to obtain. Here, we present a quantitative fuzzy logic modelling approach that is able to cope with unknown kinetic data and thus produce relevant results even though kinetic data are incomplete or only vaguely defined. Moreover, the approach can be used in the combination with the existing state-of-the-art quantitative modelling techniques only in certain parts of the system, i.e., where kinetic data are missing. The case study of the approach proposed here is performed on the model of three-gene repressilator. PMID:26451831

  7. The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt

    PubMed Central

    Mulder, Nicola J.; Christoffels, Alan; de Oliveira, Tulio; Gamieldien, Junaid; Hazelhurst, Scott; Joubert, Fourie; Kumuthini, Judit; Pillay, Ché S.; Snoep, Jacky L.; Tastan Bishop, Özlem; Tiffin, Nicki

    2016-01-01

    Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt. PMID:26845152

  8. The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt.

    PubMed

    Mulder, Nicola J; Christoffels, Alan; de Oliveira, Tulio; Gamieldien, Junaid; Hazelhurst, Scott; Joubert, Fourie; Kumuthini, Judit; Pillay, Ché S; Snoep, Jacky L; Tastan Bishop, Özlem; Tiffin, Nicki

    2016-02-01

    Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt. PMID:26845152

  9. Overview of significant challenges in molecular biology amenable to computational methods.

    PubMed

    Glaeser, R M

    1994-01-01

    Many challenging but significant opportunities exist for the development of theoretical approaches in modern Cell and Molecular Biology. The creation of data bases which contain extremely large amounts of information has proven to be an unexpectedly important facto-tin gaining acceptance and respectability for theoretical work that builds on nothing more than what is in the data base itself, such as theoretical work involving the analysis of known protein structures, or the development of more powerful homology searches. Other opportunities, not yet accepted by a broad community, involve work on complex networks (metabolic, genetic, immunologic and neural networks) and work on the "physics of how things work." The DOE National Laboratory System represents the ideal institution that would be well suited to the role of being an "incubator" for the creation of a theoretical and computational discipline within modern biology. PMID:7755540

  10. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions

    PubMed Central

    Laraia, Luca; McKenzie, Grahame; Spring, David R.; Venkitaraman, Ashok R.; Huggins, David J.

    2015-01-01

    Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs. PMID:26091166

  11. FOREWORD: Third Nordic Symposium on Computer Simulation in Physics, Chemistry, Biology and Mathematics

    NASA Astrophysics Data System (ADS)

    Kaski, K.; Salomaa, M.

    1990-01-01

    These are Proceedings of the Third Nordic Symposium on Computer Simulation in Physics, Chemistry, Biology, and Mathematics, held August 25-26, 1989, at Lahti (Finland). The Symposium belongs to an annual series of Meetings, the first one of which was arranged in 1987 at Lund (Sweden) and the second one in 1988 at Kolle-Kolle near Copenhagen (Denmark). Although these Symposia have thus far been essentially Nordic events, their international character has increased significantly; the trend is vividly reflected through contributions in the present Topical Issue. The interdisciplinary nature of Computational Science is central to the activity; this fundamental aspect is also responsible, in an essential way, for its rapidly increasing impact. Crucially important to a wide spectrum of superficially disparate fields is the common need for extensive - and often quite demanding - computational modelling. For such theoretical models, no closed-form (analytical) solutions are available or they would be extremely difficult to find; hence one must rather resort to the Art of performing computational investigations. Among the unifying features in the computational research are the methods of simulation employed; methods which frequently are quite closely related with each other even for faculties of science that are quite unrelated. Computer simulation in Natural Sciences is presently apprehended as a discipline on its own right, occupying a broad region somewhere between the experimental and theoretical methods, but also partially overlapping with and complementing them. - Whichever its proper definition may be, the computational approach serves as a novel and an extremely versatile tool with which one can equally well perform "pure" experimental modelling and conduct "computational theory". Computational studies that have earlier been made possible only through supercomputers have opened unexpected, as well as exciting, novel frontiers equally in mathematics (e.g., fractals

  12. [Biological problems of origin and development of various physiological functions (theory and application)].

    PubMed

    Ivanov, K P

    2001-01-01

    The author presents some idea about origin and development of some physiological functions: outer breathing, breath function of blood, blood circulation, thermoregulation, energy supply. The conclusions about main directions of evolution of these functions and duration of their development in phylogeny were drawn. The author gave some examples of abrupt changes of development of these functions in different groups of animals and discussed possible reasons of such changes. General quantitative estimation of the results of evolution of these functions from the position of their summArized efficiency was done. Quantitative characteristics of optimization and efficiency limits of physiological functions were suggested on the base of new data in general biology and comparative physiology. The author put toward the hypothesis about conventional "mistakes" of evolution and showed deep biological reasons of some seriOus illness. The examples of some applied problems in biology, physiology and medicine that can be solved with the data on evolution of physiological functions are presented. PMID:11548400

  13. Non-functioning adrenal adenomas discovered incidentally on computed tomography

    SciTech Connect

    Mitnick, J.S.; Bosniak, M.A.; Megibow, A.J.; Naidich, D.P.

    1983-08-01

    Eighteen patients with unilateral non-metastatic non-functioning adrenal masses were studied with computed tomography (CT). Pathological examination in cases revealed benign adrenal adenomas. The others were followed up with serial CT scans and found to show no change in tumor size over a period of six months to three years. On the basis of these findings, the authors suggest certain criteria of a benign adrenal mass, including (a) diameter less than 5 cm, (b) smooth contour, (c) well-defined margin, and (d) no change in size on follow-up. Serial CT scanning can be used as an alternative to surgery in the management of many of these patients.

  14. Chemically-functionalized microcantilevers for detection of chemical, biological and explosive material

    DOEpatents

    Pinnaduwage, Lal A [Knoxville, TN; Thundat, Thomas G [Knoxville, TN; Brown, Gilbert M [Knoxville, TN; Hawk, John Eric [Olive Branch, MS; Boiadjiev, Vassil I [Knoxville, TN

    2007-04-24

    A chemically functionalized cantilever system has a cantilever coated on one side thereof with a reagent or biological species which binds to an analyte. The system is of particular value when the analyte is a toxic chemical biological warfare agent or an explosive.

  15. A Combination of Hand-Held Models and Computer Imaging Programs Helps Students Answer Oral Questions about Molecular Structure and Function: A Controlled Investigation of Student Learning

    ERIC Educational Resources Information Center

    Harris, Michelle A.; Peck, Ronald F.; Colton, Shannon; Morris, Jennifer; Neto, Elias Chaibub; Kallio, Julie

    2009-01-01

    We conducted a controlled investigation to examine whether a combination of computer imagery and tactile tools helps introductory cell biology laboratory undergraduate students better learn about protein structure/function relationships as compared with computer imagery alone. In all five laboratory sections, students used the molecular imaging…

  16. Beyond iron: non-classical biological functions of bacterial siderophores.

    PubMed

    Johnstone, Timothy C; Nolan, Elizabeth M

    2015-04-14

    Bacteria secrete small molecules known as siderophores to acquire iron from their surroundings. For over 60 years, investigations into the bioinorganic chemistry of these molecules, including fundamental coordination chemistry studies, have provided insight into the crucial role that siderophores play in bacterial iron homeostasis. The importance of understanding the fundamental chemistry underlying bacterial life has been highlighted evermore in recent years because of the emergence of antibiotic-resistant bacteria and the need to prevent the global rise of these superbugs. Increasing reports of siderophores functioning in capacities other than iron transport have appeared recently, but reports of "non-classical" siderophore functions have long paralleled those of iron transport. One particular non-classical function of these iron chelators, namely antibiotic activity, was documented before the role of siderophores in iron transport was established. In this Perspective, we present an exposition of past and current work into non-classical functions of siderophores and highlight the directions in which we anticipate that this research is headed. Examples include the ability of siderophores to function as zincophores, chalkophores, and metallophores for a variety of other metals, sequester heavy metal toxins, transport boron, act as signalling molecules, regulate oxidative stress, and provide antibacterial activity. PMID:25764171

  17. Beyond Iron: Non-Classical Biological Functions of Bacterial Siderophores

    PubMed Central

    Johnstone, Timothy C.; Nolan, Elizabeth M.

    2015-01-01

    Bacteria secrete small molecules known as siderophores to acquire iron from their surroundings. For over 60 years, investigations into the bioinorganic chemistry of these molecules, including fundamental coordination chemistry studies, have provided insight into the crucial role that siderophores play in bacterial iron homeostasis. The importance of understanding the fundamental chemistry underlying bacterial life has been highlighted evermore in recent years because of the emergence of antibiotic-resistant bacteria and the need to prevent the global rise of these superbugs. Increasing reports of siderophores functioning in capacities other than iron transport have appeared recently, but reports of “non-classical” siderophore functions have long paralleled those of iron transport. One particular non-classical function of these iron chelators, namely antibiotic activity, was even documented before the role of siderophores in iron transport was established. In this Perspective, we present an exposition of past and current work into non-classical functions of siderophores and highlight the directions in which we anticipate that this research is headed. Examples include the ability of siderophores to function as zincophores, chalkophores, and metallophores for a variety of other metals, sequester heavy metal toxins, transport boron, act as signalling molecules, regulate oxidative stress, and provide antibacterial activity. PMID:25764171

  18. Highlights from the Student Council Symposium 2011 at the International Conference on Intelligent Systems for Molecular Biology and European Conference on Computational Biology

    PubMed Central

    2011-01-01

    The Student Council (SC) of the International Society for Computational Biology (ISCB) organized their annual symposium in conjunction with the Intelligent Systems for Molecular Biology (ISMB) conference. This meeting report summarizes the scientific content of the Student Council Symposium 2011 as well as other activities organized by the Student Council in the context of ISMB. The symposium was held in Vienna, Austria on July 15th 2011.

  19. Computing the effective action with the functional renormalization group

    NASA Astrophysics Data System (ADS)

    Codello, Alessandro; Percacci, Roberto; Rachwał, Lesław; Tonero, Alberto

    2016-04-01

    The "exact" or "functional" renormalization group equation describes the renormalization group flow of the effective average action Γ _k. The ordinary effective action Γ _0 can be obtained by integrating the flow equation from an ultraviolet scale k=Λ down to k=0. We give several examples of such calculations at one-loop, both in renormalizable and in effective field theories. We reproduce the four-point scattering amplitude in the case of a real scalar field theory with quartic potential and in the case of the pion chiral Lagrangian. In the case of gauge theories, we reproduce the vacuum polarization of QED and of Yang-Mills theory. We also compute the two-point functions for scalars and gravitons in the effective field theory of scalar fields minimally coupled to gravity.

  20. Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts.

    PubMed

    Capitani, Guido; Duarte, Jose M; Baskaran, Kumaran; Bliven, Spencer; Somody, Joseph C

    2016-02-15

    Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein-protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein-protein docking. PMID:26508758

  1. Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts

    PubMed Central

    Capitani, Guido; Duarte, Jose M.; Baskaran, Kumaran; Bliven, Spencer; Somody, Joseph C.

    2016-01-01

    Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein–protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein–protein docking. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: guido.capitani@psi.ch PMID:26508758

  2. An Atomistic Statistically Effective Energy Function for Computational Protein Design.

    PubMed

    Topham, Christopher M; Barbe, Sophie; André, Isabelle

    2016-08-01

    Shortcomings in the definition of effective free-energy surfaces of proteins are recognized to be a major contributory factor responsible for the low success rates of existing automated methods for computational protein design (CPD). The formulation of an atomistic statistically effective energy function (SEEF) suitable for a wide range of CPD applications and its derivation from structural data extracted from protein domains and protein-ligand complexes are described here. The proposed energy function comprises nonlocal atom-based and local residue-based SEEFs, which are coupled using a novel atom connectivity number factor to scale short-range, pairwise, nonbonded atomic interaction energies and a surface-area-dependent cavity energy term. This energy function was used to derive additional SEEFs describing the unfolded-state ensemble of any given residue sequence based on computed average energies for partially or fully solvent-exposed fragments in regions of irregular structure in native proteins. Relative thermal stabilities of 97 T4 bacteriophage lysozyme mutants were predicted from calculated energy differences for folded and unfolded states with an average unsigned error (AUE) of 0.84 kcal mol(-1) when compared to experiment. To demonstrate the utility of the energy function for CPD, further validation was carried out in tests of its capacity to recover cognate protein sequences and to discriminate native and near-native protein folds, loop conformers, and small-molecule ligand binding poses from non-native benchmark decoys. Experimental ligand binding free energies for a diverse set of 80 protein complexes could be predicted with an AUE of 2.4 kcal mol(-1) using an additional energy term to account for the loss in ligand configurational entropy upon binding. The atomistic SEEF is expected to improve the accuracy of residue-based coarse-grained SEEFs currently used in CPD and to extend the range of applications of extant atom-based protein statistical

  3. (99m) Tc radiolabeling and biological evaluation of nanoparticles functionalized with a versatile coating ligand.

    PubMed

    Felber, Michael; Bauwens, Matthias; Mateos, José M; Imstepf, Sebastian; Mottaghy, Felix M; Alberto, Roger

    2015-04-13

    Radiolabeling allows noninvasive imaging by single photon emission computed tomography (SPECT) or positron emission tomography (PET) for assessing the biodistribution of nanostructures. Herein, the synthesis of a new coating ligand for gold nanoparticles (AuNPs) and quantum dots (QDs) is reported. This ligand is multifunctional; it combines the metal chelate with conjugating functions to biological vectors. The concept allows the coupling of any targeting function to the chelator; an example for the prostate specific membrane antigen is given. Derivatized NPs can directly be labeled in one step with [(99m) Tc(OH2 )3 (CO)3 ](+) . AuNPs in particular are highly stable, a prerequisite for in vivo studies excluding misinterpretation of the biodistribution data. AuNPs with differing sizes (7 and 14 nm core diameter) were administered intravenously into nude NMRI mice bearing LNCaP xenografts. MicroSPECT images show for both probes rapid clearance from the blood pool through the hepatobiliary pathway. The 7 nm AuNPs revealed a significantly higher bone uptake than the 14 nm AuNPs. The high affinity towards bone mineral is further confirmed in vitro with hydroxyapatite. PMID:25765900

  4. Computation of the lattice Green function for a dislocation

    NASA Astrophysics Data System (ADS)

    Tan, Anne Marie Z.; Trinkle, Dallas R.

    2016-08-01

    Modeling isolated dislocations is challenging due to their long-ranged strain fields. Flexible boundary condition methods capture the correct long-range strain field of a defect by coupling the defect core to an infinite harmonic bulk through the lattice Green function (LGF). To improve the accuracy and efficiency of flexible boundary condition methods, we develop a numerical method to compute the LGF specifically for a dislocation geometry; in contrast to previous methods, where the LGF was computed for the perfect bulk as an approximation for the dislocation. Our approach directly accounts for the topology of a dislocation, and the errors in the LGF computation converge rapidly for edge dislocations in a simple cubic model system as well as in BCC Fe with an empirical potential. When used within the flexible boundary condition approach, the dislocation LGF relaxes dislocation core geometries in fewer iterations than when the perfect bulk LGF is used as an approximation for the dislocation, making a flexible boundary condition approach more efficient.

  5. Engineering functional nanostructures for materials and biological applications

    NASA Astrophysics Data System (ADS)

    Subramani, Chandramouleeswaran

    Engineering nanostructures with complete control over the shape, composition, organization of the surface structures, and function remains a major challenge. In my work, I have fabricated nanostructures using functional polymer motifs and nanoparticles (NPs) via supramolecular and non-supramolecular interactions. In one of the approaches to generate nanostructures, I have integrated top-down approaches such as nanoimprint lithography, electron-beam lithography, and photolithography with the self-assembly (bottom-up) of NPs to provide nanostructures with tailored shape and function. In this strategy, I have developed a geometrically assisted orthogonal assembly of nanoparticles onto polymer features at precisely defined locations. This versatile NP functionalization method can be used to fabricate protein resistant patterned surfaces to provide essentially complete control over cellular alignment, making them promising biofunctional structures for cell patterning. In another approach, I have utilized self-assembly of dendrimers and NPs without preformed templates to generate nanostructures that can be used as chemoselective membranes for the separation of small and biomacromolecules.

  6. Exosome Function: From Tumor Immunology to Pathogen Biology

    PubMed Central

    Schorey, Jeffrey S.; Bhatnagar, Sanchita

    2009-01-01

    Exosomes are the newest family member of ‘bioactive vesicles’ that function to promote intercellular communication. Exosomes are derived from the fusion of multi-vesicular bodies with the plasma membrane and extracellular release of the intraluminal vesicles. Recent studies have focused on the biogenesis and composition of exosomes as well as regulation of exosome release. Exosomes have been shown to be released by cells of hematopoietic and non-hematopoietic origin, yet their function remains enigmatic. Much of the prior work has focused on exosomes as a source of tumor antigens and in presentation of tumor antigens to T cells. However, new studies have shown that exosomes might also promote cell-to-cell spread of infectious agents. Moreover, exosomes isolated from cells infected with various intra-cellular pathogens, including Mycobacterium tuberculosis and Toxoplasma gondii, have been shown to contain microbial components and can promote antigen presentation and macrophage activation, suggesting that exosomes may function in immune surveillance. In this review, we summarize our understanding of exosome biogenesis but focus primarily on new insights into exosome function. We also discuss their possible use as disease biomarkers and vaccine candidates. PMID:18331451

  7. Building DNA nanostructures for molecular computation, templated assembly, and biological applications.

    PubMed

    Rangnekar, Abhijit; LaBean, Thomas H

    2014-06-17

    CONSPECTUS: DNA is a critical biomolecule well-known for its roles in biology and genetics. Moreover, its double-helical structure and the Watson-Crick pairing of its bases make DNA structurally predictable. This predictability enables design and synthesis of artificial DNA nanostructures by suitable programming of the base sequences of DNA strands. Since the advent of the field of DNA nanotechnology in 1982, a variety of DNA nanostructures have been designed and used for numerous applications. In this Account, we discuss the progress made by our lab which has contributed toward the overall advancement of the field. Tile-based DNA nanostructures are an integral part of structural DNA nanotechnology. These structures are formed using several short, chemically synthesized DNA strands by programming their base sequences so that they self-assemble into desired constructs. Design and assembly of several DNA tiles will be discussed in this Account. Tiles include, for example, TX tiles with three parallel, coplanar duplexes, 4 × 4 cross-tiles with four arms, and weave-tiles with weave-like architecture. Another category of tiles we will present involve multiple parallel duplexes that assemble to form closed tubular structures. All of these tile types have been used to form micrometer-scale one- and two-dimensional arrays and lattices. Origami-based structures constitute another category where a long single-stranded DNA scaffold is folded into desired shapes by association with multiple short staple strands. This Account will describe the efforts by our lab in devising new strategies to improve the maximum size of origami structures. The various DNA nanostructures detailed here have been used in a wide variety of different applications. This Account will discuss the use of DNA tiles for logical computation, encoding information as molecular barcodes, and functionalization for patterning of other nanoscale organic and inorganic materials. Consequently, we have used DNA

  8. A proposal for augmenting biological model construction with a semi-intelligent computational modeling assistant

    PubMed Central

    Christley, Scott; An, Gary

    2013-01-01

    The translational challenge in biomedical research lies in the effective and efficient transfer of mechanistic knowledge from one biological context to another. Implicit in this process is the establishment of causality from correlation in the form of mechanistic hypotheses. Effectively addressing the translational challenge requires the use of automated methods, including the ability to computationally capture the dynamic aspect of putative hypotheses such that they can be evaluated in a high throughput fashion. Ontologies provide structure and organization to biomedical knowledge; converting these representations into executable models/simulations is the next necessary step. Researchers need the ability to map their conceptual models into a model specification that can be transformed into an executable simulation program. We suggest this mapping process, which approximates certain steps in the development of a computational model, can be expressed as a set of logical rules, and a semi-intelligent computational agent, the Computational Modeling Assistant (CMA), can perform reasoning to develop a plan to achieve the construction of an executable model. Presented herein is a description and implementation for a model construction reasoning process between biomedical and simulation ontologies that is performed by the CMA to produce the specification of an executable model that can be used for dynamic knowledge representation. PMID:23990750

  9. Calibration of Biokinetic and Biological Parameters for a Groundwater Bioremediation Model using Heuristics and Function Approximation Optimization

    NASA Astrophysics Data System (ADS)

    Mugunthan, P.; Shoemaker, C. A.; Regis, R. G.

    2003-12-01

    Heuristics and function approximation optimization methods were applied in calibrating biological and biokinetic parameters for a computationally expensive groundwater bioremediation model for engineered reductive dechlorination of chlorinated ethenes. Multi-species groundwater bioremediation models that use monod type kinetics are often not amenable to traditional derivative based optimization due to stiff biokinetic equations. The performance of three heuristic methods, Stochastic Greedy Search (GS), Real Genetic Algorithm (RGA), Derandomized Evolution Strategy (DES), and, Function Approximation Optimization based on Radial Basis Function (FA-RBF) were compared on three-dimensional hypothetical and field problems. GS was implemented so as to perform a more global search. Optimization results on hypothetical problem indicated that FA-RBF performed statistically significantly better than heuristic based evolutionary algorithms at a 10% significance level. Further, this particular implementation of GS performed well and proved superior to RGA. These heuristic methods and FA-RBF, with the exception of RGA, were applied to calibrate biological and biokinetic parameters using treatability test data for enhanced bioremediation at a Naval Air Station in Alameda Point, CA. All three methods performed well and identified similar solutions. The approximate simulation times for the hypothetical and real problems were 7 min and 2.5 hours respectively. Calibration of such computationally expensive models by heuristic and function approximation methods appears promising.

  10. Functional crosstalk between membrane lipids and TLR biology.

    PubMed

    Köberlin, Marielle S; Heinz, Leonhard X; Superti-Furga, Giulio

    2016-04-01

    Toll-like receptors (TLRs) are important transmembrane proteins of the innate immune system that detect invading pathogens and subsequently orchestrate an immune response. The ensuing inflammatory processes are connected to lipid metabolism at multiple levels. Here, we describe different aspects of how membrane lipids can shape the response of TLRs. Recent reports have uncovered the role of individual lipid species on membrane protein function and mouse models have contributed to the understanding of how changes in lipid metabolism alter TLR signaling, endocytosis, and cytokine secretion. Finally, we discuss the importance of systematic approaches to identify the function of individual lipid species or the composition of membrane lipids in TLR-related processes. PMID:26895312

  11. Functionalization of carbon nanotube and nanofiber electrodes with biological macromolecules: Progress toward a nanoscale biosensor

    NASA Astrophysics Data System (ADS)

    Baker, Sarah E.

    The integration of nanoscale carbon-based electrodes with biological recognition and electrical detection promises unparalleled biological detection systems. First, biologically modified carbon-based materials have been shown to have superior long-term chemical stability when compared to other commonly used materials for biological detection such as silicon, gold, and glass surfaces. Functionalizing carbon electrodes for biological recognition and using electrochemical methods to transduce biological binding information will enable real-time, hand-held, lower cost and stable biosensing devices. Nanoscale carbon-based electrodes allow the additional capability of fabricating devices with high densities of sensing elements, enabling multi-analyte detection on a single chip. We have worked toward the integration of these sensor components by first focusing on developing and characterizing the chemistry required to functionalize single-walled carbon nanotubes and vertically aligned carbon nanofibers with oligonucleotides and proteins for specific biological recognition. Chemical, photochemical and electrochemical methods for functionalizing these materials with biological molecules were developed. We determined, using fluorescence and colorimetric techniques, that these biologically modified nanoscale carbon electrodes are biologically active, selective, and stable. A photochemical functionalization method enabled facile functionalization of dense arrays vertically aligned carbon nanofiber forests. We found that much of the vertically aligned carbon nanofiber sidewalls were functionalized and biologically accessible by this method---the absolute number of DNA molecules hybridized to DNA-functionalized nanofiber electrodes was ˜8 times higher than the number of DNA molecules hybridized to flat glassy carbon electrodes and implies that nanofiber forest sensors may facilitate higher sensitivity to target DNA sequences per unit area. We also used the photochemical method

  12. STRIPAK Complexes: structure, biological function, and involvement in human diseases

    PubMed Central

    Hwang, Juyeon; Pallas, David C.

    2014-01-01

    The mammalian striatin family consists of three proteins, striatin, S/G2 nuclear autoantigen, and zinedin. Striatin family members have no intrinsic catalytic activity, but rather function as scaffolding proteins. Remarkably, they organize multiple diverse, large signaling complexes that participate in a variety of cellular processes. Moreover, they appear to be regulatory/targeting subunits for the major eukaryotic serine/threonine protein phosphatase 2A. In addition, striatin family members associate with germinal center kinase III kinases as well as other novel components, earning these assemblies the name striatin-interacting phosphatase and kinase (STRIPAK) complexes. Recently, there has been a great increase in functional and mechanistic studies aimed at identifying and understanding the roles of STRIPAK–like complexes in cellular processes of multiple organisms. These studies have identified novel STRIPAK or STRIPAK-like complexes and have explored their roles in specific signaling pathways. Together, the results of these studies have sparked increased interest in striatin family complexes because they have revealed roles in signaling, cell cycle control, apoptosis, vesicular trafficking, Golgi assembly, cell polarity, cell migration, neural and vascular development, and cardiac function. Moreover, STRIPAK complexes have been connected to clinical conditions, including cardiac disease, diabetes, autism, and cerebral cavernous malformation. In this review, we discuss the expression, localization, and protein domain structure of striatin family members. Then we consider the diverse complexes these proteins and their homologs form in various organisms, emphasizing what is known regarding function and regulation. Finally, we will explore possible roles of striatin family complexes in disease, especially cerebral cavernous malformation. PMID:24333164

  13. Functional Nanostructured Platforms for Chemical and Biological Sensing

    SciTech Connect

    Letant, S E

    2006-03-20

    The central goal of our work is to combine semiconductor nanotechnology and surface functionalization in order to build platforms for the selective detection of bio-organisms ranging in size from bacteria (micron range) down to viruses, as well as for the detection of chemical agents (nanometer range). We will show on three porous silicon platforms how pore geometry and pore wall chemistry can be combined and optimized to capture and detect specific targets. We developed a synthetic route allowing to directly anchor proteins on silicon surfaces and illustrated the relevance of this technique by immobilizing live enzymes onto electrochemically etched luminescent nano-porous silicon. The powerful association of the specific enzymes with the transducing matrix led to a selective hybrid platform for chemical sensing. We also used light-assisted electrochemistry to produce periodic arrays of through pores on pre-patterned silicon membranes with controlled diameters ranging from many microns down to tens of nanometers. We demonstrated the first covalently functionalized silicon membranes and illustrated their selective capture abilities with antibody-coated micro-beads. These engineered membranes are extremely versatile and could be adapted to specifically recognize the external fingerprints (size and coat composition) of target bio-organisms. Finally, we fabricated locally functionalized single nanopores using a combination of focused ion beam drilling and ion beam assisted oxide deposition. We showed how a silicon oxide ring can be grown around a single nanopore and how it can be functionalized with DNA probes to detect single viral-sized beads. The next step for this platform is the detection of whole viruses and bacteria.

  14. Functional nanostructured platforms for chemical and biological sensing

    NASA Astrophysics Data System (ADS)

    Létant, S. E.

    2006-05-01

    The central goal of our work is to combine semiconductor nanotechnology and surface functionalization in order to build platforms for the selective detection of bio-organisms ranging in size from bacteria (micron range) down to viruses, as well as for the detection of chemical agents (nanometer range). We will show on three porous silicon platforms how pore geometry and pore wall chemistry can be combined and optimized to capture and detect specific targets. We developed a synthetic route allowing to directly anchor proteins on silicon surfaces and illustrated the relevance of this technique by immobilizing live enzymes onto electrochemically etched luminescent nano-porous silicon. The powerful association of the specific enzymes with the transducing matrix led to a selective hybrid platform for chemical sensing. We also used light-assisted electrochemistry to produce periodic arrays of through pores on pre-patterned silicon membranes with controlled diameters ranging from many microns down to tens of nanometers. We demonstrated the first covalently functionalized silicon membranes and illustrated their selective capture abilities with antibody-coated micro-beads. These engineered membranes are extremely versatile and could be adapted to specifically recognize the external fingerprints (size and coat composition) of target bio-organisms. Finally, we fabricated locally functionalized single nanopores using a combination of focused ion beam drilling and ion beam assisted oxide deposition. We showed how a silicon oxide ring can be grown around a single nanopore and how it can be functionalized with DNA probes to detect single viral-sized beads. The next step for this platform is the detection of whole viruses and bacteria.

  15. Biological factors of natural and artificial ecosystems stable (unstable) functioning

    NASA Astrophysics Data System (ADS)

    Pechurkin, Nikolai S.

    The problem of sustainable development of humanity on Earth and the problem of supporting human life in space have the same scientific and methodological bases. The key to solve both problems is a long term maintenance of balanced material cycle. As a whole, natural or artificial ecosystems are to be more closed than open, but their elements (links of systems) are to be substantially open in interactions with each other. Prolonged stable interactions of different links have to have unique joint results - closed material cycling or biotic turnover. It is necessary to include, at least, three types of main links into any system to support real material cycling: producers, consumers, reducers. Producer links are now under studies in many laboratories. It is evident that the higher productivity of link, the lower link stability. Especially, it concerns with parasite impact to plants. As usual, artificial ecosystems are more simple (incomplete) than natural ecosystems, sometimes, they have not enough links for prolonged stable functioning. For example, life support system for space flight can be incomplete in consumer link, having only some crew persons, instead of interacting populations of consumers. As for reducer link, it is necessary to "organize" a special coordinated work of microbial biocenoses to fulfill proper cycling. Possible evolution of links, their self development is a matter of special attention for the maintenance of prolonged stable functioning. It's the most danger for systems with populations of quickly reproducing, so-called, R - strategists, according to symbols of logistic equation. From another side, quick reproduction of R - strategists is able to increase artificial ecosystems and their links functioning. After some damages of system, R - strategist's link can be quickly "self repaired" up to level of normal functioning. Some experimental data of this kind and mathematical models are to be discussed in the paper. This work is supported by

  16. Oxygen flux analysis to understand the biological function of sirtuins.

    PubMed

    Wang, Dongning; Green, Michelle F; McDonnell, Eoin; Hirschey, Matthew D

    2013-01-01

    The sirtuins are a family of highly conserved NAD(+)-dependent lysine deacylases with important roles in metabolic regulation. Of the seven mammalian sirtuins, three localize to the mitochondria: SIRT3, SIRT4, and SIRT5. Mitochondrial sirtuins are crucial regulators of the metabolic network that controls energy homeostasis and impacts cancer, obesity, diabetes, mitochondrial diseases, metabolic disorders, and many other human diseases of aging. To best study the mitochondrial function of the sirtuins, we have employed an oxygen flux analyzer as a tool to track and record the extracellular oxygen consumption rate and acidification rate that reflects mitochondrial respiration and glycolysis, respectfully. Here we described the methods using this assay to study the substrate utilization and mitochondrial function in a human hepatocellular carcinoma cell line, Huh7. Additionally, we have generated a stable SIRT4 knocked-down Huh7 cell line. With this cell line, we evaluated how the absence of SIRT4 affects mitochondrial function, glucose utilization, glutamine oxidation, and fatty acid oxidation in these cells. PMID:24014411

  17. Effects of mechanical ventilation on diaphragm function and biology.

    PubMed

    Gayan-Ramirez, G; Decramer, M

    2002-12-01

    The pathophysiological mechanisms of weaning from mechanical ventilation are not fully known, but there is accumulating evidence that mechanical ventilation induces inspiratory muscle dysfunction. Recently, several animal models have provided potential mechanisms for mechanical ventilation-induced effects on muscle function. In patients, weaning difficulties are associated with inspiratory muscle weakness and reduced endurance capacity. Animal studies demonstrated that diaphragm force was already decreased after 12 h of controlled mechanical ventilation and this worsened with time spent on the ventilator. Diaphragmatic myofibril damage observed after 3-days controlled mechanical ventilation was inversely correlated with maximal diaphragmatic force. Downregulation of the diaphragm insulin-like growth factor-I and MyoD/myogenin messenger ribonucleic acid occurred after 24 h and diaphragmatic oxidative stress and increased protease activity after 18 h. In keeping with these findings, diaphragm fibre atrophy was shown after 12 h and reduced diaphragm mass was reported after 48 h of controlled mechanical ventilation. These animal studies show that early alterations in diaphragm function develop after short-term mechanical ventilation. These alterations may contribute to the difficulties in weaning from mechanical ventilation seen in patients. Strategies to preserve respiratory muscle mass and function during mechanical ventilation should be developed. These may include: adaptation of medication, training of the diaphragm, stabilisation of the catabolic state and pharmacotherapy. PMID:12503720

  18. Computational modeling of skin reflectance spectra for biological parameter estimation through machine learning

    NASA Astrophysics Data System (ADS)

    Vyas, Saurabh; Van Nguyen, Hien; Burlina, Philippe; Banerjee, Amit; Garza, Luis; Chellappa, Rama

    2012-06-01

    A computational skin re ectance model is used here to provide the re ectance, absorption, scattering, and transmittance based on the constitutive biological components that make up the layers of the skin. The changes in re ectance are mapped back to deviations in model parameters, which include melanosome level, collagen level and blood oxygenation. The computational model implemented in this work is based on the Kubelka- Munk multi-layer re ectance model and the Fresnel Equations that describe a generic N-layer model structure. This assumes the skin as a multi-layered material, with each layer consisting of specic absorption, scattering coecients, re ectance spectra and transmittance based on the model parameters. These model parameters include melanosome level, collagen level, blood oxygenation, blood level, dermal depth, and subcutaneous tissue re ectance. We use this model, coupled with support vector machine based regression (SVR), to predict the biological parameters that make up the layers of the skin. In the proposed approach, the physics-based forward mapping is used to generate a large set of training exemplars. The samples in this dataset are then used as training inputs for the SVR algorithm to learn the inverse mapping. This approach was tested on VIS-range hyperspectral data. Performance validation of the proposed approach was performed by measuring the prediction error on the skin constitutive parameters and exhibited very promising results.

  19. Resilin-Like Polypeptide Hydrogels Engineered for Versatile Biological Functions.

    PubMed

    Li, Linqing; Tong, Zhixiang; Jia, Xinqiao; Kiick, Kristi L

    2013-01-01

    Natural resilin, the rubber-like protein that exists in specialized compartments of most arthropods, possesses excellent mechanical properties such as low stiffness, high resilience and effective energy storage. Recombinantly-engineered resilin-like polypeptides (RLPs) that possess the favorable attributes of native resilin would be attractive candidates for the modular design of biomaterials for engineering mechanically active tissues. Based on our previous success in creating a novel RLP-based hydrogel and demonstrating useful mechanical and cell-adhesive properties, we have produced a suite of new RLP-based constructs, each equipped with 12 repeats of the putative resilin consensus sequence and a single, distinct biologically active domain. This approach allows independent control over the concentrations of cell-binding, MMP-sensitive, and polysaccharide-sequestration domains in hydrogels comprising mixtures of the various RLPs. The high purity, molecular weight and correct compositions of each new polypeptide have been confirmed via high performance liquid chromatography (HPLC), sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), and amino acid analysis. These RLP-based polypeptides exhibit largely random-coil conformation, both in solution and in the cross-linked hydrogels, as indicated by circular dichroic and infrared spectroscopic analyses. Hydrogels of various compositions, with a range of elastic moduli (1kPa to 25kPa) can be produced from these polypeptides, and the activity of the cell-binding and matrix metalloproteinase (MMP) sensitive domains was confirmed. Tris(hydroxymethyl phosphine) cross-linked RLP hydrogels were able to maintain their mechanical integrity as well as the viability of encapsulated primary human mesenchymal stem cells (MSCs). These results validate the promising properties of these RLP-based elastomeric biomaterials. PMID:23505396

  20. Computational optimization for S-type biological systems: cockroach genetic algorithm.

    PubMed

    Wu, Shinq-Jen; Wu, Cheng-Tao

    2013-10-01

    S-type biological systems (S-systems) are demonstrated to be universal approximations of continuous biological systems. S-systems are easy to be generalized to large systems. The systems are identified through data-driven identification techniques (cluster-based algorithms or computational methods). However, S-systems' identification is challenging because multiple attractors exist in such highly nonlinear systems. Moreover, in some biological systems the interactive effect cannot be neglected even the interaction order is small. Therefore, learning should be focused on increasing the gap between the true and redundant interaction. In addition, a wide searching space is necessary because no prior information is provided. The used technologies should have the ability to achieve convergence enhancement and diversity preservation. Cockroaches live in nearly all habitats and survive for more than 300 million years. In this paper, we mimic cockroaches' competitive swarm behavior and integrated it with advanced evolutionary operations. The proposed cockroach genetic algorithm (CGA) possesses strong snatching-food ability to rush forward to a target and high migration ability to escape from local minimum. CGA was tested with three small-scale systems, a twenty-state medium-scale system and a thirty-state large-scale system. A wide search space ([0,100] for rate constants and [-100,100] for kinetic orders) with random or bad initial starts are used to show the high exploration performance. PMID:23927855

  1. The role of computer networking in investigating unusual disease outbreaks and allegations of biological and toxin weapons use.

    PubMed

    Woodall, J

    1998-01-01

    Computer networking can aid in the epidemiological investigation of unusual disease outbreaks and possible uses of biological weapons. Exchange of computerized data over the Internet has many advantages in facilitating the investigation of the source of a disease outbreak. It is especially useful in the investigation of suspected or alleged releases of biological weapons. Computer networking through the Internet a fosters a truly global disease outbreak early warning system in which both government and non-government sources are contributing. Such information exchange is of great potential benefit to the Biological Weapons Convention and the attempts to develop a verification protocol. PMID:9800103

  2. [Dialectic of the interrelationship between structure and function in biology and medicine].

    PubMed

    Strukov, A I; Kakturskiĭ, L V

    1977-01-01

    The paper deals with some aspects of the dialectics of structure and function relationships in biological objects normally and pathologically. Idealistic and metaphysical concepts of the structure-function relationships (morphological idealism, holism, physiological idealism, functionalism) are critisized, and historical premises of these concepts are characterized. The principle of indissoluble unity and interconnection of changes in structure and function is emphasized, while the thesis of the primacy of function in the shaping of the form and the concept of functional diseases are rejected. Much attention is paid to the methodological principles of the study of structure and function based on the systemic approach to the investigation of biological objects from the point of view of structural levels and integratism. The groundlessness of the principles of reductionism and organicism in the solution of this problem is indicated. The connection of the concepts of structure and function with categories and laws of materialistic dialectics is dwelt on. PMID:880057

  3. Estrogen Biology: New Insights into GPER Function and Clinical Opportunities

    PubMed Central

    Prossnitz, Eric R.; Barton, Matthias

    2014-01-01

    Estrogens play an important role in the regulation of normal physiology, aging and many disease states. Although the nuclear estrogen receptors have classically been described to function as ligand-activated transcription factors mediating genomic effects in hormonally regulated tissues, more recent studies reveal that estrogens also mediate rapid signaling events traditionally associated with G protein-coupled receptors. The G protein-coupled estrogen receptor GPER (formerly GPR30) has now become recognized as a major mediator of estrogen’s rapid cellular effects throughout the body. With the discovery of selective synthetic ligands for GPER, both agonists and antagonists, as well as the use of GPER knockout mice, significant advances have been made in our understanding of GPER function at the cellular, tissue and organismal levels. In many instances, the protective/beneficial effects of estrogen are mimicked by selective GPER agonism and are absent or reduced in GPER knockout mice, suggesting an essential or at least parallel role for GPER in the actions of estrogen. In this review, we will discuss recent advances and our current understanding of the role of GPER and certain drugs such as SERMs and SERDs in physiology and disease. We will also highlight novel opportunities for clinical development towards GPER-targeted therapeutics, for molecular imaging, as well as for theranostic approaches and personalized medicine. PMID:24530924

  4. The biomolecule ubiquinone exerts a variety of biological functions.

    PubMed

    Nohl, Hans; Staniek, Katrin; Kozlov, Andrey V; Gille, Lars

    2003-01-01

    The chemistry of ubiquinone allows reversible addition of single electrons and protons. This unique property is used in nature for aerobic energy gain, for unilateral proton accumulation, for the generation of reactive oxygen species involved in physiological signaling and a variety of pathophysiological events. Since several years ubiquinone is also considered to play a major role in the control of lipid peroxidation, since this lipophilic biomolecule was recognized to recycle alpha-tocopherol radicals back to the chain-breaking form, vitamin E. Ubiquinone is therefore a biomolecule which has increasingly focused the interest of many research groups due to its alternative pro- and antioxidant activity. We have intensively investigated the role of ubiquinone as prooxidant in mitochondria and will present experimental evidences on conditions required for this function, we will also show that lysosomal ubiquinone has a double function as proton translocator and radical source under certain metabolic conditions. Furthermore, we have addressed the antioxidant role of ubiquinone and found that the efficiency of this activity is widely dependent on the type of biomembrane where ubiquinone exerts its chain-breaking activity. PMID:14695917

  5. Spruce Budworm (Lepidoptera: Tortricidae) Oral Secretions I: Biology and Function.

    PubMed

    Eveleigh, Eldon; Silk, Peter; Leclair, Gaëtan; Mayo, Peter; Francis, Brittany; Williams, Martin

    2015-12-01

    The potential roles of the oral secretions (OS) of spruce budworm (SBW; Choristoneura fumiferana Clemens) larvae and factors that may affect the volume of OS disgorged were investigated in the laboratory. Experiments revealed that diet-fed SBW larvae readily disgorge OS when induced ("milked"), with minimal overall cost to their development and eventual pupal weight. Exposure of conspecific larvae to OS throughout larval development negatively affected survival and male pupal weight; however, male development time was faster when exposed to OS. Female pupal weight and development time were not affected. Preliminary experiments suggested that OS had a repellent effect on a co-occurring herbivore, the false hemlock looper, Nepytia canosaria (Walker). OS produced by larvae that fed on three host tree species and on artificial diet significantly increased the grooming time of ants (Camponotus sp.), indicating that SBW OS have an anti-predator function. The volume of OS is significantly greater in L6 than in L4 or L5, with the volume produced by L6 depending on weight and age as well as feeding history at time of milking. These findings indicate that SBW OS function as both an intra- and interspecific epideictic pheromone and as an anti-predator defensive mechanism, while incurring minimal metabolic costs. PMID:26454475

  6. More Ideas for Monitoring Biological Experiments with the BBC Computer: Absorption Spectra, Yeast Growth, Enzyme Reactions and Animal Behaviour.

    ERIC Educational Resources Information Center

    Openshaw, Peter

    1988-01-01

    Presented are five ideas for A-level biology experiments using a laboratory computer interface. Topics investigated include photosynthesis, yeast growth, animal movements, pulse rates, and oxygen consumption and production by organisms. Includes instructions specific to the BBC computer system. (CW)

  7. An Evolutionary Computation Approach to Examine Functional Brain Plasticity.

    PubMed

    Roy, Arnab; Campbell, Colin; Bernier, Rachel A; Hillary, Frank G

    2016-01-01

    One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs) evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC) based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair) such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN) and the executive control network (ECN) during recovery from traumatic brain injury (TBI); the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in the strength

  8. An Evolutionary Computation Approach to Examine Functional Brain Plasticity

    PubMed Central

    Roy, Arnab; Campbell, Colin; Bernier, Rachel A.; Hillary, Frank G.

    2016-01-01

    One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs) evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC) based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair) such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN) and the executive control network (ECN) during recovery from traumatic brain injury (TBI); the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in the strength

  9. Computer Modeling of Protocellular Functions: Peptide Insertion in Membranes

    NASA Technical Reports Server (NTRS)

    Rodriquez-Gomez, D.; Darve, E.; Pohorille, A.

    2006-01-01

    Lipid vesicles became the precursors to protocells by acquiring the capabilities needed to survive and reproduce. These include transport of ions, nutrients and waste products across cell walls and capture of energy and its conversion into a chemically usable form. In modem organisms these functions are carried out by membrane-bound proteins (about 30% of the genome codes for this kind of proteins). A number of properties of alpha-helical peptides suggest that their associations are excellent candidates for protobiological precursors of proteins. In particular, some simple a-helical peptides can aggregate spontaneously and form functional channels. This process can be described conceptually by a three-step thermodynamic cycle: 1 - folding of helices at the water-membrane interface, 2 - helix insertion into the lipid bilayer and 3 - specific interactions of these helices that result in functional tertiary structures. Although a crucial step, helix insertion has not been adequately studied because of the insolubility and aggregation of hydrophobic peptides. In this work, we use computer simulation methods (Molecular Dynamics) to characterize the energetics of helix insertion and we discuss its importance in an evolutionary context. Specifically, helices could self-assemble only if their interactions were sufficiently strong to compensate the unfavorable Free Energy of insertion of individual helices into membranes, providing a selection mechanism for protobiological evolution.

  10. FOREWORD: Third Nordic Symposium on Computer Simulation in Physics, Chemistry, Biology and Mathematics

    NASA Astrophysics Data System (ADS)

    Kaski, K.; Salomaa, M.

    1990-01-01

    These are Proceedings of the Third Nordic Symposium on Computer Simulation in Physics, Chemistry, Biology, and Mathematics, held August 25-26, 1989, at Lahti (Finland). The Symposium belongs to an annual series of Meetings, the first one of which was arranged in 1987 at Lund (Sweden) and the second one in 1988 at Kolle-Kolle near Copenhagen (Denmark). Although these Symposia have thus far been essentially Nordic events, their international character has increased significantly; the trend is vividly reflected through contributions in the present Topical Issue. The interdisciplinary nature of Computational Science is central to the activity; this fundamental aspect is also responsible, in an essential way, for its rapidly increasing impact. Crucially important to a wide spectrum of superficially disparate fields is the common need for extensive - and often quite demanding - computational modelling. For such theoretical models, no closed-form (analytical) solutions are available or they would be extremely difficult to find; hence one must rather resort to the Art of performing computational investigations. Among the unifying features in the computational research are the methods of simulation employed; methods which frequently are quite closely related with each other even for faculties of science that are quite unrelated. Computer simulation in Natural Sciences is presently apprehended as a discipline on its own right, occupying a broad region somewhere between the experimental and theoretical methods, but also partially overlapping with and complementing them. - Whichever its proper definition may be, the computational approach serves as a novel and an extremely versatile tool with which one can equally well perform "pure" experimental modelling and conduct "computational theory". Computational studies that have earlier been made possible only through supercomputers have opened unexpected, as well as exciting, novel frontiers equally in mathematics (e.g., fractals

  11. Understanding the self-assembly of nanoscale biological systems through computational modeling

    NASA Astrophysics Data System (ADS)

    Sullivan, Daniel R.

    There has recently been much interest in exploiting or guiding the self-assembling of biological systems for fabricating functional nanoscale devices or components that requiring precise placement and alignment of components. Biological materials such as proteins, DNA, and some plant virus components are especially suited to this task due to their well- understood chemistry, interactions with inorganic components, and size-commensurability with templates designed for practical bionanotechnological applications. Due to experimental limitations on precisely tracking and controlling the assembly processes of these nanoscale systems, a fundamental understanding of the physical mechanisms governing nanobiological organization onto surfaces and templates has not yet been developed. This thesis aims to use classical molecular dynamics to simulate the organization behaviour of two unique nanobiological systems (viruses and collagen assembled on surfaces) and provide insight into the key processes and conditions driving organization.

  12. The functions of biological diversity in an age of extinction.

    PubMed

    Naeem, Shahid; Duffy, J Emmett; Zavaleta, Erika

    2012-06-15

    Ecosystems worldwide are rapidly losing taxonomic, phylogenetic, genetic, and functional diversity as a result of human appropriation of natural resources, modification of habitats and climate, and the spread of pathogenic, exotic, and domestic plants and animals. Twenty years of intense theoretical and empirical research have shown that such biotic impoverishment can markedly alter the biogeochemical and dynamic properties of ecosystems, but frontiers remain in linking this research to the complexity of wild nature, and in applying it to pressing environmental issues such as food, water, energy, and biosecurity. The question before us is whether these advances can take us beyond merely invoking the precautionary principle of conserving biodiversity to a predictive science that informs practical and specific solutions to mitigate and adapt to its loss. PMID:22700920

  13. Structure and biological functions of keratan sulfate proteoglycans.

    PubMed

    Greiling, H

    1994-01-01

    The skeletal and corneal keratan sulfate proteoglycans show a different metabolic and structural heterogeneity. The domain structure of the carbohydrate chain has been shown to be different in various animal species. There are two major types of skeletal keratan sulfate proteoglycans with and without fucose. The protein cores of the corneal chicken keratan sulfate proteoglycan (lumican) and those of another small keratan sulfate proteoglycan (fibromodulin) have been sequenced. Keratan sulfate oligosaccharides belong to the members of an antigen family of the poly-N-acetyllactosamine series. Monoclonal antibodies and immunoassay procedures for keratan sulfate proteoglycans have been prepared. In osteoarthritis, no significant specific increase of keratan sulfate has been found. Keratan sulfate is a functional substitute for chondroitin sulfate in O2-deficient tissues. PMID:8298243

  14. The biology and function of exosomes in cancer.

    PubMed

    Kalluri, Raghu

    2016-04-01

    Humans circulate quadrillions of exosomes at all times. Exosomes are a class of extracellular vesicles released by all cells, with a size range of 40-150 nm and a lipid bilayer membrane. Exosomes contain DNA, RNA, and proteins. Exosomes likely remove excess and/or unnecessary constituents from the cells, functioning like garbage bags, although their precise physiological role remains unknown. Additionally, exosomes may mediate specific cell-to-cell communication and activate signaling pathways in cells they fuse or interact with. Exosomes are detected in the tumor microenvironment, and emerging evidence suggests that they play a role in facilitating tumorigenesis by regulating angiogenesis, immunity, and metastasis. Circulating exosomes can be used as liquid biopsies and noninvasive biomarkers for early detection, diagnosis, and treatment of cancer patients. PMID:27035812

  15. Computational Multiscale Toxicodynamic Modeling of Silver and Carbon Nanoparticle Effects on Mouse Lung Function

    PubMed Central

    Mukherjee, Dwaipayan; Botelho, Danielle; Gow, Andrew J.; Zhang, Junfeng; Georgopoulos, Panos G.

    2013-01-01

    A computational, multiscale toxicodynamic model has been developed to quantify and predict pulmonary effects due to uptake of engineered nanomaterials (ENMs) in mice. The model consists of a collection of coupled toxicodynamic modules, that were independently developed and tested using information obtained from the literature. The modules were developed to describe the dynamics of tissue with explicit focus on the cells and the surfactant chemicals that regulate the process of breathing, as well as the response of the pulmonary system to xenobiotics. Alveolar type I and type II cells, and alveolar macrophages were included in the model, along with surfactant phospholipids and surfactant proteins, to account for processes occurring at multiple biological scales, coupling cellular and surfactant dynamics affected by nanoparticle exposure, and linking the effects to tissue-level lung function changes. Nanoparticle properties such as size, surface chemistry, and zeta potential were explicitly considered in modeling the interactions of these particles with biological media. The model predictions were compared with in vivo lung function response measurements in mice and analysis of mice lung lavage fluid following exposures to silver and carbon nanoparticles. The predictions were found to follow the trends of observed changes in mouse surfactant composition over 7 days post dosing, and are in good agreement with the observed changes in mouse lung function over the same period of time. PMID:24312506

  16. Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

    PubMed Central

    van den Berg, Bart H. J.; McCarthy, Fiona M.; Lamont, Susan J.; Burgess, Shane C.

    2010-01-01

    One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data. PMID:20498845

  17. Structure and functions of water-membrane interfaces and their role in proto-biological evolution

    NASA Technical Reports Server (NTRS)

    Pohorille, A.; Wilson, M.; Macelroy, R. D.

    1991-01-01

    Among the most important developments in proto-biological evolution was the emergence of membrane-like structures. These are formed by spontaneous association of relatively simple amphiphilic molecules that would have been readily available in the primordial environment. The resulting interfacial regions between water and nonpolar interior of the membrane have several properties which made them uniquely suitable for promoting subsequent evolution. They can (1) selectively attract organic material and mediate its transport, (2) serve as simple catalysts for chemical reactions, and (3) promote the formation of trans-membrane electrical and chemical gradients which could provide energy sources for proto-cells. Understanding the structure of interfaces, their interactions with organic molecules and molecular mechanisms of their functions is an essential step to understanding proto-biological evolution. In our computer simulation studies, we showed that the structure of water at interfaces with nonpolar media is significantly different from that in the bulk. In particular, the average surface dipole density points from the vapor to the liquid. As a result, negative ions can approach the interface more easily than positive ions. Amphiphilic molecules composed of hydrocarbon conjugated rings and polar substituents (e.g., phenol) assume at the interface rigid orientations in which polar groups are buried in water while hydrocarbon parts are located in the nonpolar environment. These orientational differences are of special interest in connection with the ability of some of these molecules to efficiently absorb photons. Flexible molecules with polar substituents often adopt at interfaces conformations different from those in the bulk aquaeous solution and in the gas phase. As a result, in many instances both specificity and kinetics of chemical reactions in which these molecules can participate is modified by the presence of surfaces. Of special interest is the mechanism by

  18. Computation of diffusion function measures in q-space using magnetic resonance hybrid diffusion imaging.

    PubMed

    Wu, Yu-Chien; Field, Aaron S; Alexander, Andrew L

    2008-06-01

    The distribution of water diffusion in biological tissues may be estimated by a 3-D Fourier transform (FT) of diffusion-weighted measurements in q-space. In this study, methods for estimating diffusion spectrum measures (the zero-displacement probability, the mean-squared displacement, and the orientation distribution function) directly from the q-space signals are described. These methods were evaluated using both computer simulations and hybrid diffusion imaging (HYDI) measurements on a human brain. The HYDI method obtains diffusion-weighted measurements on concentric spheres in q-space. Monte Carlo computer simulations were performed to investigate effects of noise, q-space truncation, and sampling interval on the measures. This new direct computation approach reduces HYDI data processing time and image artifacts arising from 3-D FT and regridding interpolation. In addition, it is less sensitive to the noise and q-space truncation effects than conventional approach. Although this study focused on data using the HYDI scheme, this computation approach may be applied to other diffusion sampling schemes including Cartesian diffusion spectrum imaging. PMID:18541492

  19. Discovering and validating biological hypotheses from coherent patterns in functional genomics data

    SciTech Connect

    Joachimiak, Marcin Pawel

    2008-08-12

    The area of transcriptomics analysis is among the more established in computational biology, having evolved in both technology and experimental design. Transcriptomics has a strong impetus to develop sophisticated computational methods due to the large amounts of available whole-genome datasets for many species and because of powerful applications in regulatory network reconstruction as well as elucidation and modeling of cellular transcriptional responses. While gene expression microarray data can be noisy and comparisons across experiments challenging, there are a number of sophisticated methods that aid in arriving at statistically and biologically significant conclusions. As such, computational transcriptomics analysis can provide guidance for analysis of results from newer experimental technologies. More recently, search methods have been developed to identify modules of genes, which exhibit coherent expression patterns in only a subset of experimental conditions. The latest advances in these methods allow to integrate multiple data types anddatasets, both experimental and computational, within a single statistical framework accounting for data confidence and relevance to specific biological questions. Such frameworks provide a unified environment for the exploration of specific biological hypothesis and for the discovery of coherent data patterns along with the evidence supporting them.

  20. Functional Tissue Engineering of Tendon: Establishing Biological Success Criteria for Improving Tendon Repair

    PubMed Central

    Breidenbach, Andrew P; Gilday, Steven D; Lalley, Andrea L; Dyment, Nathaniel A; Gooch, Cynthia; Shearn, Jason T; Butler, David L

    2013-01-01

    Improving tendon repair using Functional Tissue Engineering (FTE) principles has been the focus of our laboratory over the last decade. Although our primary goals were initially focused only on mechanical outcomes, we are now carefully assessing the biological properties of our tissue-engineered tendon repairs so as to link biological influences with mechanics. However, given the complexities of tendon development and healing, it remains challenging to determine which aspects of tendon biology are the most important to focus on in the context of tissue engineering. To address this problem, we have formalized a strategy to identify, prioritize, and evaluate potential biological success criteria for tendon repair. We have defined numerous biological properties of normal tendon relative to cellular phenotype, extracellular matrix and tissue ultra-structure that we would like to reproduce in our tissue-engineered repairs and prioritized these biological criteria by examining their relative importance during both normal development and natural tendon healing. Here, we propose three specific biological criteria which we believe are essential for normal tendon function: 1) scleraxis-expressing cells; 2) well-organized and axially-aligned collagen fibrils having bimodal diameter distribution; and 3) a specialized tendon-to-bone insertion site. Moving forward, these biological success criteria will be used in conjunction with our already established mechanical success criteria to evaluate the effectiveness of our tissue-engineered tendon repairs. PMID:24200342

  1. Functional tissue engineering of tendon: Establishing biological success criteria for improving tendon repair.

    PubMed

    Breidenbach, Andrew P; Gilday, Steven D; Lalley, Andrea L; Dyment, Nathaniel A; Gooch, Cynthia; Shearn, Jason T; Butler, David L

    2014-06-27

    Improving tendon repair using Functional Tissue Engineering (FTE) principles has been the focus of our laboratory over the last decade. Although our primary goals were initially focused only on mechanical outcomes, we are now carefully assessing the biological properties of our tissue-engineered tendon repairs so as to link biological influences with mechanics. However, given the complexities of tendon development and healing, it remains challenging to determine which aspects of tendon biology are the most important to focus on in the context of tissue engineering. To address this problem, we have formalized a strategy to identify, prioritize, and evaluate potential biological success criteria for tendon repair. We have defined numerous biological properties of normal tendon relative to cellular phenotype, extracellular matrix and tissue ultra-structure that we would like to reproduce in our tissue-engineered repairs and prioritized these biological criteria by examining their relative importance during both normal development and natural tendon healing. Here, we propose three specific biological criteria which we believe are essential for normal tendon function: (1) scleraxis-expressing cells; (2) well-organized and axially-aligned collagen fibrils having bimodal diameter distribution; and (3) a specialized tendon-to-bone insertion site. Moving forward, these biological success criteria will be used in conjunction with our already established mechanical success criteria to evaluate the effectiveness of our tissue-engineered tendon repairs. PMID:24200342

  2. Computation of Multimodal Size-Velocity-Temperature Spray Distribution Functions

    NASA Astrophysics Data System (ADS)

    Archambault, Mark R.

    2002-09-01

    An alternative approach to modeling spray flows-one which does not involve simulation or stochastic integration is to directly compute the evolution of the probability density function (PDF) describing the drops. The purpose of this paper is to continue exploring an alternative method of solving the spray flow problem. The approach is to derive and solve a set of Eulerian moment transport equations for the quantities of interest in the spray, coupled with the appropriate gas-phase (Eulerian) equations. A second purpose is to continue to explore how a maximum-entropy criterion may be used to provide closure for such a moment-based model. The hope is to further develop an Eulerian-Eulerian model that will permit one to solve for detailed droplet statistics directly without the use of stochastic integration or post-averaging of simulations.

  3. Imaging local brain function with emission computed tomography

    SciTech Connect

    Kuhl, D.E.

    1984-03-01

    Positron emission tomography (PET) using /sup 18/F-fluorodeoxyglucose (FDG) was used to map local cerebral glucose utilization in the study of local cerebral function. This information differs fundamentally from structural assessment by means of computed tomography (CT). In normal human volunteers, the FDG scan was used to determine the cerebral metabolic response to conrolled sensory stimulation and the effects of aging. Cerebral metabolic patterns are distinctive among depressed and demented elderly patients. The FDG scan appears normal in the depressed patient, studded with multiple metabolic defects in patients with multiple infarct dementia, and in the patients with Alzheimer disease, metabolism is particularly reduced in the parietal cortex, but only slightly reduced in the caudate and thalamus. The interictal FDG scan effectively detects hypometabolic brain zones that are sites of onset for seizures in patients with partial epilepsy, even though these zones usually appear normal on CT scans. The future prospects of PET are discussed.

  4. Computational Effective Fault Detection by Means of Signature Functions

    PubMed Central

    Baranski, Przemyslaw; Pietrzak, Piotr

    2016-01-01

    The paper presents a computationally effective method for fault detection. A system’s responses are measured under healthy and ill conditions. These signals are used to calculate so-called signature functions that create a signal space. The current system’s response is projected into this space. The signal location in this space easily allows to determine the fault. No classifier such as a neural network, hidden Markov models, etc. is required. The advantage of this proposed method is its efficiency, as computing projections amount to calculating dot products. Therefore, this method is suitable for real-time embedded systems due to its simplicity and undemanding processing capabilities which permit the use of low-cost hardware and allow rapid implementation. The approach performs well for systems that can be considered linear and stationary. The communication presents an application, whereby an industrial process of moulding is supervised. The machine is composed of forms (dies) whose alignment must be precisely set and maintained during the work. Typically, the process is stopped periodically to manually control the alignment. The applied algorithm allows on-line monitoring of the device by analysing the acceleration signal from a sensor mounted on a die. This enables to detect failures at an early stage thus prolonging the machine’s life. PMID:26949942

  5. Computational Effective Fault Detection by Means of Signature Functions.

    PubMed

    Baranski, Przemyslaw; Pietrzak, Piotr

    2016-01-01

    The paper presents a computationally effective method for fault detection. A system's responses are measured under healthy and ill conditions. These signals are used to calculate so-called signature functions that create a signal space. The current system's response is projected into this space. The signal location in this space easily allows to determine the fault. No classifier such as a neural network, hidden Markov models, etc. is required. The advantage of this proposed method is its efficiency, as computing projections amount to calculating dot products. Therefore, this method is suitable for real-time embedded systems due to its simplicity and undemanding processing capabilities which permit the use of low-cost hardware and allow rapid implementation. The approach performs well for systems that can be considered linear and stationary. The communication presents an application, whereby an industrial process of moulding is supervised. The machine is composed of forms (dies) whose alignment must be precisely set and maintained during the work. Typically, the process is stopped periodically to manually control the alignment. The applied algorithm allows on-line monitoring of the device by analysing the acceleration signal from a sensor mounted on a die. This enables to detect failures at an early stage thus prolonging the machine's life. PMID:26949942

  6. Biological Functions of the Genes in the Mammaprint Breast Cancer Profile Reflect the Hallmarks of Cancer

    PubMed Central

    Tian, Sun; Roepman, Paul; van’t Veer, Laura J; Bernards, Rene; de Snoo, Femke; Glas, Annuska M

    2010-01-01

    Background: MammaPrint was developed as a diagnostic tool to predict risk of breast cancer metastasis using the expression of 70 genes. To better understand the tumor biology assessed by MammaPrint, we interpreted the biological functions of the 70-genes and showed how the genes reflect the six hallmarks of cancer as defined by Hanahan and Weinberg. Results: We used a bottom-up system biology approach to elucidate how the cellular processes reflected by the 70-genes work together to regulate tumor activities and progression. The biological functions of the genes were analyzed using literature research and several bioinformatics tools. Protein-protein interaction network analyses indicated that the 70-genes form highly interconnected networks and that their expression levels are regulated by key tumorigenesis related genes such as TP53, RB1, MYC, JUN and CDKN2A. The biological functions of the genes could be associated with the essential steps necessary for tumor progression and metastasis, and cover the six well-defined hallmarks of cancer, reflecting the acquired malignant characteristics of a cancer cell along with tumor progression and metastasis-related biological activities. Conclusion: Genes in the MammaPrint gene signature comprehensively measure the six hallmarks of cancer-related biology. This finding establishes a link between a molecular signature and the underlying molecular mechanisms of tumor cell progression and metastasis. PMID:21151591

  7. Selenium and arsenic in biology: their chemical forms and biological functions.

    PubMed

    Shibata, Y; Morita, M; Fuwa, K

    1992-01-01

    Based on the recent development of analytical methods, sensitive systems for the analysis and speciation of selenium and arsenic have been established. A palladium addition technique was developed for the accurate determination of selenium in biological samples using graphite furnace atomic absorption analysis. For the speciation of the elements, combined methods of HPLC either with ICP-AES or with ICP-MS were found to work well. These systems were applied to the elucidation of the chemical form of the elements in natural samples. Some chemical properties of the selenium-mercury complex in dolphin liver were elucidated: i.e., it was a cationic, water-soluble, low molecular weight compound containing selenium and mercury in a 1:1 molar ratio, and was shown to be different from a known selenium-mercury complex, bis(methylmercuric)selenide. The major selenium compound excreted in human urine was revealed to be other than any of those previously identified (TMSe, selenate, and selenite). TMSe, a suspected major metabolite in urine, was found, if at all, in low levels. The major water-soluble, and lipid-soluble arsenic compounds in a brown seaweed, U. pinnatifida (WAKAME), were rigorously identified, and the results were compared with other data on marine algae and animals. The major organic arsenic compounds (termed "arseno-sugars") in marine algae commonly contain 5-deoxy-5-dimethylarsinyl-ribofuranoside moiety. There are various kinds of arseno-sugar derivatives containing different side-chains attached to the anomeric position of the sugar, and the distribution of each arsenic species seems to be related to algal species. The arseno-sugar (A-XI) is present in every alga so far examined, is metabolized to lipids, and possibly may play some specific role in the algal cells. On the other hand, the major arsenic compound in fish, crustacea and molluscs has been identified as arsenobetaine, which is an arseno-analog of glycinebetaine, a very common osmo-regulator in

  8. Assessing executive function using a computer game: computational modeling of cognitive processes.

    PubMed

    Hagler, Stuart; Jimison, Holly Brugge; Pavel, Misha

    2014-07-01

    Early and reliable detection of cognitive decline is one of the most important challenges of current healthcare. In this project, we developed an approach whereby a frequently played computer game can be used to assess a variety of cognitive processes and estimate the results of the pen-and-paper trail making test (TMT)--known to measure executive function, as well as visual pattern recognition, speed of processing, working memory, and set-switching ability. We developed a computational model of the TMT based on a decomposition of the test into several independent processes, each characterized by a set of parameters that can be estimated from play of a computer game designed to resemble the TMT. An empirical evaluation of the model suggests that it is possible to use the game data to estimate the parameters of the underlying cognitive processes and using the values of the parameters to estimate the TMT performance. Cognitive measures and trends in these measures can be used to identify individuals for further assessment, to provide a mechanism for improving the early detection of neurological problems, and to provide feedback and monitoring for cognitive interventions in the home. PMID:25014944

  9. Towards understanding the biological function of hopanoids (Invited)

    NASA Astrophysics Data System (ADS)

    Doughty, D. M.; Hunter, R.; Summons, R. E.; Newman, D. K.

    2010-12-01

    Rhodopseudomonas palustris TIE-1 expresses bacterial hopanoid lipids that are structurally similar and evolutionarily related to eukaryotic sterols. The genome of R. palustris TIE-1 contains two copies of the hpnN gene (hpnN1 and hpnN2) that are orthologs of genes encoding eukaryotic sterol and lipid transporters. Hopanoid localization to the outer membrane was found to be dependent upon hpnN1. Since the cell cycle of R. palustris TIE-1 is obligately bimodal with each cell division resulting in the generation of one mother and one swarmer cell, evidence was obtained that hopanoids where specifically localized to the outer membrane of mother cells. The sequestration of hopanoids to the mother cells was also disrupted by the deletion of the hpnN1 gene. Mutants lacking the hopanoid transporters were able to grow normally at 30 °C but showed decreased growth at 38 °C. The hopanoid transporter mutant formed cellular filaments when grown at elevated temperature. Because sedimentary steranes and hopanes comprise some of the earliest evidence for the emergence of distinct bacteria and eukaryotic phyla, a better appreciation of the function of hopanoids will improve our ability to interpret the evolution of life on Earth.

  10. Matrix metalloproteinases: their biological functions and clinical implications.

    PubMed

    Hijova, E

    2005-01-01

    Matrix metalloproteinases (MMPs), which are also known as matrixins, are proteinases that participate in extracellular matrix remodelling and degradation. Under normal physiological conditions, the activities of MMPs are precisely regulated at the level of transcription, at that of activation of the pro-MMP precursor zymogenes as well as at that of inhibition by endogenous inhibitors (tissue inhibitors of metalloproteinases, TIMPs). Alterations in the regulation of MMP activity are implicated in diseases such as cancer, fibrosis, arthritis and atherosclerosis. The pathological effects of MMPs and TIMPs in cardiovascular diseases involve vascular remodelling, atherosclerotic plaque instability and cardiac remodelling in congestive heart failure or after myocardial infarction. Since excessive tissue remodelling and increased matrix metalloproteinases activity have been demonstrated during atherosclerotic lesion progression (including plaque disruption), MMPs represent a potential target for therapeutic intervention aimed at the modification of vascular pathology by restoring the physiological balance between MMPs and TIMPs. Recent findings suggest that MMPs are also involved in cancer initiation, invasion and metastasis; MMP inhibitors could be considered for evaluation as cancer chemopreventive molecules. This review describes the members of MMP and TIMP families and discusses the structure, function and regulation of MMP activity. (Tab. 1, Ref: 45.) PMID:16026148

  11. Small regulatory RNAs in Streptococcus pneumoniae: discovery and biological functions

    PubMed Central

    Wilton, Joana; Acebo, Paloma; Herranz, Cristina; Gómez, Alicia; Amblar, Mónica

    2015-01-01

    Streptococcus pneumoniae is a prominent human pathogen responsible for many severe diseases and the leading cause of childhood mortality worldwide. The pneumococcus is remarkably adept at colonizing and infecting different niches in the human body, and its adaptation to dynamic host environment is a central aspect of its pathogenesis. In the last decade, increasing findings have evidenced small RNAs (sRNAs) as vital regulators in a number of important processes in bacteria. In S. pneumoniae, a small antisense RNA was first discovered in the pMV158 plasmid as a copy number regulator. More recently, genome-wide screens revealed that the pneumococcal genome also encodes multiple sRNAs, many of which have important roles in virulence while some are implicated in competence control. The knowledge of the sRNA-mediated regulation in pneumococcus remains very limited, and future research is needed for better understanding of functions and mechanisms. Here, we provide a comprehensive summary of the current knowledge on sRNAs from S. pneumoniae, focusing mainly on the trans-encoded sRNAs. PMID:25904932

  12. Production and biological function of volatile esters in Saccharomyces cerevisiae

    PubMed Central

    Saerens, Sofie M. G.; Delvaux, Freddy R.; Verstrepen, Kevin J.; Thevelein, Johan M.

    2010-01-01

    Summary The need to understand and control ester synthesis is driven by the fact that esters play a key role in the sensorial quality of fermented alcoholic beverages like beer, wine and sake. As esters are synthesized in yeast via several complex metabolic pathways, there is a need to gain a clear understanding of ester metabolism and its regulation. The individual genes involved, their functions and regulatory mechanisms have to be identified. In alcoholic beverages, there are two important groups of esters: the acetate esters and the medium‐chain fatty acid (MCFA) ethyl esters. For acetate ester synthesis, the genes involved have already been cloned and characterized. Also the biochemical pathways and the regulation of acetate ester synthesis are well defined. With respect to the molecular basis of MCFA ethyl ester synthesis, however, significant progress has only recently been made. Next to the characterization of the biochemical pathways and regulation of ester synthesis, a new and more important question arises: what is the advantage for yeast to produce these esters? Several hypotheses have been proposed in the past, but none was satisfactorily. This paper reviews the current hypotheses of ester synthesis in yeast in relation to the complex regulation of the alcohol acetyl transferases and the different factors that allow ester formation to be controlled during fermentation. PMID:21255318

  13. Chemical Visualization of Boolean Functions: A Simple Chemical Computer

    NASA Astrophysics Data System (ADS)

    Blittersdorf, R.; Müller, J.; Schneider, F. W.

    1995-08-01

    We present a chemical realization of the Boolean functions AND, OR, NAND, and NOR with a neutralization reaction carried out in three coupled continuous flow stirred tank reactors (CSTR). Two of these CSTR's are used as input reactors, the third reactor marks the output. The chemical reaction is the neutralization of hydrochloric acid (HCl) with sodium hydroxide (NaOH) in the presence of phenolphtalein as an indicator, which is red in alkaline solutions and colorless in acidic solutions representing the two binary states 1 and 0, respectively. The time required for a "chemical computation" is determined by the flow rate of reactant solutions into the reactors since the neutralization reaction itself is very fast. While the acid flow to all reactors is equal and constant, the flow rate of NaOH solution controls the states of the input reactors. The connectivities between the input and output reactors determine the flow rate of NaOH solution into the output reactor, according to the chosen Boolean function. Thus the state of the output reactor depends on the states of the input reactors.

  14. Computing black hole partition functions from quasinormal modes

    NASA Astrophysics Data System (ADS)

    Arnold, Peter; Szepietowski, Phillip; Vaman, Diana

    2016-07-01

    We propose a method of computing one-loop determinants in black hole space-times (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A numerical evaluation must face the fact that the sum over the quasinormal modes, indexed by momentum and overtone numbers, is divergent. A necessary ingredient is then a regularization scheme to handle the divergent contributions of individual fixed-momentum sectors to the partition function. To this end, we formulate an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. We then discuss the application of such techniques to more complicated spacetimes.

  15. Chaste: An Open Source C++ Library for Computational Physiology and Biology

    PubMed Central

    Mirams, Gary R.; Arthurs, Christopher J.; Bernabeu, Miguel O.; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G.; Harvey, Daniel G.; Marsh, Megan E.; Osborne, James M.; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J.

    2013-01-01

    Chaste — Cancer, Heart And Soft Tissue Environment — is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to ‘re-invent the wheel’ with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials. PMID:23516352

  16. Chaste: an open source C++ library for computational physiology and biology.

    PubMed

    Mirams, Gary R; Arthurs, Christopher J; Bernabeu, Miguel O; Bordas, Rafel; Cooper, Jonathan; Corrias, Alberto; Davit, Yohan; Dunn, Sara-Jane; Fletcher, Alexander G; Harvey, Daniel G; Marsh, Megan E; Osborne, James M; Pathmanathan, Pras; Pitt-Francis, Joe; Southern, James; Zemzemi, Nejib; Gavaghan, David J

    2013-01-01

    Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high-performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to 're-invent the wheel' with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials. PMID:23516352

  17. Schematic and realistic biological motion identification in children with high-functioning autism spectrum disorder

    PubMed Central

    Wright, Kristyn; Kelley, Elizabeth; Poulin-Dubois, Diane

    2014-01-01

    Research investigating biological motion perception in children with ASD has revealed conflicting findings concerning whether impairments in biological motion perception exist. The current study investigated how children with high-functioning ASD (HF-ASD) performed on two tasks of biological motion identification: a novel schematic motion identification task and a point-light biological motion identification task. Twenty-two HFASD children were matched with 21 TD children on gender, non-verbal mental, and chronological, age (M years = 6.72). On both tasks, HF-ASD children performed with similar accuracy as TD children. Across groups, children performed better on animate than on inanimate trials of both tasks. These findings suggest that HF-ASD children's identification of both realistic and schematic biological motion identification is unimpaired. PMID:25395988

  18. Schematic and realistic biological motion identification in children with high-functioning autism spectrum disorder.

    PubMed

    Wright, Kristyn; Kelley, Elizabeth; Poulin-Dubois, Diane

    2014-10-01

    Research investigating biological motion perception in children with ASD has revealed conflicting findings concerning whether impairments in biological motion perception exist. The current study investigated how children with high-functioning ASD (HF-ASD) performed on two tasks of biological motion identification: a novel schematic motion identification task and a point-light biological motion identification task. Twenty-two HFASD children were matched with 21 TD children on gender, non-verbal mental, and chronological, age (M years = 6.72). On both tasks, HF-ASD children performed with similar accuracy as TD children. Across groups, children performed better on animate than on inanimate trials of both tasks. These findings suggest that HF-ASD children's identification of both realistic and schematic biological motion identification is unimpaired. PMID:25395988

  19. Sharing Structure and Function in Biological Design with SBOL 2.0.

    PubMed

    Roehner, Nicholas; Beal, Jacob; Clancy, Kevin; Bartley, Bryan; Misirli, Goksel; Grünberg, Raik; Oberortner, Ernst; Pocock, Matthew; Bissell, Michael; Madsen, Curtis; Nguyen, Tramy; Zhang, Michael; Zhang, Zhen; Zundel, Zach; Densmore, Douglas; Gennari, John H; Wipat, Anil; Sauro, Herbert M; Myers, Chris J

    2016-06-17

    The Synthetic Biology Open Language (SBOL) is a standard that enables collaborative engineering of biological systems across different institutions and tools. SBOL is developed through careful consideration of recent synthetic biology trends, real use cases, and consensus among leading researchers in the field and members of commercial biotechnology enterprises. We demonstrate and discuss how a set of SBOL-enabled software tools can form an integrated, cross-organizational workflow to recapitulate the design of one of the largest published genetic circuits to date, a 4-input AND sensor. This design encompasses the structural components of the system, such as its DNA, RNA, small molecules, and proteins, as well as the interactions between these components that determine the system's behavior/function. The demonstrated workflow and resulting circuit design illustrate the utility of SBOL 2.0 in automating the exchange of structural and functional specifications for genetic parts, devices, and the biological systems in which they operate. PMID:27111421

  20. Evolutionary cell biology: functional insight from “endless forms most beautiful”

    PubMed Central

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

    2015-01-01

    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

  1. End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

    DOE PAGESBeta

    Linshiz, Gregory; Jensen, Erik; Stawski, Nina; Bi, Changhao; Elsbree, Nick; Jiao, Hong; Kim, Jungkyu; Mathies, Richard; Keasling, Jay D.; Hillson, Nathan J.

    2016-02-02

    Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

  2. Motion as a source of environmental information: a fresh view on biological motion computation by insect brains

    PubMed Central

    Egelhaaf, Martin; Kern, Roland; Lindemann, Jens Peter

    2014-01-01

    Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around (“optic flow”) to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and—in many behavioral contexts—less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism. PMID:25389392

  3. InteractoMIX: a suite of computational tools to exploit interactomes in biological and clinical research.

    PubMed

    Poglayen, Daniel; Marín-López, Manuel Alejandro; Bonet, Jaume; Fornes, Oriol; Garcia-Garcia, Javier; Planas-Iglesias, Joan; Segura, Joan; Oliva, Baldo; Fernandez-Fuentes, Narcis

    2016-06-15

    Virtually all the biological processes that occur inside or outside cells are mediated by protein-protein interactions (PPIs). Hence, the charting and description of the PPI network, initially in organisms, the interactome, but more recently in specific tissues, is essential to fully understand cellular processes both in health and disease. The study of PPIs is also at the heart of renewed efforts in the medical and biotechnological arena in the quest of new therapeutic targets and drugs. Here, we present a mini review of 11 computational tools and resources tools developed by us to address different aspects of PPIs: from interactome level to their atomic 3D structural details. We provided details on each specific resource, aims and purpose and compare with equivalent tools in the literature. All the tools are presented in a centralized, one-stop, web site: InteractoMIX (http://interactomix.com). PMID:27284060

  4. Perceptron-like computation based on biologically-inspired neurons with heterosynaptic mechanisms

    NASA Astrophysics Data System (ADS)

    Kaluza, Pablo; Urdapilleta, Eugenio

    2014-10-01

    Perceptrons are one of the fundamental paradigms in artificial neural networks and a key processing scheme in supervised classification tasks. However, the algorithm they provide is given in terms of unrealistically simple processing units and connections and therefore, its implementation in real neural networks is hard to be fulfilled. In this work, we present a neural circuit able to perform perceptron's computation based on realistic models of neurons and synapses. The model uses Wang-Buzsáki neurons with coupling provided by axodendritic and axoaxonic synapses (heterosynapsis). The main characteristics of the feedforward perceptron operation are conserved, which allows to combine both approaches: whereas the classical artificial system can be used to learn a particular problem, its solution can be directly implemented in this neural circuit. As a result, we propose a biologically-inspired system able to work appropriately in a wide range of frequencies and system parameters, while keeping robust to noise and error.

  5. Scalable Computational Methods for the Analysis of High-Throughput Biological Data

    SciTech Connect

    Langston, Michael A

    2012-09-06

    This primary focus of this research project is elucidating genetic regulatory mechanisms that control an organism's responses to low-dose ionizing radiation. Although low doses (at most ten centigrays) are not lethal to humans, they elicit a highly complex physiological response, with the ultimate outcome in terms of risk to human health unknown. The tools of molecular biology and computational science will be harnessed to study coordinated changes in gene expression that orchestrate the mechanisms a cell uses to manage the radiation stimulus. High performance implementations of novel algorithms that exploit the principles of fixed-parameter tractability will be used to extract gene sets suggestive of co-regulation. Genomic mining will be performed to scrutinize, winnow and highlight the most promising gene sets for more detailed investigation. The overall goal is to increase our understanding of the health risks associated with exposures to low levels of radiation.

  6. Physical and Computational Modeling for Chemical and Biological Weapons Airflow Applications

    SciTech Connect

    McEligot, Donald Marinus; Mc Creery, Glenn Ernest; Pink, Robert John; Barringer, C.; Knight, K. J.

    2002-11-01

    There is a need for information on dispersion and infiltration of chemical and biological agents in complex building environments. A recent collaborative study conducted at the Idaho National Engineering and Environmental Laboratory (INEEL) and Bechtel Corporation Research and Development had the objective of assessing computational fluid dynamics (CFD) models for simulation of flow around complicated buildings through a comparison of experimental and numerical results. The test facility used in the experiments was INEEL’s unique large Matched-Index-of-Refraction (MIR) flow system. The CFD code used for modeling was Fluent, a widely available commercial flow simulation package. For the experiment, a building plan was selected to approximately represent an existing facility. It was found that predicted velocity profiles from above the building and in front of the building were in good agreement with the measurements.

  7. [Study on action mechanism of Danhong injection based on computational system biology approach].

    PubMed

    Lv, Yan-ni; Wei, Xiao-hua; Xiao, Pin

    2015-02-01

    Danhong injection is a compound preparation of traditional Chinese medicine Salvia miltiorrhiza and Carthamus tinctorius, and has been widely applied in treating coronary heart diseases and ischemic encephalopathy in clinic. Despite the complexity of its chemical compounds and the diversity of targets, especially in system biology, there have not a report for its action mechanism as a whole regulatory biological network. In this study, protein data of S. miltiorrhiza and C. tinctorius were searched in TCMGeneDIT database and agilent literature search (ALS) system to establish the multi-component protein network of S. miltiorrhiza, C. tinctorius and Danhong injection. Besides, the protein interaction network was built based on the protein-protein interaction in Genecards, BIND, BioGRID, IntAct, MINT and other databases. According to the findings, 10 compounds of S. miltiorrhiza and 14 compounds of C. tinctorius were correlated with proteins. The 24 common compounds had interactions with 81 proteins, and formed a protein interaction network with 60 none-isolated nodes. The Cluster ONE module was applied to make an enrichment analysis on the protein interaction network and extract one sub-network with significant difference P <0.05. The sub-network contains 23 key proteins, which involved five signaling pathways, namely Nod-like receptor signaling pathway, epithelial cell signaling in helicobacter pylori infection, Toll-like receptor signaling pathway, RIG-I-like receptor signaling pathway and neurotrophin signaling pathway through KEGG signaling pathway mapping. In this study, the computational system biology approach was adopted to preliminarily explain the molecular mechanism of main compounds of Danhong injection in preventing and treating diseases and provide reference for systematic studies on traditional Chinese medicine compounds. PMID:26084184

  8. Tools for building a comprehensive modeling system for virtual screening under real biological conditions: The Computational Titration algorithm.

    PubMed

    Kellogg, Glen E; Fornabaio, Micaela; Chen, Deliang L; Abraham, Donald J; Spyrakis, Francesca; Cozzini, Pietro; Mozzarelli, Andrea

    2006-05-01

    Computational tools utilizing a unique empirical modeling system based on the hydrophobic effect and the measurement of logP(o/w) (the partition coefficient for solvent transfer between 1-octanol and water) are described. The associated force field, Hydropathic INTeractions (HINT), contains much rich information about non-covalent interactions in the biological environment because of its basis in an experiment that measures interactions in solution. HINT is shown to be the core of an evolving virtual screening system that is capable of taking into account a number of factors often ignored such as entropy, effects of solvent molecules at the active site, and the ionization states of acidic and basic residues and ligand functional groups. The outline of a comprehensive modeling system for virtual screening that incorporates these features is described. In addition, a detailed description of the Computational Titration algorithm is provided. As an example, three complexes of dihydrofolate reductase (DHFR) are analyzed with our system and these results are compared with the experimental free energies of binding. PMID:16236534

  9. Three-dimensional visualisation of soft biological structures by X-ray computed micro-tomography.

    PubMed

    Shearer, Tom; Bradley, Robert S; Hidalgo-Bastida, L Araida; Sherratt, Michael J; Cartmell, Sarah H

    2016-07-01

    Whereas the two-dimensional (2D) visualisation of biological samples is routine, three-dimensional (3D) imaging remains a time-consuming and relatively specialised pursuit. Current commonly adopted techniques for characterising the 3D structure of non-calcified tissues and biomaterials include optical and electron microscopy of serial sections and sectioned block faces, and the visualisation of intact samples by confocal microscopy or electron tomography. As an alternative to these approaches, X-ray computed micro-tomography (microCT) can both rapidly image the internal 3D structure of macroscopic volumes at sub-micron resolutions and visualise dynamic changes in living tissues at a microsecond scale. In this Commentary, we discuss the history and current capabilities of microCT. To that end, we present four case studies to illustrate the ability of microCT to visualise and quantify: (1) pressure-induced changes in the internal structure of unstained rat arteries, (2) the differential morphology of stained collagen fascicles in tendon and ligament, (3) the development of Vanessa cardui chrysalises, and (4) the distribution of cells within a tissue-engineering construct. Future developments in detector design and the use of synchrotron X-ray sources might enable real-time 3D imaging of dynamically remodelling biological samples. PMID:27278017

  10. Hidden Markov models and other machine learning approaches in computational molecular biology

    SciTech Connect

    Baldi, P.

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In this tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.

  11. Systems biology in psychiatric research: from complex data sets over wiring diagrams to computer simulations.

    PubMed

    Tretter, Felix; Gebicke-Haerter, Peter J

    2012-01-01

    The classification of psychiatric disorders has always been a problem in clinical settings. The present debate about the major systems in clinical practice, DSM-IV and ICD-10, has resulted in attempts to improve and replace those schemes by some that include more endophenotypic and molecular features. However, these disorders not only require more precise diagnostic tools, but also have to be viewed more extensively in their dynamic behaviors, which require more precise data sets related to their origins and developments. This enormous challenge in brain research has to be approached on different levels of the biological system by new methods, including improvements in electroencephalography, brain imaging, and molecular biology. All these methods entail accumulations of large data sets that become more and more difficult to interpret. In particular, on the molecular level, there is an apparent need to use highly sophisticated computer programs to tackle these problems. Evidently, only interdisciplinary work among mathematicians, physicists, biologists, and clinicians can further improve our understanding of complex diseases of the brain. PMID:22231839

  12. Graphene for multi-functional synthetic biology: the last 'zeitgeist' in nanomedicine.

    PubMed

    Servant, A; Bianco, A; Prato, M; Kostarelos, K

    2014-04-01

    The high versatility of graphene has attracted significant attention in many areas of scientific research from electronics to physics and mechanics. One of the most intriguing utilisation of graphene remains however in nanomedicine and synthetic biology. In particular, the last decade has witnessed an exponential growth in the generation of novel candidate therapeutics of multiple biological activities based on graphene constructs with small molecules, such as anti-cancer drugs. In this Digest, we summarise the different synthetic strategies and routes available to fabricate these promising graphene conjugates and the opportunities for the design of multi-functional tools for synthetic biology that they offer. PMID:24594351

  13. From video to computation of biological fluid-structure interaction problems

    NASA Astrophysics Data System (ADS)

    Dillard, Seth I.; Buchholz, James H. J.; Udaykumar, H. S.

    2016-04-01

    This work deals with the techniques necessary to obtain a purely Eulerian procedure to conduct CFD simulations of biological systems with moving boundary flow phenomena. Eulerian approaches obviate difficulties associated with mesh generation to describe or fit flow meshes to body surfaces. The challenges associated with constructing embedded boundary information, body motions and applying boundary conditions on the moving bodies for flow computation are addressed in the work. The overall approach is applied to the study of a fluid-structure interaction problem, i.e., the hydrodynamics of swimming of an American eel, where the motion of the eel is derived from video imaging. It is shown that some first-blush approaches do not work, and therefore, careful consideration of appropriate techniques to connect moving images to flow simulations is necessary and forms the main contribution of the paper. A combination of level set-based active contour segmentation with optical flow and image morphing is shown to enable the image-to-computation process.

  14. High performance computing approaches for 3D reconstruction of complex biological specimens.

    PubMed

    da Silva, M Laura; Roca-Piera, Javier; Fernández, José-Jesús

    2010-01-01

    Knowledge of the structure of specimens is crucial to determine the role that they play in cellular and molecular biology. To yield the three-dimensional (3D) reconstruction by means of tomographic reconstruction algorithms, we need the use of large projection images and high processing time. Therefore, we propose the use of the high performance computing (HPC) to cope with the huge computational demands of this problem. We have implemented a HPC strategy where the distribution of tasks follows the master-slave paradigm. The master processor distributes a slab of slices, a piece of the final 3D structure to reconstruct, among the slave processors and receives reconstructed slices of the volume. We have evaluated the performance of our HPC approach using different sizes of the slab. We have observed that it is possible to find out an optimal size of the slab for the number of processor used that minimize communications time while maintaining a reasonable grain of parallelism to be exploited by the set of processors. PMID:20865517

  15. Electromagnetic fields as structure-function zeitgebers in biological systems: environmental orchestrations of morphogenesis and consciousness

    PubMed Central

    Rouleau, Nicolas; Dotta, Blake T.

    2014-01-01

    Within a cell system structure dictates function. Any interaction between cells, or a cell and its environment, has the potential to have long term implications on the function of a given cell and emerging cell aggregates. The structure and function of cells are continuously subjected to modification by electrical and chemical stimuli. However, biological systems are also subjected to an ever-present influence: the electromagnetic (EM) environment. Biological systems have the potential to be influenced by subtle energies which are exchanged at atomic and subatomic scales as EM phenomena. These energy exchanges have the potential to manifest at higher orders of discourse and affect the output (behavior) of a biological system. Here we describe theoretical and experimental evidence of EM influence on cells and the integration of whole systems. Even weak interactions between EM energies and biological systems display the potential to affect a developing system. We suggest the growing literature of EM effects on biological systems has significant implications to the cell and its functional aggregates. PMID:25426035

  16. An interdisciplinary approach to study individuality in biological and physical systems functioning

    NASA Astrophysics Data System (ADS)

    Mygal, V. P.; But, A. V.; Mygal, G. V.; Klimenko, I. A.

    2016-07-01

    Signals of system functioning of different nature are presented in the parameter space (state-velocity-acceleration) as a trajectory of dynamic events. Such signals geometrization allows to reveal the hidden spatio-temporal correlation in dynamics of systems functioning. It is shown that the nature of relationship between the dynamic parameters of signal determines the natural cycle of sensor functioning. Its restructuring displays the inherited features of systems functioning in signature package. The universal differential-geometry parameters and new integrative indexes of system functioning are used to analyze the signatures of biological and physical signals.

  17. An interdisciplinary approach to study individuality in biological and physical systems functioning.

    PubMed

    Mygal, V P; But, A V; Mygal, G V; Klimenko, I A

    2016-01-01

    Signals of system functioning of different nature are presented in the parameter space (state-velocity-acceleration) as a trajectory of dynamic events. Such signals geometrization allows to reveal the hidden spatio-temporal correlation in dynamics of systems functioning. It is shown that the nature of relationship between the dynamic parameters of signal determines the natural cycle of sensor functioning. Its restructuring displays the inherited features of systems functioning in signature package. The universal differential-geometry parameters and new integrative indexes of system functioning are used to analyze the signatures of biological and physical signals. PMID:27412253

  18. An interdisciplinary approach to study individuality in biological and physical systems functioning

    PubMed Central

    Mygal, V. P.; But, A. V.; Mygal, G. V.; Klimenko, I. A.

    2016-01-01

    Signals of system functioning of different nature are presented in the parameter space (state-velocity-acceleration) as a trajectory of dynamic events. Such signals geometrization allows to reveal the hidden spatio-temporal correlation in dynamics of systems functioning. It is shown that the nature of relationship between the dynamic parameters of signal determines the natural cycle of sensor functioning. Its restructuring displays the inherited features of systems functioning in signature package. The universal differential-geometry parameters and new integrative indexes of system functioning are used to analyze the signatures of biological and physical signals. PMID:27412253

  19. Computational genomic identification and functional reconstitution of plant natural product biosynthetic pathways.

    PubMed

    Medema, Marnix H; Osbourn, Anne

    2016-08-27

    Covering: 2003 to 2016The last decade has seen the first major discoveries regarding the genomic basis of plant natural product biosynthetic pathways. Four key computationally driven strategies have been developed to identify such pathways, which make use of physical clustering, co-expression, evolutionary co-occurrence and epigenomic co-regulation of the genes involved in producing a plant natural product. Here, we discuss how these approaches can be used for the discovery of plant biosynthetic pathways encoded by both chromosomally clustered and non-clustered genes. Additionally, we will discuss opportunities to prioritize plant gene clusters for experimental characterization, and end with a forward-looking perspective on how synthetic biology technologies will allow effective functional reconstitution of candidate pathways using a variety of genetic systems. PMID:27321668

  20. Computational Studies of Membrane Proteins: Models and Predictions for Biological Understanding

    PubMed Central

    Liang, Jie; Naveed, Hammad; Jimenez-Morales, David; Adamian, Larisa; Lin, Meishan

    2013-01-01

    We discuss recent progresses in computational studies of membrane proteins based on physical models with parameters derived from bioinformatics analysis. We describe computational identification of membrane proteins and prediction of their topology from sequence, discovery of sequence and spatial motifs, and implications of these discoveries. The detection of evolutionary signal for understanding the substitution pattern of residues in the TM segments and for sequence alignment are also discussed. We further discuss empirical potential functions for energetics of inserting residues in the TM domain, for interactions between TM helices or strands, and their applications in predicting lipid-facing surfaces of the TM domain. Recent progresses in structure predictions of membrane proteins are also reviewed, with further discussions on calculation of ensemble properties such as melting temperature based on simplified state space model. Additional topics include prediction of oligomerization state of membrane proteins, identification of the interfaces for protein-protein interactions, and design of membrane proteins. PMID:22051023