WorldWideScience

Sample records for computational biology

  1. Computational biology

    DEFF Research Database (Denmark)

    Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

    2011-01-01

    Computation via biological devices has been the subject of close scrutiny since von Neumann’s early work some 60 years ago. In spite of the many relevant works in this field, the notion of programming biological devices seems to be, at best, ill-defined. While many devices are claimed or proved t...

  2. Computational biology for ageing

    Science.gov (United States)

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

    2011-01-01

    High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions. PMID:21115530

  3. Michael Levitt and Computational Biology

    Science.gov (United States)

    dropdown arrow Site Map A-Z Index Menu Synopsis Michael Levitt and Computational Biology Resources with Michael Levitt, PhD, professor of structural biology at the Stanford University School of Medicine, has function. ... Levitt's early work pioneered computational structural biology, which helped to predict

  4. Computational Systems Chemical Biology

    OpenAIRE

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

    2011-01-01

    There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007).

  5. Computational aspects of systematic biology.

    Science.gov (United States)

    Lilburn, Timothy G; Harrison, Scott H; Cole, James R; Garrity, George M

    2006-06-01

    We review the resources available to systematic biologists who wish to use computers to build classifications. Algorithm development is in an early stage, and only a few examples of integrated applications for systematic biology are available. The availability of data is crucial if systematic biology is to enter the computer age.

  6. Computational Biology and High Performance Computing 2000

    Energy Technology Data Exchange (ETDEWEB)

    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.

  7. Synthetic biology: engineering molecular computers

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Complicated systems cannot survive the rigors of a chaotic environment, without balancing mechanisms that sense, decide upon and counteract the exerted disturbances. Especially so with living organisms, forced by competition to incredible complexities, escalating also their self-controlling plight. Therefore, they compute. Can we harness biological mechanisms to create artificial computing systems? Biology offers several levels of design abstraction: molecular machines, cells, organisms... ranging from the more easily-defined to the more inherently complex. At the bottom of this stack we find the nucleic acids, RNA and DNA, with their digital structure and relatively precise interactions. They are central enablers of designing artificial biological systems, in the confluence of engineering and biology, that we call Synthetic biology. In the first part, let us follow their trail towards an overview of building computing machines with molecules -- and in the second part, take the case study of iGEM Greece 201...

  8. How Computers are Arming biology!

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 23; Issue 1. In-vitro to In-silico - How Computers are Arming biology! Geetha Sugumaran Sushila Rajagopal. Face to Face Volume 23 Issue 1 January 2018 pp 83-102. Fulltext. Click here to view fulltext PDF. Permanent link:

  9. Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology.

    Science.gov (United States)

    Bonham, Kevin S; Stefan, Melanie I

    2017-10-01

    While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.

  10. Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology.

    Directory of Open Access Journals (Sweden)

    Kevin S Bonham

    2017-10-01

    Full Text Available While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance.

  11. Application of computational intelligence to biology

    CERN Document Server

    Sekhar, Akula

    2016-01-01

    This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

  12. Computational structural biology: methods and applications

    National Research Council Canada - National Science Library

    Schwede, Torsten; Peitsch, Manuel Claude

    2008-01-01

    ... sequencing reinforced the observation that structural information is needed to understand the detailed function and mechanism of biological molecules such as enzyme reactions and molecular recognition events. Furthermore, structures are obviously key to the design of molecules with new or improved functions. In this context, computational structural biology...

  13. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available 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.

  14. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    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.

  15. Applicability of Computational Systems Biology in Toxicology

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning; Hadrup, Niels; Audouze, Karine Marie Laure

    2014-01-01

    be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method......Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources...... and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search...

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

    Science.gov (United States)

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

    2017-09-01

    Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

  17. Computational Tools for Stem Cell Biology.

    Science.gov (United States)

    Bian, Qin; Cahan, Patrick

    2016-12-01

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

  18. Micro-Computers in Biology Inquiry.

    Science.gov (United States)

    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)

  19. Ranked retrieval of Computational Biology models.

    Science.gov (United States)

    Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

    2010-08-11

    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. 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. 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.

  20. Computational biology and bioinformatics in Nigeria.

    Science.gov (United States)

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

    2014-04-01

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

  1. Computational biology and bioinformatics in Nigeria.

    Directory of Open Access Journals (Sweden)

    Segun A Fatumo

    2014-04-01

    Full Text Available 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.

  2. The case for biological quantum computer elements

    Science.gov (United States)

    Baer, Wolfgang; Pizzi, Rita

    2009-05-01

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

  3. Computational intelligence, medicine and biology selected links

    CERN Document Server

    Zaitseva, Elena

    2015-01-01

    This book contains an interesting and state-of the art collection of chapters presenting several examples of attempts to developing modern tools utilizing computational intelligence in different real life problems encountered by humans. Reasoning, prediction, modeling, optimization, decision making, etc. need modern, soft and intelligent algorithms, methods and methodologies to solve, in the efficient ways, problems appearing in human activity. The contents of the book is divided into two parts. Part I, consisting of four chapters, is devoted to selected links of computational intelligence, medicine, health care and biomechanics. Several problems are considered: estimation of healthcare system reliability, classification of ultrasound thyroid images, application of fuzzy logic to measure weight status and central fatness, and deriving kinematics directly from video records. Part II, also consisting of four chapters, is devoted to selected links of computational intelligence and biology. The common denominato...

  4. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar

    2016-03-21

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

  5. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

    2016-01-01

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users' intuition about model similarity, and to support complex model searches in databases.

  6. Multiobjective optimization in bioinformatics and computational biology.

    Science.gov (United States)

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

    2007-01-01

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

  7. Computing chemical organizations in biological networks.

    Science.gov (United States)

    Centler, Florian; Kaleta, Christoph; di Fenizio, Pietro Speroni; Dittrich, Peter

    2008-07-15

    Novel techniques are required to analyze computational models of intracellular processes as they increase steadily in size and complexity. The theory of chemical organizations has recently been introduced as such a technique that links the topology of biochemical reaction network models to their dynamical repertoire. The network is decomposed into algebraically closed and self-maintaining subnetworks called organizations. They form a hierarchy representing all feasible system states including all steady states. We present three algorithms to compute the hierarchy of organizations for network models provided in SBML format. Two of them compute the complete organization hierarchy, while the third one uses heuristics to obtain a subset of all organizations for large models. While the constructive approach computes the hierarchy starting from the smallest organization in a bottom-up fashion, the flux-based approach employs self-maintaining flux distributions to determine organizations. A runtime comparison on 16 different network models of natural systems showed that none of the two exhaustive algorithms is superior in all cases. Studying a 'genome-scale' network model with 762 species and 1193 reactions, we demonstrate how the organization hierarchy helps to uncover the model structure and allows to evaluate the model's quality, for example by detecting components and subsystems of the model whose maintenance is not explained by the model. All data and a Java implementation that plugs into the Systems Biology Workbench is available from http://www.minet.uni-jena.de/csb/prj/ot/tools.

  8. Computational Modeling of Biological Systems From Molecules to Pathways

    CERN Document Server

    2012-01-01

    Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

  9. Toward computational cumulative biology by combining models of biological datasets.

    Science.gov (United States)

    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.

  10. Computer Models and Automata Theory in Biology and Medicine

    CERN Document Server

    Baianu, I C

    2004-01-01

    The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

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

    Science.gov (United States)

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

    2011-10-01

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

  12. Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.

    Science.gov (United States)

    Yin, Zekun; Lan, Haidong; Tan, Guangming; Lu, Mian; Vasilakos, Athanasios V; Liu, Weiguo

    2017-01-01

    The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

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

    Science.gov (United States)

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

    2014-11-01

    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. 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. 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. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Applications of membrane computing in systems and synthetic biology

    CERN Document Server

    Gheorghe, Marian; Pérez-Jiménez, Mario

    2014-01-01

    Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying th...

  15. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-01

    -transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three

  16. UC Merced Center for Computational Biology Final Report

    Energy Technology Data Exchange (ETDEWEB)

    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

  17. Uncertainty in biology a computational modeling approach

    CERN Document Server

    Gomez-Cabrero, David

    2016-01-01

    Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies.  Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process.  This book wants to address four main issues related to the building and validation of computational models of biomedical processes: Modeling establishment under uncertainty Model selection and parameter fitting Sensitivity analysis and model adaptation Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples.  This book is intended for graduate stude...

  18. Computation: A New Open Access Journal of Computational Chemistry, Computational Biology and Computational Engineering

    OpenAIRE

    Karlheinz Schwarz; Rainer Breitling; Christian Allen

    2013-01-01

    Computation (ISSN 2079-3197; http://www.mdpi.com/journal/computation) is an international scientific open access journal focusing on fundamental work in the field of computational science and engineering. Computational science has become essential in many research areas by contributing to solving complex problems in fundamental science all the way to engineering. The very broad range of application domains suggests structuring this journal into three sections, which are briefly characterized ...

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

    Science.gov (United States)

    Melham, Tom

    2013-04-01

    Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. The computational linguistics of biological sequences

    Energy Technology Data Exchange (ETDEWEB)

    Searls, D. [Univ. of Pennsylvania, Philadelphia, PA (United States)

    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.

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

    Science.gov (United States)

    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…

  2. Computation: A New Open Access Journal of Computational Chemistry, Computational Biology and Computational Engineering

    Directory of Open Access Journals (Sweden)

    Karlheinz Schwarz

    2013-09-01

    Full Text Available Computation (ISSN 2079-3197; http://www.mdpi.com/journal/computation is an international scientific open access journal focusing on fundamental work in the field of computational science and engineering. Computational science has become essential in many research areas by contributing to solving complex problems in fundamental science all the way to engineering. The very broad range of application domains suggests structuring this journal into three sections, which are briefly characterized below. In each section a further focusing will be provided by occasionally organizing special issues on topics of high interests, collecting papers on fundamental work in the field. More applied papers should be submitted to their corresponding specialist journals. To help us achieve our goal with this journal, we have an excellent editorial board to advise us on the exciting current and future trends in computation from methodology to application. We very much look forward to hearing all about the research going on across the world. [...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2012-01-01

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

  6. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-26

    RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp.

  7. XIV Mediterranean Conference on Medical and Biological Engineering and Computing

    CERN Document Server

    Christofides, Stelios; Pattichis, Constantinos

    2016-01-01

    This volume presents the proceedings of Medicon 2016, held in Paphos, Cyprus. Medicon 2016 is the XIV in the series of regional meetings of the International Federation of Medical and Biological Engineering (IFMBE) in the Mediterranean. The goal of Medicon 2016 is to provide updated information on the state of the art on Medical and Biological Engineering and Computing under the main theme “Systems Medicine for the Delivery of Better Healthcare Services”. Medical and Biological Engineering and Computing cover complementary disciplines that hold great promise for the advancement of research and development in complex medical and biological systems. Research and development in these areas are impacting the science and technology by advancing fundamental concepts in translational medicine, by helping us understand human physiology and function at multiple levels, by improving tools and techniques for the detection, prevention and treatment of disease. Medicon 2016 provides a common platform for the cross fer...

  8. The Virtual Cell: a software environment for computational cell biology.

    Science.gov (United States)

    Loew, L M; Schaff, J C

    2001-10-01

    The newly emerging field of computational cell biology requires software tools that address the needs of a broad community of scientists. Cell biological processes are controlled by an interacting set of biochemical and electrophysiological events that are distributed within complex cellular structures. Computational modeling is familiar to researchers in fields such as molecular structure, neurobiology and metabolic pathway engineering, and is rapidly emerging in the area of gene expression. Although some of these established modeling approaches can be adapted to address problems of interest to cell biologists, relatively few software development efforts have been directed at the field as a whole. The Virtual Cell is a computational environment designed for cell biologists as well as for mathematical biologists and bioengineers. It serves to aid the construction of cell biological models and the generation of simulations from them. The system enables the formulation of both compartmental and spatial models, the latter with either idealized or experimentally derived geometries of one, two or three dimensions.

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

    DEFF Research Database (Denmark)

    Gentleman, R.C.; Carey, V.J.; Bates, D.M.

    2004-01-01

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

  10. Computational Biomechanics Theoretical Background and BiologicalBiomedical Problems

    CERN Document Server

    Tanaka, Masao; Nakamura, Masanori

    2012-01-01

    Rapid developments have taken place in biological/biomedical measurement and imaging technologies as well as in computer analysis and information technologies. The increase in data obtained with such technologies invites the reader into a virtual world that represents realistic biological tissue or organ structures in digital form and allows for simulation and what is called “in silico medicine.” This volume is the third in a textbook series and covers both the basics of continuum mechanics of biosolids and biofluids and the theoretical core of computational methods for continuum mechanics analyses. Several biomechanics problems are provided for better understanding of computational modeling and analysis. Topics include the mechanics of solid and fluid bodies, fundamental characteristics of biosolids and biofluids, computational methods in biomechanics analysis/simulation, practical problems in orthopedic biomechanics, dental biomechanics, ophthalmic biomechanics, cardiovascular biomechanics, hemodynamics...

  11. Structure, function, and behaviour of computational models in systems biology.

    Science.gov (United States)

    Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Le Novère, Nicolas

    2013-05-31

    Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such "bio-models" necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. We present a conceptual framework - the meaning facets - which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model's components (structure), the meaning of the model's intended use (function), and the meaning of the model's dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

  12. Catalyzing Inquiry at the Interface of Computing and Biology

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  14. 7th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Engelbrecht, Andries; Abraham, Ajith; Plessis, Mathys; Snášel, Václav; Muda, Azah

    2016-01-01

    World Congress on Nature and Biologically Inspired Computing (NaBIC) is organized to discuss the state-of-the-art as well as to address various issues with respect to Nurturing Intelligent Computing Towards Advancement of Machine Intelligence. This Volume contains the papers presented in the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africa during December 01-03, 2015. The 39 papers presented in this Volume were carefully reviewed and selected. The Volume would be a valuable reference to researchers, students and practitioners in the computational intelligence field.

  15. Inter-level relations in computer science, biology, and psychology

    NARCIS (Netherlands)

    Boogerd, F.; Bruggeman, F.; Jonker, C.M.; Looren de Jong, H.; Tamminga, A.; Treur, J.; Westerhoff, H.V.; Wijngaards, W.C.A.

    2002-01-01

    Investigations into inter-level relations in computer science, biology and psychology call for an empirical turn in the philosophy of mind. Rather than concentrate on a priori discussions of inter-level relations between 'completed' sciences, a case is made for the actual study of the way

  16. Inter-level relations in computer science, biology and psychology

    NARCIS (Netherlands)

    Boogerd, F.C.; Bruggeman, F.J.; Jonker, C.M.; Looren De Jong, H.; Tamminga, A.M.; Treur, J.; Westerhoff, H.V.; Wijngaards, W.C.A.

    2002-01-01

    Investigations into inter-level relations in computer science, biology and psychology call for an empirical turn in the philosophy of mind. Rather than concentrate on a priori discussions of inter-level relations between "completed" sciences, a case is made for the actual study of the way

  17. Inter-level relations in computer science, biology, and psychology

    NARCIS (Netherlands)

    Boogerd, Fred; Bruggeman, Frank; Jonker, Catholijn; Looren de Jong, Huib; Tamminga, Allard; Treur, Jan; Westerhoff, Hans; Wijngaards, Wouter

    2002-01-01

    Investigations into inter-level relations in computer science, biology and psychology call for an *empirical* turn in the philosophy of mind. Rather than concentrate on *a priori* discussions of inter-level relations between “completed” sciences, a case is made for the actual study of the way

  18. Filling the gap between biology and computer science.

    Science.gov (United States)

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

    2008-07-17

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

  19. Biology Students Building Computer Simulations Using StarLogo TNG

    Science.gov (United States)

    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…

  20. 2nd Colombian Congress on Computational Biology and Bioinformatics

    CERN Document Server

    Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan

    2014-01-01

    This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis.  .

  1. Discovery of novel bacterial toxins by genomics and computational biology.

    Science.gov (United States)

    Doxey, Andrew C; Mansfield, Michael J; Montecucco, Cesare

    2018-06-01

    Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology. One consequence is that genes encoding novel bacterial toxins can be identified by bioinformatic and computational methods based on previous knowledge accumulated from studies of the biology and pathology of thousands of known bacterial protein toxins. Starting from the paradigmatic cases of diphtheria toxin, tetanus and botulinum neurotoxins, this review discusses traditional experimental approaches as well as bioinformatics and genomics-driven approaches that facilitate the discovery of novel bacterial toxins. We discuss recent work on the identification of novel botulinum-like toxins from genera such as Weissella, Chryseobacterium, and Enteroccocus, and the implications of these computationally identified toxins in the field. Finally, we discuss the promise of metagenomics in the discovery of novel toxins and their ecological niches, and present data suggesting the existence of uncharacterized, botulinum-like toxin genes in insect gut metagenomes. Copyright © 2018. Published by Elsevier Ltd.

  2. Computational Biology and the Limits of Shared Vision

    DEFF Research Database (Denmark)

    Carusi, Annamaria

    2011-01-01

    of cases is necessary in order to gain a better perspective on social sharing of practices, and on what other factors this sharing is dependent upon. The article presents the case of currently emerging inter-disciplinary visual practices in the domain of computational biology, where the sharing of visual...... practices would be beneficial to the collaborations necessary for the research. Computational biology includes sub-domains where visual practices are coming to be shared across disciplines, and those where this is not occurring, and where the practices of others are resisted. A significant point......, its domain of study. Social practices alone are not sufficient to account for the shaping of evidence. The philosophy of Merleau-Ponty is introduced as providing an alternative framework for thinking of the complex inter-relations between all of these factors. This [End Page 300] philosophy enables us...

  3. Application of computational systems biology to explore environmental toxicity hazards

    DEFF Research Database (Denmark)

    Audouze, Karine Marie Laure; Grandjean, Philippe

    2011-01-01

    Background: Computer-based modeling is part of a new approach to predictive toxicology.Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT......) to ascertain their possible links to relevant adverse effects.Methods: We extracted chemical-protein association networks for each DDT isomer and its metabolites using ChemProt, a disease chemical biology database that includes both binding and gene expression data, and we explored protein-protein interactions...... using a human interactome network. To identify associated dysfunctions and diseases, we integrated protein-disease annotations into the protein complexes using the Online Mendelian Inheritance in Man database and the Comparative Toxicogenomics Database.Results: We found 175 human proteins linked to p,p´-DDT...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-10-01

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

  5. Computing paths and cycles in biological interaction graphs

    Directory of Open Access Journals (Sweden)

    von Kamp Axel

    2009-06-01

    Full Text Available Abstract Background Interaction graphs (signed directed graphs provide an important qualitative modeling approach for Systems Biology. They enable the analysis of causal relationships in cellular networks and can even be useful for predicting qualitative aspects of systems dynamics. Fundamental issues in the analysis of interaction graphs are the enumeration of paths and cycles (feedback loops and the calculation of shortest positive/negative paths. These computational problems have been discussed only to a minor extent in the context of Systems Biology and in particular the shortest signed paths problem requires algorithmic developments. Results We first review algorithms for the enumeration of paths and cycles and show that these algorithms are superior to a recently proposed enumeration approach based on elementary-modes computation. The main part of this work deals with the computation of shortest positive/negative paths, an NP-complete problem for which only very few algorithms are described in the literature. We propose extensions and several new algorithm variants for computing either exact results or approximations. Benchmarks with various concrete biological networks show that exact results can sometimes be obtained in networks with several hundred nodes. A class of even larger graphs can still be treated exactly by a new algorithm combining exhaustive and simple search strategies. For graphs, where the computation of exact solutions becomes time-consuming or infeasible, we devised an approximative algorithm with polynomial complexity. Strikingly, in realistic networks (where a comparison with exact results was possible this algorithm delivered results that are very close or equal to the exact values. This phenomenon can probably be attributed to the particular topology of cellular signaling and regulatory networks which contain a relatively low number of negative feedback loops. Conclusion The calculation of shortest positive

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

    Science.gov (United States)

    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.

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

    OpenAIRE

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

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

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

    Science.gov (United States)

    Patterson, Eann A; Whelan, Maurice P

    2017-10-01

    Computational models in biology and biomedical science are often constructed to aid people's understanding of phenomena or to inform decisions with socioeconomic consequences. Model credibility is the willingness of people to trust a model's predictions and is often difficult to establish for computational biology models. A 3 × 3 matrix has been proposed to allow such models to be categorised with respect to their testability and epistemic foundation in order to guide the selection of an appropriate process of validation to supply evidence to establish credibility. Three approaches to validation are identified that can be deployed depending on whether a model is deemed untestable, testable or lies somewhere in between. In the latter two cases, the validation process involves the quantification of uncertainty which is a key output. The issues arising due to the complexity and inherent variability of biological systems are discussed and the creation of 'digital twins' proposed as a means to alleviate the issues and provide a more robust, transparent and traceable route to model credibility and acceptance. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

    Science.gov (United States)

    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.

  10. Computer modeling in developmental biology: growing today, essential tomorrow.

    Science.gov (United States)

    Sharpe, James

    2017-12-01

    D'Arcy Thompson was a true pioneer, applying mathematical concepts and analyses to the question of morphogenesis over 100 years ago. The centenary of his famous book, On Growth and Form , is therefore a great occasion on which to review the types of computer modeling now being pursued to understand the development of organs and organisms. Here, I present some of the latest modeling projects in the field, covering a wide range of developmental biology concepts, from molecular patterning to tissue morphogenesis. Rather than classifying them according to scientific question, or scale of problem, I focus instead on the different ways that modeling contributes to the scientific process and discuss the likely future of modeling in developmental biology. © 2017. Published by The Company of Biologists Ltd.

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

    Science.gov (United States)

    Kasson, Peter M

    2013-01-01

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

  12. Parallel computing and molecular dynamics of biological membranes

    International Nuclear Information System (INIS)

    La Penna, G.; Letardi, S.; Minicozzi, V.; Morante, S.; Rossi, G.C.; Salina, G.

    1998-01-01

    In this talk I discuss the general question of the portability of molecular dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision of the today available platforms does not seem to affect the numerical accuracy of the simulations, while the absence of integer addressing from CPU to individual nodes puts strong constraints on possible programming strategies. Liquids can be satisfactorily simulated using the ''systolic'' method. For more complex systems, like the biological ones at which we are ultimately interested in, the ''domain decomposition'' approach is best suited to beat the quadratic growth of the inter-molecular computational time with the number of atoms of the system. The promising perspectives of using this strategy for extensive simulations of lipid bilayers are briefly reviewed. (orig.)

  13. Community-driven computational biology with Debian Linux.

    Science.gov (United States)

    Möller, Steffen; Krabbenhöft, Hajo Nils; Tille, Andreas; Paleino, David; Williams, Alan; Wolstencroft, Katy; Goble, Carole; Holland, Richard; Belhachemi, Dominique; Plessy, Charles

    2010-12-21

    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. 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. 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.

  14. Computational brain models: Advances from system biology and future challenges

    Directory of Open Access Journals (Sweden)

    George E. Barreto

    2015-02-01

    Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    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. Revision history aware repositories of computational models of biological systems.

    Science.gov (United States)

    Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

    2011-01-14

    Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware

  18. Revision history aware repositories of computational models of biological systems

    Directory of Open Access Journals (Sweden)

    Nickerson David P

    2011-01-01

    Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

  19. Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

    Science.gov (United States)

    Diaz Ochoa, Juan G

    2018-01-01

    Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

  20. Computer simulations for biological aging and sexual reproduction

    Directory of Open Access Journals (Sweden)

    DIETRICH STAUFFER

    2001-03-01

    Full Text Available The sexual version of the Penna model of biological aging, simulated since 1996, is compared here with alternative forms of reproduction as well as with models not involving aging. In particular we want to check how sexual forms of life could have evolved and won over earlier asexual forms hundreds of million years ago. This computer model is based on the mutation-accumulation theory of aging, using bits-strings to represent the genome. Its population dynamics is studied by Monte Carlo methods.A versão sexual do modelo de envelhecimento biológico de Penna, simulada desde 1996, é comparada aqui com formas alternativas de reprodução bem como com modelos que não envolvem envelhecimento. Em particular, queremos verificar como formas sexuais de vida poderiam ter evoluído e predominado sobre formas assexuais há centenas de milhões de anos. Este modelo computacional baseia-se na teoria do envelhecimento por acumulação de mutações, usando 'bits-strings' para representar o genoma. Sua dinâmica de populações é estudada por métodos de Monte Carlo.

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

    Science.gov (United States)

    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.

  2. Computational Biology Methods for Characterization of Pluripotent Cells.

    Science.gov (United States)

    Araúzo-Bravo, Marcos J

    2016-01-01

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

  3. The Air Force "In Silico" -- Computational Biology in 2025

    National Research Council Canada - National Science Library

    Coates, Christopher

    2007-01-01

    The biological sciences have recently experienced remarkable advances and there are now frequent claims that "we are on the advent of being able to model or simulate biological systems to the smallest, molecular detail...

  4. 9th International Conference on Practical Applications of Computational Biology and Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan

    2015-01-01

    This proceedings presents recent practical applications of Computational Biology and  Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  6. Parallel metaheuristics in computational biology: an asynchronous cooperative enhanced scatter search method

    OpenAIRE

    Penas, David R.; González, Patricia; Egea, José A.; Banga, Julio R.; Doallo, Ramón

    2015-01-01

    Metaheuristics are gaining increased attention as efficient solvers for hard global optimization problems arising in bioinformatics and computational systems biology. Scatter Search (SS) is one of the recent outstanding algorithms in that class. However, its application to very hard problems, like those considering parameter estimation in dynamic models of systems biology, still results in excessive computation times. In order to reduce the computational cost of the SS and improve its success...

  7. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

    OpenAIRE

    Shuo Gu; Jianfeng Pei

    2017-01-01

    With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regula...

  8. Computational tools for high-throughput discovery in biology

    OpenAIRE

    Jones, Neil Christopher

    2007-01-01

    High throughput data acquisition technology has inarguably transformed the landscape of the life sciences, in part by making possible---and necessary---the computational disciplines of bioinformatics and biomedical informatics. These fields focus primarily on developing tools for analyzing data and generating hypotheses about objects in nature, and it is in this context that we address three pressing problems in the fields of the computational life sciences which each require computing capaci...

  9. 6th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Luscombe, Nicholas; Fdez-Riverola, Florentino; Rodríguez, Juan; Practical Applications of Computational Biology & Bioinformatics

    2012-01-01

    The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable.. The analysis of the datasets of Next Generation Sequencing needs new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Also Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. This book presents the results of the  6th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, 28-30th March, 2012 which brought together interdisciplinary scientists that have a strong background in the biological and computational sciences.

  10. 7th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Nanni, Loris; Rocha, Miguel; Fdez-Riverola, Florentino

    2013-01-01

    The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we ...

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

    Science.gov (United States)

    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…

  12. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

    Directory of Open Access Journals (Sweden)

    Shuo Gu

    2017-01-01

    Full Text Available With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

  13. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.

    Science.gov (United States)

    Gu, Shuo; Pei, Jianfeng

    2017-01-01

    With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

  14. 8th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Santana, Juan

    2014-01-01

    Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

  15. 11th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Mohamad, Mohd; Rocha, Miguel; Paz, Juan; Pinto, Tiago

    2017-01-01

    Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of r...

  16. 10th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Mayo, Francisco; Paz, Juan

    2016-01-01

    Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

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

    Science.gov (United States)

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

  18. Where mathematics, computer science, linguistics and biology meet essays in honour of Gheorghe Păun

    CERN Document Server

    Mitrana, Victor

    2001-01-01

    In the last years, it was observed an increasing interest of computer scientists in the structure of biological molecules and the way how they can be manipulated in vitro in order to define theoretical models of computation based on genetic engineering tools. Along the same lines, a parallel interest is growing regarding the process of evolution of living organisms. Much of the current data for genomes are expressed in the form of maps which are now becoming available and permit the study of the evolution of organisms at the scale of genome for the first time. On the other hand, there is an active trend nowadays throughout the field of computational biology toward abstracted, hierarchical views of biological sequences, which is very much in the spirit of computational linguistics. In the last decades, results and methods in the field of formal language theory that might be applied to the description of biological sequences were pointed out.

  19. Complex fluids in biological systems experiment, theory, and computation

    CERN Document Server

    2015-01-01

    This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

  20. Fundamentals of bioinformatics and computational biology methods and exercises in matlab

    CERN Document Server

    Singh, Gautam B

    2015-01-01

    This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...

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

    Directory of Open Access Journals (Sweden)

    Peter D. Karp

    2015-01-01

    Full Text Available 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.

  2. Computer simulation of heating of biological tissue during laser radiation

    International Nuclear Information System (INIS)

    Bojanic, S.; Sreckovic, M.

    1995-01-01

    Computer model is based on an implicit finite difference scheme to solve the diffusion equation for light distribution and the bio-heat equation. A practical application of the model is to calculate the temperature distributions during thermal coagulation of prostate by radiative heating. (author)

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

    Science.gov (United States)

    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,…

  4. Inferring biological functions of guanylyl cyclases with computational methods

    KAUST Repository

    Alquraishi, May Majed; Meier, Stuart Kurt

    2013-01-01

    A number of studies have shown that functionally related genes are often co-expressed and that computational based co-expression analysis can be used to accurately identify functional relationships between genes and by inference, their encoded proteins. Here we describe how a computational based co-expression analysis can be used to link the function of a specific gene of interest to a defined cellular response. Using a worked example we demonstrate how this methodology is used to link the function of the Arabidopsis Wall-Associated Kinase-Like 10 gene, which encodes a functional guanylyl cyclase, to host responses to pathogens. © Springer Science+Business Media New York 2013.

  5. Inferring biological functions of guanylyl cyclases with computational methods

    KAUST Repository

    Alquraishi, May Majed

    2013-09-03

    A number of studies have shown that functionally related genes are often co-expressed and that computational based co-expression analysis can be used to accurately identify functional relationships between genes and by inference, their encoded proteins. Here we describe how a computational based co-expression analysis can be used to link the function of a specific gene of interest to a defined cellular response. Using a worked example we demonstrate how this methodology is used to link the function of the Arabidopsis Wall-Associated Kinase-Like 10 gene, which encodes a functional guanylyl cyclase, to host responses to pathogens. © Springer Science+Business Media New York 2013.

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

    Science.gov (United States)

    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…

  7. Monitoring Biological Modes in a Bioreactor Process by Computer Simulation

    Directory of Open Access Journals (Sweden)

    Samia Semcheddine

    2015-12-01

    Full Text Available This paper deals with the general framework of fermentation system modeling and monitoring, focusing on the fermentation of Escherichia coli. Our main objective is to develop an algorithm for the online detection of acetate production during the culture of recombinant proteins. The analysis the fermentation process shows that it behaves like a hybrid dynamic system with commutation (since it can be represented by 5 nonlinear models. We present a strategy of fault detection based on residual generation for detecting the different actual biological modes. The residual generation is based on nonlinear analytical redundancy relations. The simulation results show that the several modes that are occulted during the bacteria cultivation can be detected by residuals using a nonlinear dynamic model and a reduced instrumentation.

  8. Theoretical discussion for quantum computation in biological systems

    Science.gov (United States)

    Baer, Wolfgang

    2010-04-01

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

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

    OpenAIRE

    Karp, P.D.; Berger, B.; Kovats, D.; Lengauer, T.; Linial, M.; Sabeti, P.; Hide, W.; Rost, B.

    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, computati...

  10. How computational models can help unlock biological systems.

    Science.gov (United States)

    Brodland, G Wayne

    2015-12-01

    With computation models playing an ever increasing role in the advancement of science, it is important that researchers understand what it means to model something; recognize the implications of the conceptual, mathematical and algorithmic steps of model construction; and comprehend what models can and cannot do. Here, we use examples to show that models can serve a wide variety of roles, including hypothesis testing, generating new insights, deepening understanding, suggesting and interpreting experiments, tracing chains of causation, doing sensitivity analyses, integrating knowledge, and inspiring new approaches. We show that models can bring together information of different kinds and do so across a range of length scales, as they do in multi-scale, multi-faceted embryogenesis models, some of which connect gene expression, the cytoskeleton, cell properties, tissue mechanics, morphogenetic movements and phenotypes. Models cannot replace experiments nor can they prove that particular mechanisms are at work in a given situation. But they can demonstrate whether or not a proposed mechanism is sufficient to produce an observed phenomenon. Although the examples in this article are taken primarily from the field of embryo mechanics, most of the arguments and discussion are applicable to any form of computational modelling. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  11. The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

    Science.gov (United States)

    Anupama, Jigisha; Francescatto, Margherita; Rahman, Farzana; Fatima, Nazeefa; DeBlasio, Dan; Shanmugam, Avinash Kumar; Satagopam, Venkata; Santos, Alberto; Kolekar, Pandurang; Michaut, Magali; Guney, Emre

    2018-01-01

    Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

  12. Computational protein design-the next generation tool to expand synthetic biology applications.

    Science.gov (United States)

    Gainza-Cirauqui, Pablo; Correia, Bruno Emanuel

    2018-05-02

    One powerful approach to engineer synthetic biology pathways is the assembly of proteins sourced from one or more natural organisms. However, synthetic pathways often require custom functions or biophysical properties not displayed by natural proteins, limitations that could be overcome through modern protein engineering techniques. Structure-based computational protein design is a powerful tool to engineer new functional capabilities in proteins, and it is beginning to have a profound impact in synthetic biology. Here, we review efforts to increase the capabilities of synthetic biology using computational protein design. We focus primarily on computationally designed proteins not only validated in vitro, but also shown to modulate different activities in living cells. Efforts made to validate computational designs in cells can illustrate both the challenges and opportunities in the intersection of protein design and synthetic biology. We also highlight protein design approaches, which although not validated as conveyors of new cellular function in situ, may have rapid and innovative applications in synthetic biology. We foresee that in the near-future, computational protein design will vastly expand the functional capabilities of synthetic cells. Copyright © 2018. Published by Elsevier Ltd.

  13. The ISCB Student Council Internship Program: Expanding computational biology capacity worldwide.

    Directory of Open Access Journals (Sweden)

    Jigisha Anupama

    2018-01-01

    Full Text Available Education and training are two essential ingredients for a successful career. On one hand, universities provide students a curriculum for specializing in one's field of study, and on the other, internships complement coursework and provide invaluable training experience for a fruitful career. Consequently, undergraduates and graduates are encouraged to undertake an internship during the course of their degree. The opportunity to explore one's research interests in the early stages of their education is important for students because it improves their skill set and gives their career a boost. In the long term, this helps to close the gap between skills and employability among students across the globe and balance the research capacity in the field of computational biology. However, training opportunities are often scarce for computational biology students, particularly for those who reside in less-privileged regions. Aimed at helping students develop research and academic skills in computational biology and alleviating the divide across countries, the Student Council of the International Society for Computational Biology introduced its Internship Program in 2009. The Internship Program is committed to providing access to computational biology training, especially for students from developing regions, and improving competencies in the field. Here, we present how the Internship Program works and the impact of the internship opportunities so far, along with the challenges associated with this program.

  14. WE-DE-202-00: Connecting Radiation Physics with Computational Biology

    International Nuclear Information System (INIS)

    2016-01-01

    Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

  15. WE-DE-202-00: Connecting Radiation Physics with Computational Biology

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2016-06-15

    Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

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

    Science.gov (United States)

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

    2013-12-01

    This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  17. Modeling biological problems in computer science: a case study in genome assembly.

    Science.gov (United States)

    Medvedev, Paul

    2018-01-30

    As computer scientists working in bioinformatics/computational biology, we often face the challenge of coming up with an algorithm to answer a biological question. This occurs in many areas, such as variant calling, alignment and assembly. In this tutorial, we use the example of the genome assembly problem to demonstrate how to go from a question in the biological realm to a solution in the computer science realm. We show the modeling process step-by-step, including all the intermediate failed attempts. Please note this is not an introduction to how genome assembly algorithms work and, if treated as such, would be incomplete and unnecessarily long-winded. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  18. Mathematical computer simulation of the process of ultrasound interaction with biological medium

    International Nuclear Information System (INIS)

    Yakovleva, T.; Nassiri, D.; Ciantar, D.

    1996-01-01

    The aim of the paper is to study theoretically the interaction of ultrasound irradiation with biological medium and the peculiarities of ultrasound scattering by inhomogeneities of biological tissue, which can be represented by fractal structures. This investigation has been used for the construction of the computer model of three-dimensional ultrasonic imaging system what gives the possibility to define more accurately the pathological changes in such a tissue by means of its image analysis. Poster 180. (author)

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

    Directory of Open Access Journals (Sweden)

    Ivo D Dinov

    2008-05-01

    Full Text Available 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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2007-02-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Allen, Edward J

    2014-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    Quinn, Terrance; Sinkala, Zachariah

    2014-01-01

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

  7. 10 years for the Journal of Bioinformatics and Computational Biology (2003-2013) -- a retrospective.

    Science.gov (United States)

    Eisenhaber, Frank; Sherman, Westley Arthur

    2014-06-01

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

  8. Computer-aided design of biological circuits using TinkerCell.

    Science.gov (United States)

    Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M

    2010-01-01

    Synthetic biology is an engineering discipline that builds on modeling practices from systems biology and wet-lab techniques from genetic engineering. As synthetic biology advances, efficient procedures will be developed that will allow a synthetic biologist to design, analyze, and build biological networks. In this idealized pipeline, computer-aided design (CAD) is a necessary component. The role of a CAD application would be to allow efficient transition from a general design to a final product. TinkerCell is a design tool for serving this purpose in synthetic biology. In TinkerCell, users build biological networks using biological parts and modules. The network can be analyzed using one of several functions provided by TinkerCell or custom programs from third-party sources. Since best practices for modeling and constructing synthetic biology networks have not yet been established, TinkerCell is designed as a flexible and extensible application that can adjust itself to changes in the field. © 2010 Landes Bioscience

  9. Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

    CERN Document Server

    2017-01-01

    This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

  10. Defining Biological Networks for Noise Buffering and Signaling Sensitivity Using Approximate Bayesian Computation

    Directory of Open Access Journals (Sweden)

    Shuqiang Wang

    2014-01-01

    Full Text Available Reliable information processing in cells requires high sensitivity to changes in the input signal but low sensitivity to random fluctuations in the transmitted signal. There are often many alternative biological circuits qualifying for this biological function. Distinguishing theses biological models and finding the most suitable one are essential, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Here, we employ the approximate Bayesian computation (ABC method based on sequential Monte Carlo (SMC to search for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. By systematically analyzing three-component circuits, we rank these biological circuits and identify three-basic-biological-motif buffering noise while maintaining sensitivity to long-term changes in input signals. We discuss in detail a particular implementation in control of nutrient homeostasis in yeast. The principal component analysis of the posterior provides insight into the nature of the reaction between nodes.

  11. The transhumanism of Ray Kurzweil. Is biological ontology reducible to computation?

    Directory of Open Access Journals (Sweden)

    Javier Monserrat

    2016-02-01

    Full Text Available Computer programs, primarily engineering machine vision and programming of somatic sensors, have already allowed, and they will do it more perfectly in the future, to build high perfection androids or cyborgs. They will collaborate with man and open new moral reflections to respect the ontological dignity in the new humanoid machines. In addition, both men and new androids will be in connection with huge external computer networks that will grow up to almost incredible levels the efficiency in the domain of body and nature. However, our current scientific knowledge, on the one hand, about hardware and software that will support both the humanoid machines and external computer networks, made with existing engineering (and also the foreseeable medium and even long term engineering and, on the other hand, our scientific knowledge about animal and human behavior from neural-biological structures that produce a psychic system, allow us to establish that there is no scientific basis to talk about an ontological identity between the computational machines and man. Accordingly, different ontologies (computational machines and biological entities will produce various different functional systems. There may be simulation, but never ontological identity. These ideas are essential to assess the transhumanism of Ray Kurzweil.

  12. Periodicity computation of generalized mathematical biology problems involving delay differential equations.

    Science.gov (United States)

    Jasim Mohammed, M; Ibrahim, Rabha W; Ahmad, M Z

    2017-03-01

    In this paper, we consider a low initial population model. Our aim is to study the periodicity computation of this model by using neutral differential equations, which are recognized in various studies including biology. We generalize the neutral Rayleigh equation for the third-order by exploiting the model of fractional calculus, in particular the Riemann-Liouville differential operator. We establish the existence and uniqueness of a periodic computational outcome. The technique depends on the continuation theorem of the coincidence degree theory. Besides, an example is presented to demonstrate the finding.

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Weizhe Zhang

    2013-01-01

    Full Text Available 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.

  15. Computer Simulation and Data Analysis in Molecular Biology and Biophysics An Introduction Using R

    CERN Document Server

    Bloomfield, Victor

    2009-01-01

    This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data analysis. It introduces tools to enable readers to learn and use fundamental methods for constructing quantitative models of biological mechanisms, both deterministic and with some elements of randomness, including complex reaction equilibria and kinetics, population models, and regulation of metabolism and development; to understand how concepts of probability can help in explaining important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data from spectroscopic, genomic, and proteomic sources. These quantitative tools are implemented using the free, open source software program R. R provides an excellent environment for general numerical and statistical computing and graphics, with capabilities similar to Matlab®. Since R is increasingly used in bioinformat...

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

    Science.gov (United States)

    Tadmor, Brigitta; Tidor, Bruce

    2005-09-01

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

  17. ADAM: analysis of discrete models of biological systems using computer algebra.

    Science.gov (United States)

    Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

    2011-07-20

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

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

    Energy Technology Data Exchange (ETDEWEB)

    DOE Office of Science, Biological and Environmental Research Program Office (BER),

    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.

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

    Science.gov (United States)

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

    2016-01-01

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

  20. Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

    Science.gov (United States)

    Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

    2014-01-01

    The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

  1. Dispensing processes impact apparent biological activity as determined by computational and statistical analyses.

    Directory of Open Access Journals (Sweden)

    Sean Ekins

    Full Text Available Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research.

  2. Effectiveness of computer-assisted learning in biology teaching in primary schools in Serbia

    Directory of Open Access Journals (Sweden)

    Županec Vera

    2013-01-01

    Full Text Available The paper analyzes the comparative effectiveness of Computer-Assisted Learning (CAL and the traditional teaching method in biology on primary school pupils. A stratified random sample consisted of 214 pupils from two primary schools in Novi Sad. The pupils in the experimental group learned the biology content (Chordate using CAL, whereas the pupils in the control group learned the same content using traditional teaching. The research design was the pretest-posttest equivalent groups design. All instruments (the pretest, the posttest and the retest contained the questions belonging to three different cognitive domains: knowing, applying, and reasoning. Arithmetic mean, standard deviation, and standard error were analyzed using the software package SPSS 14.0, and t-test was used in order to establish the difference between the same statistical indicators. The analysis of results of the post­test and the retest showed that the pupils from the CAL group achieved significantly higher quantity and quality of knowledge in all three cognitive domains than the pupils from the traditional group. The results accomplished by the pupils from the CAL group suggest that individual CAL should be more present in biology teaching in primary schools, with the aim of raising the quality of biology education in pupils. [Projekat Ministarstva nauke Republike Srbije, br. 179010: Quality of Educational System in Serbia in the European Perspective

  3. Proceedings of the 8. Mediterranean Conference on Medical and Biological Engineering and Computing (Medicon `98)

    Energy Technology Data Exchange (ETDEWEB)

    Christofides, Stelios; Pattichis, Constantinos; Schizas, Christos; Keravnou-Papailiou, Elpida; Kaplanis, Prodromos; Spyros, Spyrou; Christodoulides, George; Theodoulou, Yiannis [eds.

    1999-12-31

    Medicon `98 is the eighth in the series of regional meetings of the International Federation of Medical and Biological Engineering (IFMBE) in the Mediterranean. The goal of Medicon `98 is to provide updated information on the state of the art on medical and biological engineering and computing. Medicon `98 was held in Lemesos, Cyprus, between 14-17 June, 1998. The full papers of the proceedings were published on CD and consisted of 190 invited and submitted papers. A book of abstracts was also published in paper form and was available to all the participants. Twenty seven papers fall within the scope of INIS and are dealing with Nuclear Medicine,Computerized Tomography, Radiology, Radiotherapy, Magnetic Resonance Imaging and Personnel Dosimetry (eds).

  4. Proceedings of the 8. Mediterranean Conference on Medical and Biological Engineering and Computing (Medicon '98)

    International Nuclear Information System (INIS)

    Christofides, Stelios; Pattichis, Constantinos; Schizas, Christos; Keravnou-Papailiou, Elpida; Kaplanis, Prodromos; Spyros, Spyrou; Christodoulides, George; Theodoulou, Yiannis

    1998-01-01

    Medicon '98 is the eighth in the series of regional meetings of the International Federation of Medical and Biological Engineering (IFMBE) in the Mediterranean. The goal of Medicon '98 is to provide updated information on the state of the art on medical and biological engineering and computing. Medicon '98 was held in Lemesos, Cyprus, between 14-17 June, 1998. The full papers of the proceedings were published on CD and consisted of 190 invited and submitted papers. A book of abstracts was also published in paper form and was available to all the participants. Twenty seven papers fall within the scope of INIS and are dealing with Nuclear Medicine,Computerized Tomography, Radiology, Radiotherapy, Magnetic Resonance Imaging and Personnel Dosimetry (eds)

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

    Science.gov (United States)

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

    2010-02-01

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

  6. On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

    KAUST Repository

    Moreo, P.; Gaffney, E. A.; Garcí a-Aznar, J. M.; Doblaré , M.

    2009-01-01

    The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise

  7. MACBenAbim: A Multi-platform Mobile Application for searching keyterms in Computational Biology and Bioinformatics.

    Science.gov (United States)

    Oluwagbemi, Olugbenga O; Adewumi, Adewole; Esuruoso, Abimbola

    2012-01-01

    Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context. MACBenAbim is available from the authors for non-commercial purposes.

  8. Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference.

    Science.gov (United States)

    Wren, Jonathan D; Dozmorov, Mikhail G; Burian, Dennis; Kaundal, Rakesh; Perkins, Andy; Perkins, Ed; Kupfer, Doris M; Springer, Gordon K

    2013-01-01

    The tenth annual conference of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS 2013), "The 10th Anniversary in a Decade of Change: Discovery in a Sea of Data", took place at the Stoney Creek Inn & Conference Center in Columbia, Missouri on April 5-6, 2013. This year's Conference Chairs were Gordon Springer and Chi-Ren Shyu from the University of Missouri and Edward Perkins from the US Army Corps of Engineers Engineering Research and Development Center, who is also the current MCBIOS President (2012-3). There were 151 registrants and a total of 111 abstracts (51 oral presentations and 60 poster session abstracts).

  9. SED-ED, a workflow editor for computational biology experiments written in SED-ML.

    Science.gov (United States)

    Adams, Richard R

    2012-04-15

    The simulation experiment description markup language (SED-ML) is a new community data standard to encode computational biology experiments in a computer-readable XML format. Its widespread adoption will require the development of software support to work with SED-ML files. Here, we describe a software tool, SED-ED, to view, edit, validate and annotate SED-ML documents while shielding end-users from the underlying XML representation. SED-ED supports modellers who wish to create, understand and further develop a simulation description provided in SED-ML format. SED-ED is available as a standalone Java application, as an Eclipse plug-in and as an SBSI (www.sbsi.ed.ac.uk) plug-in, all under an MIT open-source license. Source code is at https://sed-ed-sedmleditor.googlecode.com/svn. The application itself is available from https://sourceforge.net/projects/jlibsedml/files/SED-ED/.

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

    Energy Technology Data Exchange (ETDEWEB)

    TermehYousefi, Amin, E-mail: at.tyousefi@gmail.com [Department of Human Intelligence Systems, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech) (Japan); Bagheri, Samira; Shahnazar, Sheida [Nanotechnology & Catalysis Research Centre (NANOCAT), IPS Building, University Malaya, 50603 Kuala Lumpur (Malaysia); Rahman, Md. Habibur [Department of Computer Science and Engineering, University of Asia Pacific, Green Road, Dhaka-1215 (Bangladesh); Kadri, Nahrizul Adib [Department of Biomedical Engineering, Faculty of Engineering, University Malaya, 50603 Kuala Lumpur (Malaysia)

    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. - Graphical abstract: 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. 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

  11. Computational Assessment of Pharmacokinetics and Biological Effects of Some Anabolic and Androgen Steroids.

    Science.gov (United States)

    Roman, Marin; Roman, Diana Larisa; Ostafe, Vasile; Ciorsac, Alecu; Isvoran, Adriana

    2018-02-05

    The aim of this study is to use computational approaches to predict the ADME-Tox profiles, pharmacokinetics, molecular targets, biological activity spectra and side/toxic effects of 31 anabolic and androgen steroids in humans. The following computational tools are used: (i) FAFDrugs4, SwissADME and admetSARfor obtaining the ADME-Tox profiles and for predicting pharmacokinetics;(ii) SwissTargetPrediction and PASS online for predicting the molecular targets and biological activities; (iii) PASS online, Toxtree, admetSAR and Endocrine Disruptomefor envisaging the specific toxicities; (iv) SwissDock to assess the interactions of investigated steroids with cytochromes involved in drugs metabolism. Investigated steroids usually reveal a high gastrointestinal absorption and a good oral bioavailability, may inhibit someof the human cytochromes involved in the metabolism of xenobiotics (CYP2C9 being the most affected) and reflect a good capacity for skin penetration. There are predicted numerous side effects of investigated steroids in humans: genotoxic carcinogenicity, hepatotoxicity, cardiovascular, hematotoxic and genitourinary effects, dermal irritations, endocrine disruption and reproductive dysfunction. These results are important to be known as an occupational exposure to anabolic and androgenic steroids at workplaces may occur and because there also is a deliberate human exposure to steroids for their performance enhancement and anti-aging properties.

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

    Directory of Open Access Journals (Sweden)

    Sungsoo Na

    2009-09-01

    Full Text Available 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.

  13. Discovering local patterns of co - evolution: computational aspects and biological examples

    Directory of Open Access Journals (Sweden)

    Tuller Tamir

    2010-01-01

    Full Text Available Abstract Background Co-evolution is the process in which two (or more sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions and to predict physical interactions. More generally, it can be used for answering fundamental questions about the evolution of biological systems. Orthologs that exhibit a strong signal of co-evolution in a certain part of the evolutionary tree may show a mild signal of co-evolution in other branches of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive selection. Previous publications in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local. Results In this work, we describe a new set of biological problems that are related to finding patterns of local co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above. We use our approach to trace the co-evolution of fungal, eukaryotic, and mammalian genes at high resolution across the different parts of the corresponding phylogenetic trees. Specifically, we discover regions in the fungi tree that are enriched with positive evolution. We show that metabolic genes exhibit a remarkable level of co-evolution and different patterns of co-evolution in various biological datasets. In addition, we find that protein complexes that are related to gene expression exhibit non-homogenous levels of co-evolution across different parts of the fungi evolutionary line. In the case of mammalian evolution

  14. RISE OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY IN INDIA: A LOOK THROUGH PUBLICATIONS

    Directory of Open Access Journals (Sweden)

    Anjali Srivastava

    2017-09-01

    Full Text Available Computational biology and bioinformatics have been part and parcel of biomedical research for few decades now. However, the institutionalization of bioinformatics research took place with the establishment of Distributed Information Centres (DISCs in the research institutions of repute in various disciplines by the Department of Biotechnology, Government of India. Though, at initial stages, this endeavor was mainly focused on providing infrastructure for using information technology and internet based communication and tools for carrying out computational biology and in-silico assisted research in varied arena of research starting from disease biology to agricultural crops, spices, veterinary science and many more, the natural outcome of establishment of such facilities resulted into new experiments with bioinformatics tools. Thus, Biotechnology Information Systems (BTIS grew into a solid movement and a large number of publications started coming out of these centres. In the end of last century, bioinformatics started developing like a full-fledged research subject. In the last decade, a need was felt to actually make a factual estimation of the result of this endeavor of DBT which had, by then, established about two hundred centres in almost all disciplines of biomedical research. In a bid to evaluate the efforts and outcome of these centres, BTIS Centre at CSIR-CDRI, Lucknow was entrusted with collecting and collating the publications of these centres. However, when the full data was compiled, the DBT task force felt that the study must include Non-BTIS centres also so as to expand the report to have a glimpse of bioinformatics publications from the country.

  15. Delivering The Benefits of Chemical-Biological Integration in Computational Toxicology at the EPA (ACS Fall meeting)

    Science.gov (United States)

    Abstract: Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intent...

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

    Science.gov (United States)

    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)

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

    Science.gov (United States)

    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

  18. What it takes to understand and cure a living system: computational systems biology and a systems biology-driven pharmacokinetics-pharmacodynamics platform

    NARCIS (Netherlands)

    Swat, Maciej; Kiełbasa, Szymon M.; Polak, Sebastian; Olivier, Brett; Bruggeman, Frank J.; Tulloch, Mark Quinton; Snoep, Jacky L.; Verhoeven, Arthur J.; Westerhoff, Hans V.

    2011-01-01

    The utility of model repositories is discussed in the context of systems biology (SB). It is shown how such repositories, and in particular their live versions, can be used for computational SB: we calculate the robustness of the yeast glycolytic network with respect to perturbations of one of its

  19. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    Energy Technology Data Exchange (ETDEWEB)

    Guerrier, C. [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Holcman, D., E-mail: david.holcman@ens.fr [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Mathematical Institute, Oxford OX2 6GG, Newton Institute (United Kingdom)

    2017-07-01

    The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

  20. Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

    International Nuclear Information System (INIS)

    Guerrier, C.; Holcman, D.

    2017-01-01

    The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.

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

    Science.gov (United States)

    Pârvu, Ovidiu; Gilbert, David

    2016-01-01

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

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

    KAUST Repository

    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.

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

    Directory of Open Access Journals (Sweden)

    Gary R Mirams

    Full Text Available 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.

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

    Science.gov (United States)

    Adie, Steven G; Graf, Benedikt W; Ahmad, Adeel; Carney, P Scott; Boppart, Stephen A

    2012-05-08

    Aberrations in optical microscopy reduce image resolution and contrast, and can limit imaging depth when focusing into biological samples. Static correction of aberrations may be achieved through appropriate lens design, but this approach does not offer the flexibility of simultaneously correcting aberrations for all imaging depths, nor the adaptability to correct for sample-specific aberrations for high-quality tomographic optical imaging. Incorporation of adaptive optics (AO) methods have demonstrated considerable improvement in optical image contrast and resolution in noninterferometric microscopy techniques, as well as in optical coherence tomography. Here we present a method to correct aberrations in a tomogram rather than the beam of a broadband optical interferometry system. Based on Fourier optics principles, we correct aberrations of a virtual pupil using Zernike polynomials. When used in conjunction with the computed imaging method interferometric synthetic aperture microscopy, this computational AO enables object reconstruction (within the single scattering limit) with ideal focal-plane resolution at all depths. Tomographic reconstructions of tissue phantoms containing subresolution titanium-dioxide particles and of ex vivo rat lung tissue demonstrate aberration correction in datasets acquired with a highly astigmatic illumination beam. These results also demonstrate that imaging with an aberrated astigmatic beam provides the advantage of a more uniform depth-dependent signal compared to imaging with a standard gaussian beam. With further work, computational AO could enable the replacement of complicated and expensive optical hardware components with algorithms implemented on a standard desktop computer, making high-resolution 3D interferometric tomography accessible to a wider group of users and nonspecialists.

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

    KAUST Repository

    Mirams, Gary R

    2013-03-14

    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.

  6. Phase-contrast x-ray computed tomography for biological imaging

    Science.gov (United States)

    Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

    1997-10-01

    We have shown so far that 3D structures in biological sot tissues such as cancer can be revealed by phase-contrast x- ray computed tomography using an x-ray interferometer. As a next step, we aim at applications of this technique to in vivo observation, including radiographic applications. For this purpose, the size of view field is desired to be more than a few centimeters. Therefore, a larger x-ray interferometer should be used with x-rays of higher energy. We have evaluated the optimal x-ray energy from an aspect of does as a function of sample size. Moreover, desired spatial resolution to an image sensor is discussed as functions of x-ray energy and sample size, basing on a requirement in the analysis of interference fringes.

  7. Quantum annealing versus classical machine learning applied to a simplified computational biology problem

    Science.gov (United States)

    Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

    2018-01-01

    Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

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

    Energy Technology Data Exchange (ETDEWEB)

    Langston, Michael A. [Univ. of Tennessee, Knoxville, TN (United States)

    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.

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

    Science.gov (United States)

    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.

  10. CoreFlow: A computational platform for integration, analysis and modeling of complex biological data

    DEFF Research Database (Denmark)

    Pasculescu, Adrian; Schoof, Erwin; Creixell, Pau

    2014-01-01

    between data generation, analysis and manuscript writing. CoreFlow is being released to the scientific community as an open-sourced software package complete with proteomics-specific examples, which include corrections for incomplete isotopic labeling of peptides (SILAC) or arginine-to-proline conversion......A major challenge in mass spectrometry and other large-scale applications is how to handle, integrate, and model the data that is produced. Given the speed at which technology advances and the need to keep pace with biological experiments, we designed a computational platform, CoreFlow, which...... provides programmers with a framework to manage data in real-time. It allows users to upload data into a relational database (MySQL), and to create custom scripts in high-level languages such as R, Python, or Perl for processing, correcting and modeling this data. CoreFlow organizes these scripts...

  11. Molecular structure descriptors in the computer-aided design of biologically active compounds

    International Nuclear Information System (INIS)

    Raevsky, Oleg A

    1999-01-01

    The current state of description of molecular structure in computer-aided molecular design of biologically active compounds by means of descriptors is analysed. The information contents of descriptors increases in the following sequence: element-level descriptors-structural formulae descriptors-electronic structure descriptors-molecular shape descriptors-intermolecular interaction descriptors. Each subsequent class of descriptors normally covers information contained in the previous-level ones. It is emphasised that it is practically impossible to describe all the features of a molecular structure in terms of any single class of descriptors. It is recommended to optimise the number of descriptors used by means of appropriate statistical procedures and characteristics of structure-property models based on these descriptors. The bibliography includes 371 references.

  12. Micro-computed tomography imaging and analysis in developmental biology and toxicology.

    Science.gov (United States)

    Wise, L David; Winkelmann, Christopher T; Dogdas, Belma; Bagchi, Ansuman

    2013-06-01

    Micro-computed tomography (micro-CT) is a high resolution imaging technique that has expanded and strengthened in use since it was last reviewed in this journal in 2004. The technology has expanded to include more detailed analysis of bone, as well as soft tissues, by use of various contrast agents. It is increasingly applied to questions in developmental biology and developmental toxicology. Relatively high-throughput protocols now provide a powerful and efficient means to evaluate embryos and fetuses subjected to genetic manipulations or chemical exposures. This review provides an overview of the technology, including scanning, reconstruction, visualization, segmentation, and analysis of micro-CT generated images. This is followed by a review of more recent applications of the technology in some common laboratory species that highlight the diverse issues that can be addressed. Copyright © 2013 Wiley Periodicals, Inc.

  13. Quantum annealing versus classical machine learning applied to a simplified computational biology problem

    Science.gov (United States)

    Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

    2018-03-01

    Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

  14. Computing health quality measures using Informatics for Integrating Biology and the Bedside.

    Science.gov (United States)

    Klann, Jeffrey G; Murphy, Shawn N

    2013-04-19

    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. 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. 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. 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. 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 health. However, its current form might allow

  15. COMODI: an ontology to characterise differences in versions of computational models in biology.

    Science.gov (United States)

    Scharm, Martin; Waltemath, Dagmar; Mendes, Pedro; Wolkenhauer, Olaf

    2016-07-11

    Open model repositories provide ready-to-reuse computational models of biological systems. Models within those repositories evolve over time, leading to different model versions. Taken together, the underlying changes reflect a model's provenance and thus can give valuable insights into the studied biology. Currently, however, changes cannot be semantically interpreted. To improve this situation, we developed an ontology of terms describing changes in models. The ontology can be used by scientists and within software to characterise model updates at the level of single changes. When studying or reusing a model, these annotations help with determining the relevance of a change in a given context. We manually studied changes in selected models from BioModels and the Physiome Model Repository. Using the BiVeS tool for difference detection, we then performed an automatic analysis of changes in all models published in these repositories. The resulting set of concepts led us to define candidate terms for the ontology. In a final step, we aggregated and classified these terms and built the first version of the ontology. We present COMODI, an ontology needed because COmputational MOdels DIffer. It empowers users and software to describe changes in a model on the semantic level. COMODI also enables software to implement user-specific filter options for the display of model changes. Finally, COMODI is a step towards predicting how a change in a model influences the simulation results. COMODI, coupled with our algorithm for difference detection, ensures the transparency of a model's evolution, and it enhances the traceability of updates and error corrections. COMODI is encoded in OWL. It is openly available at http://comodi.sems.uni-rostock.de/ .

  16. Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications.

    Science.gov (United States)

    Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Maudsley, Stuart

    2013-01-01

    Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

  17. Ab initio computational study of vincristine as a biological active compound: NMR and NBO analyses

    Directory of Open Access Journals (Sweden)

    Shiva Joohari

    2015-06-01

    Full Text Available Vincristine is a biological active alkaloid that has been used clinically against a variety of neoplasms. In the current study we have theoretically investigated the magnetic properties of titled compound to predict physical and chemical properties of vincristine as a biological inhibitor. Ab initio computation using HF and B3LYP with 3-21G(d and 6-31G(d level of theory have been performed and then magnetic shielding tensor (, ppm, shielding asymmetry (, magnetic shielding anisotropy (aniso, ppm, the skew of a tensor (K, chemical shift anisotropy ( and chemical shift ( were calculated to indicate the details of the interaction mechanism between microtubules and vincristine. Moreover, EHOMO, ELUMO and Ebg were evaluated. The maximum and minimum values of Ebg were found in HF/3-21g and B3LYP/3-21g respectively. It was also uggested that O24, O37, O49 and O55 with minimum values of iso, are active sites of titled compound. Furthermore the calculated chemical shifts were compared with experimental data in DMSO and CDCl3 solvents.

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

    Energy Technology Data Exchange (ETDEWEB)

    Baldi, P. [California Inst. of Tech., Pasadena, CA (United States)

    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.

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

    Science.gov (United States)

    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.

  20. A comparative analysis on computational methods for fitting an ERGM to biological network data

    Directory of Open Access Journals (Sweden)

    Sudipta Saha

    2015-03-01

    Full Text Available Exponential random graph models (ERGM based on graph theory are useful in studying global biological network structure using its local properties. However, computational methods for fitting such models are sensitive to the type, structure and the number of the local features of a network under study. In this paper, we compared computational methods for fitting an ERGM with local features of different types and structures. Two commonly used methods, such as the Markov Chain Monte Carlo Maximum Likelihood Estimation and the Maximum Pseudo Likelihood Estimation are considered for estimating the coefficients of network attributes. We compared the estimates of observed network to our random simulated network using both methods under ERGM. The motivation was to ascertain the extent to which an observed network would deviate from a randomly simulated network if the physical numbers of attributes were approximately same. Cut-off points of some common attributes of interest for different order of nodes were determined through simulations. We implemented our method to a known regulatory network database of Escherichia coli (E. coli.

  1. Computer simulation of induced electric currents and fields in biological bodies by 60 Hz magnetic fields

    International Nuclear Information System (INIS)

    Xi Weiguo; Stuchly, M.A.; Gandhi, O.P.

    1993-01-01

    Possible health effects of human exposure to 60 Hz magnetic fields are a subject of increasing concern. An understanding of the coupling of electromagnetic fields to human body tissues is essential for assessment of their biological effects. A method is presented for the computerized simulation of induced electric currents and fields in bodies of men and rodents from power-line frequency magnetic fields. In the impedance method, the body is represented by a 3 dimensional impedance network. The computational model consists of several tens of thousands of cubic numerical cells and thus represented a realistic shape. The modelling for humans is performed with two models, a heterogeneous model based on cross-section anatomy and a homogeneous one using an average tissue conductivity. A summary of computed results of induced electric currents and fields is presented. It is confirmed that induced currents are lower than endangerous current levels for most environmental exposures. However, the induced current density varies greatly, with the maximum being at least 10 times larger than the average. This difference is likely to be greater when more detailed anatomy and morphology are considered. 15 refs., 2 figs., 1 tab

  2. CoreFlow: a computational platform for integration, analysis and modeling of complex biological data.

    Science.gov (United States)

    Pasculescu, Adrian; Schoof, Erwin M; Creixell, Pau; Zheng, Yong; Olhovsky, Marina; Tian, Ruijun; So, Jonathan; Vanderlaan, Rachel D; Pawson, Tony; Linding, Rune; Colwill, Karen

    2014-04-04

    A major challenge in mass spectrometry and other large-scale applications is how to handle, integrate, and model the data that is produced. Given the speed at which technology advances and the need to keep pace with biological experiments, we designed a computational platform, CoreFlow, which provides programmers with a framework to manage data in real-time. It allows users to upload data into a relational database (MySQL), and to create custom scripts in high-level languages such as R, Python, or Perl for processing, correcting and modeling this data. CoreFlow organizes these scripts into project-specific pipelines, tracks interdependencies between related tasks, and enables the generation of summary reports as well as publication-quality images. As a result, the gap between experimental and computational components of a typical large-scale biology project is reduced, decreasing the time between data generation, analysis and manuscript writing. CoreFlow is being released to the scientific community as an open-sourced software package complete with proteomics-specific examples, which include corrections for incomplete isotopic labeling of peptides (SILAC) or arginine-to-proline conversion, and modeling of multiple/selected reaction monitoring (MRM/SRM) results. CoreFlow was purposely designed as an environment for programmers to rapidly perform data analysis. These analyses are assembled into project-specific workflows that are readily shared with biologists to guide the next stages of experimentation. Its simple yet powerful interface provides a structure where scripts can be written and tested virtually simultaneously to shorten the life cycle of code development for a particular task. The scripts are exposed at every step so that a user can quickly see the relationships between the data, the assumptions that have been made, and the manipulations that have been performed. Since the scripts use commonly available programming languages, they can easily be

  3. Birth/birth-death processes and their computable transition probabilities with biological applications.

    Science.gov (United States)

    Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

    2018-03-01

    Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.

  4. Community-driven development for computational biology at Sprints, Hackathons and Codefests.

    Science.gov (United States)

    Möller, Steffen; Afgan, Enis; Banck, Michael; Bonnal, Raoul J P; Booth, Timothy; Chilton, John; Cock, Peter J A; Gumbel, Markus; Harris, Nomi; Holland, Richard; Kalaš, Matúš; Kaján, László; Kibukawa, Eri; Powel, David R; Prins, Pjotr; Quinn, Jacqueline; Sallou, Olivier; Strozzi, Francesco; Seemann, Torsten; Sloggett, Clare; Soiland-Reyes, Stian; Spooner, William; Steinbiss, Sascha; Tille, Andreas; Travis, Anthony J; Guimera, Roman; Katayama, Toshiaki; Chapman, Brad A

    2014-01-01

    Computational biology comprises a wide range of technologies and approaches. Multiple technologies can be combined to create more powerful workflows if the individuals contributing the data or providing tools for its interpretation can find mutual understanding and consensus. Much conversation and joint investigation are required in order to identify and implement the best approaches. Traditionally, scientific conferences feature talks presenting novel technologies or insights, followed up by informal discussions during coffee breaks. In multi-institution collaborations, in order to reach agreement on implementation details or to transfer deeper insights in a technology and practical skills, a representative of one group typically visits the other. However, this does not scale well when the number of technologies or research groups is large. Conferences have responded to this issue by introducing Birds-of-a-Feather (BoF) sessions, which offer an opportunity for individuals with common interests to intensify their interaction. However, parallel BoF sessions often make it hard for participants to join multiple BoFs and find common ground between the different technologies, and BoFs are generally too short to allow time for participants to program together. This report summarises our experience with computational biology Codefests, Hackathons and Sprints, which are interactive developer meetings. They are structured to reduce the limitations of traditional scientific meetings described above by strengthening the interaction among peers and letting the participants determine the schedule and topics. These meetings are commonly run as loosely scheduled "unconferences" (self-organized identification of participants and topics for meetings) over at least two days, with early introductory talks to welcome and organize contributors, followed by intensive collaborative coding sessions. We summarise some prominent achievements of those meetings and describe differences in how

  5. Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

    Science.gov (United States)

    Ma, Zhanshan (Sam)

    In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three

  6. Development of a computational system for management of risks in radiosterilization processes of biological tissues

    International Nuclear Information System (INIS)

    Montoya, Cynara Viterbo

    2009-01-01

    Risk management can be understood to be a systematic management which aims to identify record and control the risks of a process. Applying risk management becomes a complex activity, due to the variety of professionals involved. In order to execute risk management the following are requirements of paramount importance: the experience, discernment and judgment of a multidisciplinary team, guided by means of quality tools, so as to provide standardization in the process of investigating the cause and effects of risks and dynamism in obtaining the objective desired, i.e. the reduction and control of the risk. This work aims to develop a computational system of risk management (software) which makes it feasible to diagnose the risks of the processes of radiosterilization of biological tissues. The methodology adopted was action-research, according to which the researcher performs an active role in the establishment of the problems found, in the follow-up and in the evaluation of the actions taken owing to the problems. The scenario of this action-research was the Laboratory of Biological Tissues (LTB) in the Radiation Technology Center IPEN/CNEN-SP - Sao Paulo/Brazil. The software developed was executed in PHP and Flash/MySQL language, the server (hosting), the software is available on the Internet (www.vcrisk.com.br), which the user can access from anywhere by means of the login/access password previously sent by email to the team responsible for the tissue to be analyzed. The software presents friendly navigability whereby the user is directed step-by-step in the process of investigating the risk up to the means of reducing it. The software 'makes' the user comply with the term and present the effectiveness of the actions taken to reduce the risk. Applying this system provided the organization (LTB/CTR/IPEN) with dynamic communication, effective between the members of the multidisciplinary team: a) in decision-making; b) in lessons learned; c) in knowing the new risk

  7. Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.

    Science.gov (United States)

    Waltemath, Dagmar; Adams, Richard; Bergmann, Frank T; Hucka, Michael; Kolpakov, Fedor; Miller, Andrew K; Moraru, Ion I; Nickerson, David; Sahle, Sven; Snoep, Jacky L; Le Novère, Nicolas

    2011-12-15

    The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools. In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions. With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research

  8. Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language

    Science.gov (United States)

    2011-01-01

    Background The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools. Results In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions. Conclusions With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from

  9. Report from the 2nd Summer School in Computational Biology organized by the Queen's University of Belfast

    Directory of Open Access Journals (Sweden)

    Frank Emmert-Streib

    2014-12-01

    Full Text Available In this paper, we present a meeting report for the 2nd Summer School in Computational Biology organized by the Queen's University of Belfast. We describe the organization of the summer school, its underlying concept and student feedback we received after the completion of the summer school.

  10. From Levy to Brownian: a computational model based on biological fluctuation.

    Directory of Open Access Journals (Sweden)

    Surya G Nurzaman

    Full Text Available BACKGROUND: Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. METHODOLOGY/PRINCIPAL FINDINGS: We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. CONCLUSIONS/SIGNIFICANCE: Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

  11. From Lévy to Brownian: a computational model based on biological fluctuation.

    Science.gov (United States)

    Nurzaman, Surya G; Matsumoto, Yoshio; Nakamura, Yutaka; Shirai, Kazumichi; Koizumi, Satoshi; Ishiguro, Hiroshi

    2011-02-03

    Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

  12. Machine learning in computational biology to accelerate high-throughput protein expression.

    Science.gov (United States)

    Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

    2017-08-15

    The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

    Science.gov (United States)

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

    2012-05-04

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

  14. The secondary metabolite bioinformatics portal: Computational tools to facilitate synthetic biology of secondary metabolite production

    Directory of Open Access Journals (Sweden)

    Tilmann Weber

    2016-06-01

    Full Text Available Natural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http://www.secondarymetabolites.org is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field.

  15. The Robotic Scientist: Distilling Natural Laws from Experimental Data, from Cognitive Robotics to Computational Biology

    Energy Technology Data Exchange (ETDEWEB)

    Lipson, Hod [Cornell University

    2011-10-25

    Can machines discover analytical laws automatically? For centuries, scientists have attempted to identify and document analytical laws that underlie physical phenomena in nature. Despite the prevalence of computing power, the process of finding natural laws and their corresponding equations has resisted automation. A key challenge to finding analytic relations automatically is defining algorithmically what makes a correlation in observed data important and insightful. By seeking dynamical invariants and symmetries, we show how we can go from finding just predictive models to finding deeper conservation laws. We demonstrated this approach by automatically searching motion-tracking data captured from various physical systems, ranging from simple harmonic oscillators to chaotic double-pendula. Without any prior knowledge about physics, kinematics, or geometry, the algorithm discovered Hamiltonians, Lagrangians, and other laws of geometric and momentum conservation. The discovery rate accelerated as laws found for simpler systems were used to bootstrap explanations for more complex systems, gradually uncovering the “alphabet” used to describe those systems. Application to modeling physical and biological systems will be shown.

  16. The nature and use of prediction skills in a biological computer simulation

    Science.gov (United States)

    Lavoie, Derrick R.; Good, Ron

    The primary goal of this study was to examine the science process skill of prediction using qualitative research methodology. The think-aloud interview, modeled after Ericsson and Simon (1984), let to the identification of 63 program exploration and prediction behaviors.The performance of seven formal and seven concrete operational high-school biology students were videotaped during a three-phase learning sequence on water pollution. Subjects explored the effects of five independent variables on two dependent variables over time using a computer-simulation program. Predictions were made concerning the effect of the independent variables upon dependent variables through time. Subjects were identified according to initial knowledge of the subject matter and success at solving three selected prediction problems.Successful predictors generally had high initial knowledge of the subject matter and were formal operational. Unsuccessful predictors generally had low initial knowledge and were concrete operational. High initial knowledge seemed to be more important to predictive success than stage of Piagetian cognitive development.Successful prediction behaviors involved systematic manipulation of the independent variables, note taking, identification and use of appropriate independent-dependent variable relationships, high interest and motivation, and in general, higher-level thinking skills. Behaviors characteristic of unsuccessful predictors were nonsystematic manipulation of independent variables, lack of motivation and persistence, misconceptions, and the identification and use of inappropriate independent-dependent variable relationships.

  17. Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

    Science.gov (United States)

    Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

    2018-01-01

    Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

  18. COMPUTATIONAL MODELING AND SIMULATION IN BIOLOGY TEACHING: A MINIMALLY EXPLORED FIELD OF STUDY WITH A LOT OF POTENTIAL

    Directory of Open Access Journals (Sweden)

    Sonia López

    2016-09-01

    Full Text Available This study is part of a research project that aims to characterize the epistemological, psychological and didactic presuppositions of science teachers (Biology, Physics, Chemistry that implement Computational Modeling and Simulation (CMS activities as a part of their teaching practice. We present here a synthesis of a literature review on the subject, evidencing how in the last two decades this form of computer usage for science teaching has boomed in disciplines such as Physics and Chemistry, but in a lesser degree in Biology. Additionally, in the works that dwell on the use of CMS in Biology, we identified a lack of theoretical bases that support their epistemological, psychological and/or didactic postures. Accordingly, this generates significant considerations for the fields of research and teacher instruction in Science Education.

  19. An algorithm to detect and communicate the differences in computational models describing biological systems.

    Science.gov (United States)

    Scharm, Martin; Wolkenhauer, Olaf; Waltemath, Dagmar

    2016-02-15

    Repositories support the reuse of models and ensure transparency about results in publications linked to those models. With thousands of models available in repositories, such as the BioModels database or the Physiome Model Repository, a framework to track the differences between models and their versions is essential to compare and combine models. Difference detection not only allows users to study the history of models but also helps in the detection of errors and inconsistencies. Existing repositories lack algorithms to track a model's development over time. Focusing on SBML and CellML, we present an algorithm to accurately detect and describe differences between coexisting versions of a model with respect to (i) the models' encoding, (ii) the structure of biological networks and (iii) mathematical expressions. This algorithm is implemented in a comprehensive and open source library called BiVeS. BiVeS helps to identify and characterize changes in computational models and thereby contributes to the documentation of a model's history. Our work facilitates the reuse and extension of existing models and supports collaborative modelling. Finally, it contributes to better reproducibility of modelling results and to the challenge of model provenance. The workflow described in this article is implemented in BiVeS. BiVeS is freely available as source code and binary from sems.uni-rostock.de. The web interface BudHat demonstrates the capabilities of BiVeS at budhat.sems.uni-rostock.de. © The Author 2015. Published by Oxford University Press.

  20. Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

    Science.gov (United States)

    Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

    2017-01-01

    Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

  1. 16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Haqiq, Abdelkrim; Alimi, Adel; Mezzour, Ghita; Rokbani, Nizar; Muda, Azah

    2017-01-01

    This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

  2. Enhancing Lecture Presentations in Introductory Biology with Computer-Based Multimedia.

    Science.gov (United States)

    Fifield, Steve; Peifer, Rick

    1994-01-01

    Uses illustrations and text to discuss convenient ways to organize and present computer-based multimedia to students in lecture classes. Includes the following topics: (1) Effects of illustrations on learning; (2) Using computer-based illustrations in lecture; (3) MacPresents-Multimedia Presentation Software; (4) Advantages of computer-based…

  3. Technical Development and Application of Soft Computing in Agricultural and Biological Engineering

    Science.gov (United States)

    Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

  4. Development of Soft Computing and Applications in Agricultural and Biological Engineering

    Science.gov (United States)

    Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and...

  5. Computational biology approaches to plant metabolism and photosynthesis: applications for corals in times of climate change and environmental stress.

    Science.gov (United States)

    Crabbe, M James C

    2010-08-01

    Knowledge of factors that are important in reef resilience helps us to understand how reef ecosystems react following major anthropogenic and environmental disturbances. The symbiotic relationship between the photosynthetic zooxanthellae algal cells and corals is that the zooxanthellae provide the coral with carbon, while the coral provides protection and access to enough light for the zooxanthellae to photosynthesise. This article reviews some recent advances in computational biology relevant to photosynthetic organisms, including Beyesian approaches to kinetics, computational methods for flux balances in metabolic processes, and determination of clades of zooxanthallae. Application of these systems will be important in the conservation of coral reefs in times of climate change and environmental stress.

  6. Creation of computer system for simulation nanoparticles interaction with biological objects concept

    International Nuclear Information System (INIS)

    Sarana, Yu.V.; Smol'nik, N.S.; Mel'nov, S.B.

    2014-01-01

    Main problem of nanotoxicology is that biological effects of most nanoparticles are unknown. So creation of system predictioning nanoparticles biological activity spectra is a great challenge. Here we give a concept of such system creation; it includes 6 stages realization of which help to implement nanotechnology most safely and effectively. (authors)

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

    Science.gov (United States)

    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.

  8. The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right.

    Science.gov (United States)

    Audie, J; Boyd, C

    2010-01-01

    The case for peptide-based drugs is compelling. Due to their chemical, physical and conformational diversity, and relatively unproblematic toxicity and immunogenicity, peptides represent excellent starting material for drug discovery. Nature has solved many physiological and pharmacological problems through the use of peptides, polypeptides and proteins. If nature could solve such a diversity of challenging biological problems through the use of peptides, it seems reasonable to infer that human ingenuity will prove even more successful. And this, indeed, appears to be the case, as a number of scientific and methodological advances are making peptides and peptide-based compounds ever more promising pharmacological agents. Chief among these advances are powerful chemical and biological screening technologies for lead identification and optimization, methods for enhancing peptide in vivo stability, bioavailability and cell-permeability, and new delivery technologies. Other advances include the development and experimental validation of robust computational methods for peptide lead identification and optimization. Finally, scientific analysis, biology and chemistry indicate the prospect of designing relatively small peptides to therapeutically modulate so-called 'undruggable' protein-protein interactions. Taken together a clear picture is emerging: through the synergistic use of the scientific imagination and the computational, chemical and biological methods that are currently available, effective peptide therapeutics for novel targets can be designed that surpass even the proven peptidic designs of nature.

  9. Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials

    International Nuclear Information System (INIS)

    Winkler, David A.

    2016-01-01

    Nanomaterials research is one of the fastest growing contemporary research areas. The unprecedented properties of these materials have meant that they are being incorporated into products very quickly. Regulatory agencies are concerned they cannot assess the potential hazards of these materials adequately, as data on the biological properties of nanomaterials are still relatively limited and expensive to acquire. Computational modelling methods have much to offer in helping understand the mechanisms by which toxicity may occur, and in predicting the likelihood of adverse biological impacts of materials not yet tested experimentally. This paper reviews the progress these methods, particularly those QSAR-based, have made in understanding and predicting potentially adverse biological effects of nanomaterials, and also the limitations and pitfalls of these methods. - Highlights: • Nanomaterials regulators need good information to make good decisions. • Nanomaterials and their interactions with biology are very complex. • Computational methods use existing data to predict properties of new nanomaterials. • Statistical, data driven modelling methods have been successfully applied to this task. • Much more must be learnt before robust toolkits will be widely usable by regulators.

  10. S100A4 and its role in metastasis – computational integration of data on biological networks.

    Science.gov (United States)

    Buetti-Dinh, Antoine; Pivkin, Igor V; Friedman, Ran

    2015-08-01

    Characterising signal transduction networks is fundamental to our understanding of biology. However, redundancy and different types of feedback mechanisms make it difficult to understand how variations of the network components contribute to a biological process. In silico modelling of signalling interactions therefore becomes increasingly useful for the development of successful therapeutic approaches. Unfortunately, quantitative information cannot be obtained for all of the proteins or complexes that comprise the network, which limits the usability of computational models. We developed a flexible computational framework for the analysis of biological signalling networks. We demonstrate our approach by studying the mechanism of metastasis promotion by the S100A4 protein, and suggest therapeutic strategies. The advantage of the proposed method is that only limited information (interaction type between species) is required to set up a steady-state network model. This permits a straightforward integration of experimental information where the lack of details are compensated by efficient sampling of the parameter space. We investigated regulatory properties of the S100A4 network and the role of different key components. The results show that S100A4 enhances the activity of matrix metalloproteinases (MMPs), causing higher cell dissociation. Moreover, it leads to an increased stability of the pathological state. Thus, avoiding metastasis in S100A4-expressing tumours requires multiple target inhibition. Moreover, the analysis could explain the previous failure of MMP inhibitors in clinical trials. Finally, our method is applicable to a wide range of biological questions that can be represented as directional networks.

  11. G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

    Science.gov (United States)

    Lee, Hui Sun; Im, Wonpil

    2016-04-01

    Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

  12. An introduction to the mathematics of biology with computer algebra models

    CERN Document Server

    Yeargers, Edward K; Herod, James V

    1996-01-01

    Biology is a source of fascination for most scientists, whether their training is in the life sciences or not. In particular, there is a special satisfaction in discovering an understanding of biology in the context of another science like mathematics. Fortunately there are plenty of interesting (and fun) problems in biology, and virtually all scientific disciplines have become the richer for it. For example, two major journals, Mathematical Biosciences and Journal of Mathematical Biology, have tripled in size since their inceptions 20-25 years ago. The various sciences have a great deal to give to one another, but there are still too many fences separating them. In writing this book we have adopted the philosophy that mathematical biology is not merely the intrusion of one science into another, but has a unity of its own, in which both the biology and the math­ ematics should be equal and complete, and should flow smoothly into and out of one another. We have taught mathematical biology with this philosophy...

  13. The use of computer in the biological dosimetry of radiation injury with lymphocyte micronucleus

    International Nuclear Information System (INIS)

    Jiang Benrong; Yao Buo

    1994-01-01

    A new approach for determining by computer the radiation dosage in early diagnosis of radiation injury was presented, with a purpose to widen its practical application. A set of programs designed in Clanguage for computing and drawing was compiled. The technical details discussed here can be used for compiling other kinds of practical programs. It is a valuable attempt in improving the efficiency of the computer-aid clinical diagnosis

  14. High Performance Computing and Storage Requirements for Biological and Environmental Research Target 2017

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Wasserman, Harvey [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

    2013-05-01

    The National Energy Research Scientific Computing Center (NERSC) is the primary computing center for the DOE Office of Science, serving approximately 4,500 users working on some 650 projects that involve nearly 600 codes in a wide variety of scientific disciplines. In addition to large-­scale computing and storage resources NERSC provides support and expertise that help scientists make efficient use of its systems. The latest review revealed several key requirements, in addition to achieving its goal of characterizing BER computing and storage needs.

  15. Documenting and predicting topic changes in Computers in Biology and Medicine: A bibliometric keyword analysis from 1990 to 2017

    Directory of Open Access Journals (Sweden)

    Oliver Faust

    Full Text Available The Computers in Biology and Medicine (CBM journal promotes the use of computing machinery in the fields of bioscience and medicine. Since the first volume in 1970, the importance of computers in these fields has grown dramatically, this is evident in the diversification of topics and an increase in the publication rate. In this study, we quantify both change and diversification of topics covered in. This is done by analysing the author supplied keywords, since they were electronically captured in 1990. The analysis starts by selecting 40 keywords, related to Medical (M (7, Data (D (10, Feature (F (17 and (AI (6 methods. Automated keyword clustering shows the statistical connection between the selected keywords. We found that the three most popular topics in CBM are: Support Vector Machine (SVM, Electroencephalography (EEG and IMAGE PROCESSING. In a separate analysis step, we bagged the selected keywords into sequential one year time slices and calculated the normalized appearance. The results were visualised with graphs that indicate the CBM topic changes. These graphs show that there was a transition from Artificial Neural Network (ANN to SVM. In 2006 SVM replaced ANN as the most important AI algorithm. Our investigation helps the editorial board to manage and embrace topic change. Furthermore, our analysis is interesting for the general reader, as the results can help them to adjust their research directions. Keywords: Research trends, Topic analysis, Topic detection and tracking, Text mining, Computers in biology and medicine

  16. Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

    CERN Document Server

    Pisharady, Pramod Kumar; Poh, Loh Ai

    2014-01-01

    This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

  17. Computation of fields in an arbitrarily shaped heterogeneous dielectric or biological body by an iterative conjugate gradient method

    International Nuclear Information System (INIS)

    Wang, J.J.H.; Dubberley, J.R.

    1989-01-01

    Electromagnetic (EM) fields in a three-dimensional, arbitrarily shaped heterogeneous dielectric or biological body illuminated by a plane wave are computed by an iterative conjugate gradient method. The method is a generalized method of moments applied to the volume integral equation. Because no matrix is explicitly involved or stored, the present iterative method is capable of computing EM fields in objects an order of magnitude larger than those that can be handled by the conventional method of moments. Excellent numerical convergence is achieved. Perfect convergence to the result of the conventional moment method using the same basis and weighted with delta functions is consistently achieved in all the cases computed, indicating that these two algorithms (direct and interactive) are equivalent

  18. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, Daniel D. [Integrative Genetics and Genomics, University of California Davis, Davis, CA (United States); Department of Biomedical Engineering, University of California Davis, Davis, CA (United States); Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng, E-mail: cmtan@ucdavis.edu [Department of Biomedical Engineering, University of California Davis, Davis, CA (United States)

    2014-12-09

    As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  19. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    International Nuclear Information System (INIS)

    Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

    2014-01-01

    As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  20. G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

    Science.gov (United States)

    2016-01-01

    Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

  1. Medical and biological and ergonomic aspects of security of personal computer users

    Directory of Open Access Journals (Sweden)

    Н.Б. Римар-Щербина

    2008-03-01

    Full Text Available  In this review article having experiment of decrease of the bad electromagnetic fields influence on the personnel computers customers organism is summed with the help of technical equipment.

  2. Continuous development of schemes for parallel computing of the electrostatics in biological systems: implementation in DelPhi.

    Science.gov (United States)

    Li, Chuan; Petukh, Marharyta; Li, Lin; Alexov, Emil

    2013-08-15

    Due to the enormous importance of electrostatics in molecular biology, calculating the electrostatic potential and corresponding energies has become a standard computational approach for the study of biomolecules and nano-objects immersed in water and salt phase or other media. However, the electrostatics of large macromolecules and macromolecular complexes, including nano-objects, may not be obtainable via explicit methods and even the standard continuum electrostatics methods may not be applicable due to high computational time and memory requirements. Here, we report further development of the parallelization scheme reported in our previous work (Li, et al., J. Comput. Chem. 2012, 33, 1960) to include parallelization of the molecular surface and energy calculations components of the algorithm. The parallelization scheme utilizes different approaches such as space domain parallelization, algorithmic parallelization, multithreading, and task scheduling, depending on the quantity being calculated. This allows for efficient use of the computing resources of the corresponding computer cluster. The parallelization scheme is implemented in the popular software DelPhi and results in speedup of several folds. As a demonstration of the efficiency and capability of this methodology, the electrostatic potential, and electric field distributions are calculated for the bovine mitochondrial supercomplex illustrating their complex topology, which cannot be obtained by modeling the supercomplex components alone. Copyright © 2013 Wiley Periodicals, Inc.

  3. Gradient matching methods for computational inference in mechanistic models for systems biology: a review and comparative analysis

    Directory of Open Access Journals (Sweden)

    Benn eMacdonald

    2015-11-01

    Full Text Available Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs, is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimised so as to minimise some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data.

  4. Quantitative computational models of molecular self-assembly in systems biology.

    Science.gov (United States)

    Thomas, Marcus; Schwartz, Russell

    2017-05-23

    Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

  5. A Reconfigurable and Biologically Inspired Paradigm for Computation Using Network-On-Chip and Spiking Neural Networks

    Directory of Open Access Journals (Sweden)

    Jim Harkin

    2009-01-01

    Full Text Available FPGA devices have emerged as a popular platform for the rapid prototyping of biological Spiking Neural Networks (SNNs applications, offering the key requirement of reconfigurability. However, FPGAs do not efficiently realise the biologically plausible neuron and synaptic models of SNNs, and current FPGA routing structures cannot accommodate the high levels of interneuron connectivity inherent in complex SNNs. This paper highlights and discusses the current challenges of implementing scalable SNNs on reconfigurable FPGAs. The paper proposes a novel field programmable neural network architecture (EMBRACE, incorporating low-power analogue spiking neurons, interconnected using a Network-on-Chip architecture. Results on the evaluation of the EMBRACE architecture using the XOR benchmark problem are presented, and the performance of the architecture is discussed. The paper also discusses the adaptability of the EMBRACE architecture in supporting fault tolerant computing.

  6. Phase-contrast x-ray computed tomography for observing biological specimens and organic materials

    Science.gov (United States)

    Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

    1995-02-01

    A novel three-dimensional x-ray imaging method has been developed by combining a phase-contrast x-ray imaging technique with x-ray computed tomography. This phase-contrast x-ray computed tomography (PCX-CT) provides sectional images of organic specimens that would produce absorption-contrast x-ray CT images with little contrast. Comparing PCX-CT images of rat cerebellum and cancerous rabbit liver specimens with corresponding absorption-contrast CT images shows that PCX-CT is much more sensitive to the internal structure of organic specimens.

  7. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    Directory of Open Access Journals (Sweden)

    Daniel eLewis

    2014-12-01

    Full Text Available As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo systems, with only a few examples of prominent work done on predicting the dynamics of cell-free systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  8. Recent advances in modeling languages for pathway maps and computable biological networks.

    Science.gov (United States)

    Slater, Ted

    2014-02-01

    As our theories of systems biology grow more sophisticated, the models we use to represent them become larger and more complex. Languages necessarily have the expressivity and flexibility required to represent these models in ways that support high-resolution annotation, and provide for simulation and analysis that are sophisticated enough to allow researchers to master their data in the proper context. These languages also need to facilitate model sharing and collaboration, which is currently best done by using uniform data structures (such as graphs) and language standards. In this brief review, we discuss three of the most recent systems biology modeling languages to appear: BEL, PySB and BCML, and examine how they meet these needs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Biological substantiation of antipsychotic-associated pneumonia: Systematic literature review and computational analyses.

    Science.gov (United States)

    Sultana, Janet; Calabró, Marco; Garcia-Serna, Ricard; Ferrajolo, Carmen; Crisafulli, Concetta; Mestres, Jordi; Trifirò', Gianluca

    2017-01-01

    Antipsychotic (AP) safety has been widely investigated. However, mechanisms underlying AP-associated pneumonia are not well-defined. The aim of this study was to investigate the known mechanisms of AP-associated pneumonia through a systematic literature review, confirm these mechanisms using an independent data source on drug targets and attempt to identify novel AP drug targets potentially linked to pneumonia. A search was conducted in Medline and Web of Science to identify studies exploring the association between pneumonia and antipsychotic use, from which information on hypothesized mechanism of action was extracted. All studies had to be in English and had to concern AP use as an intervention in persons of any age and for any indication, provided that the outcome was pneumonia. Information on the study design, population, exposure, outcome, risk estimate and mechanism of action was tabulated. Public repositories of pharmacology and drug safety data were used to identify the receptor binding profile and AP safety events. Cytoscape was then used to map biological pathways that could link AP targets and off-targets to pneumonia. The literature search yielded 200 articles; 41 were included in the review. Thirty studies reported a hypothesized mechanism of action, most commonly activation/inhibition of cholinergic, histaminergic and dopaminergic receptors. In vitro pharmacology data confirmed receptor affinities identified in the literature review. Two targets, thromboxane A2 receptor (TBXA2R) and platelet activating factor receptor (PTAFR) were found to be novel AP target receptors potentially associated with pneumonia. Biological pathways constructed using Cytoscape identified plausible biological links potentially leading to pneumonia downstream of TBXA2R and PTAFR. Innovative approaches for biological substantiation of drug-adverse event associations may strengthen evidence on drug safety profiles and help to tailor pharmacological therapies to patient risk

  10. Face to Face In-vitro to In-silico – How Computers are Arming Biology!

    Indian Academy of Sciences (India)

    ment of novel computational methods to understand the structure and functions of .... to pairwise alignment (the query is aligned only to the best match in the database), where the ... Andrej Sali, while he was a doctorate student at Prof. Sir Tom ...

  11. Combined Model of Intrinsic and Extrinsic Variability for Computational Network Design with Application to Synthetic Biology

    Science.gov (United States)

    Toni, Tina; Tidor, Bruce

    2013-01-01

    Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady

  12. Computer-Based Support of Decision Making Processes during Biological Incidents

    Directory of Open Access Journals (Sweden)

    Karel Antos

    2010-04-01

    Full Text Available The paper describes contextual analysis of a general system that should provide a computerized support of decision making processes related to response operations in case of a biological incident. This analysis is focused on information systems and information resources perspective and their integration using appropriate tools and technology. In the contextual design the basic modules of BioDSS system are suggested and further elaborated. The modules deal with incident description, scenarios development and recommendation of appropriate countermeasures. Proposals for further research are also included.

  13. Pushing the frontiers of first-principles based computer simulations of chemical and biological systems.

    Science.gov (United States)

    Brunk, Elizabeth; Ashari, Negar; Athri, Prashanth; Campomanes, Pablo; de Carvalho, F Franco; Curchod, Basile F E; Diamantis, Polydefkis; Doemer, Manuel; Garrec, Julian; Laktionov, Andrey; Micciarelli, Marco; Neri, Marilisa; Palermo, Giulia; Penfold, Thomas J; Vanni, Stefano; Tavernelli, Ivano; Rothlisberger, Ursula

    2011-01-01

    The Laboratory of Computational Chemistry and Biochemistry is active in the development and application of first-principles based simulations of complex chemical and biochemical phenomena. Here, we review some of our recent efforts in extending these methods to larger systems, longer time scales and increased accuracies. Their versatility is illustrated with a diverse range of applications, ranging from the determination of the gas phase structure of the cyclic decapeptide gramicidin S, to the study of G protein coupled receptors, the interaction of transition metal based anti-cancer agents with protein targets, the mechanism of action of DNA repair enzymes, the role of metal ions in neurodegenerative diseases and the computational design of dye-sensitized solar cells. Many of these projects are done in collaboration with experimental groups from the Institute of Chemical Sciences and Engineering (ISIC) at the EPFL.

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

    OpenAIRE

    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 modificati...

  15. Simulation of biological ion channels with technology computer-aided design.

    Science.gov (United States)

    Pandey, Santosh; Bortei-Doku, Akwete; White, Marvin H

    2007-01-01

    Computer simulations of realistic ion channel structures have always been challenging and a subject of rigorous study. Simulations based on continuum electrostatics have proven to be computationally cheap and reasonably accurate in predicting a channel's behavior. In this paper we discuss the use of a device simulator, SILVACO, to build a solid-state model for KcsA channel and study its steady-state response. SILVACO is a well-established program, typically used by electrical engineers to simulate the process flow and electrical characteristics of solid-state devices. By employing this simulation program, we have presented an alternative computing platform for performing ion channel simulations, besides the known methods of writing codes in programming languages. With the ease of varying the different parameters in the channel's vestibule and the ability of incorporating surface charges, we have shown the wide-ranging possibilities of using a device simulator for ion channel simulations. Our simulated results closely agree with the experimental data, validating our model.

  16. Creating a pipeline of talent for informatics: STEM initiative for high school students in computer science, biology, and biomedical informatics

    Directory of Open Access Journals (Sweden)

    Joyeeta Dutta-Moscato

    2014-01-01

    Full Text Available This editorial provides insights into how informatics can attract highly trained students by involving them in science, technology, engineering, and math (STEM training at the high school level and continuing to provide mentorship and research opportunities through the formative years of their education. Our central premise is that the trajectory necessary to be expert in the emergent fields in front of them requires acceleration at an early time point. Both pathology (and biomedical informatics are new disciplines which would benefit from involvement by students at an early stage of their education. In 2009, Michael T Lotze MD, Kirsten Livesey (then a medical student, now a medical resident at University of Pittsburgh Medical Center (UPMC, Richard Hersheberger, PhD (Currently, Dean at Roswell Park, and Megan Seippel, MS (the administrator launched the University of Pittsburgh Cancer Institute (UPCI Summer Academy to bring high school students for an 8 week summer academy focused on Cancer Biology. Initially, pathology and biomedical informatics were involved only in the classroom component of the UPCI Summer Academy. In 2011, due to popular interest, an informatics track called Computer Science, Biology and Biomedical Informatics (CoSBBI was launched. CoSBBI currently acts as a feeder program for the undergraduate degree program in bioinformatics at the University of Pittsburgh, which is a joint degree offered by the Departments of Biology and Computer Science. We believe training in bioinformatics is the best foundation for students interested in future careers in pathology informatics or biomedical informatics. We describe our approach to the recruitment, training and research mentoring of high school students to create a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics. We emphasize here how mentoring of high school students in pathology informatics and biomedical

  17. Creating a pipeline of talent for informatics: STEM initiative for high school students in computer science, biology, and biomedical informatics.

    Science.gov (United States)

    Dutta-Moscato, Joyeeta; Gopalakrishnan, Vanathi; Lotze, Michael T; Becich, Michael J

    2014-01-01

    This editorial provides insights into how informatics can attract highly trained students by involving them in science, technology, engineering, and math (STEM) training at the high school level and continuing to provide mentorship and research opportunities through the formative years of their education. Our central premise is that the trajectory necessary to be expert in the emergent fields in front of them requires acceleration at an early time point. Both pathology (and biomedical) informatics are new disciplines which would benefit from involvement by students at an early stage of their education. In 2009, Michael T Lotze MD, Kirsten Livesey (then a medical student, now a medical resident at University of Pittsburgh Medical Center (UPMC)), Richard Hersheberger, PhD (Currently, Dean at Roswell Park), and Megan Seippel, MS (the administrator) launched the University of Pittsburgh Cancer Institute (UPCI) Summer Academy to bring high school students for an 8 week summer academy focused on Cancer Biology. Initially, pathology and biomedical informatics were involved only in the classroom component of the UPCI Summer Academy. In 2011, due to popular interest, an informatics track called Computer Science, Biology and Biomedical Informatics (CoSBBI) was launched. CoSBBI currently acts as a feeder program for the undergraduate degree program in bioinformatics at the University of Pittsburgh, which is a joint degree offered by the Departments of Biology and Computer Science. We believe training in bioinformatics is the best foundation for students interested in future careers in pathology informatics or biomedical informatics. We describe our approach to the recruitment, training and research mentoring of high school students to create a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics. We emphasize here how mentoring of high school students in pathology informatics and biomedical informatics

  18. SWIM: a computational tool to unveiling crucial nodes in complex biological networks.

    Science.gov (United States)

    Paci, Paola; Colombo, Teresa; Fiscon, Giulia; Gurtner, Aymone; Pavesi, Giulio; Farina, Lorenzo

    2017-03-20

    SWItchMiner (SWIM) is a wizard-like software implementation of a procedure, previously described, able to extract information contained in complex networks. Specifically, SWIM allows unearthing the existence of a new class of hubs, called "fight-club hubs", characterized by a marked negative correlation with their first nearest neighbors. Among them, a special subset of genes, called "switch genes", appears to be characterized by an unusual pattern of intra- and inter-module connections that confers them a crucial topological role, interestingly mirrored by the evidence of their clinic-biological relevance. Here, we applied SWIM to a large panel of cancer datasets from The Cancer Genome Atlas, in order to highlight switch genes that could be critically associated with the drastic changes in the physiological state of cells or tissues induced by the cancer development. We discovered that switch genes are found in all cancers we studied and they encompass protein coding genes and non-coding RNAs, recovering many known key cancer players but also many new potential biomarkers not yet characterized in cancer context. Furthermore, SWIM is amenable to detect switch genes in different organisms and cell conditions, with the potential to uncover important players in biologically relevant scenarios, including but not limited to human cancer.

  19. Cell illustrator 4.0: a computational platform for systems biology.

    Science.gov (United States)

    Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru

    2011-01-01

    Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

  20. PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

    Science.gov (United States)

    Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

    2016-03-10

    Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and

  1. On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

    KAUST Repository

    Moreo, P.

    2009-11-14

    The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

  2. A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing.

    Science.gov (United States)

    Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

    2015-10-23

    The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.

  3. Investigation of biological microstructures by using diffraction-enhanced imaging computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Shu Hang [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China); Graudate School of the Chinese Academy of Sciences, 100864 Beijing (China); Liu Bo [Capital University of Medical Sciences (China); Zhu, Peiping [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China)]. E-mail: zhupp@ihep.ac.cn; Gao Xin [Capital University of Medical Sciences (China); Yin Hongxia [Capital University of Medical Sciences (China); Yuan Qingxi [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China); Wang Junyue [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China); Graudate School of the Chinese Academy of Sciences, 100864 Beijing (China); Huang Wanxia [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China); Gao Xiulai [Capital University of Medical Sciences (China); Luo Shuqian [Capital University of Medical Sciences (China); Wu Ziyu [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China) and National Center for NanoScience and Technology (China)]. E-mail: wuzy@mail.ihep.ac.cn; Fang Shouxian [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, CAS, Beijing (China)

    2006-11-15

    Diffraction-enhanced imaging computer tomography (DEI-CT) is a new method to provide the object's inner information. Previous reports demonstrated its applicability in soft and hard tissue imaging. Here, we provide further evidence for the improved overall image quality and for the option to distinguish the inner microstructures of the guinea pig's cochlea. Data has shown the details of the cochlea's inner microstructure such as vestibular membrane which only have 6 {mu}m. A better knowledge of these microstructures may be relevant to achieve progress in the otology of clinical anatomization.

  4. Investigation of biological microstructures by using diffraction-enhanced imaging computed tomography

    International Nuclear Information System (INIS)

    Shu Hang; Liu Bo; Zhu, Peiping; Gao Xin; Yin Hongxia; Yuan Qingxi; Wang Junyue; Huang Wanxia; Gao Xiulai; Luo Shuqian; Wu Ziyu; Fang Shouxian

    2006-01-01

    Diffraction-enhanced imaging computer tomography (DEI-CT) is a new method to provide the object's inner information. Previous reports demonstrated its applicability in soft and hard tissue imaging. Here, we provide further evidence for the improved overall image quality and for the option to distinguish the inner microstructures of the guinea pig's cochlea. Data has shown the details of the cochlea's inner microstructure such as vestibular membrane which only have 6 μm. A better knowledge of these microstructures may be relevant to achieve progress in the otology of clinical anatomization

  5. Seven-channel digital telemetry system for monitoring and direct computer capturing of biological data.

    Science.gov (United States)

    Drewes, A M; Andreasen, A; Assentoft, J E; Nagel, O

    1993-09-01

    A seven-channel telemetry system for collection and display of biological data is presented. The system can amplify bioelectrical signals in the range of 2 microV to 200 mV and has a bandwidth of 0.1-80 Hz. After multiplexing, the signals are digitized with a resolution of 8 bits. The data are frequency modulated directly on a VHF transmitter. After receiving the data on a VHF receiver, they are routed directly to the RS232 input connector on the PC. Thereby the advantage of direct communication between the transmitter and the PC can be utilized. Expensive analog equipment is avoided and display of the signals on the PC screen as well as signal analysis can be performed. The system has been tested and was found to be stable and highly reliable.

  6. A computer simulation approach to quantify the true area and true area compressibility modulus of biological membranes

    International Nuclear Information System (INIS)

    Chacón, Enrique; Tarazona, Pedro; Bresme, Fernando

    2015-01-01

    We present a new computational approach to quantify the area per lipid and the area compressibility modulus of biological membranes. Our method relies on the analysis of the membrane fluctuations using our recently introduced coupled undulatory (CU) mode [Tarazona et al., J. Chem. Phys. 139, 094902 (2013)], which provides excellent estimates of the bending modulus of model membranes. Unlike the projected area, widely used in computer simulations of membranes, the CU area is thermodynamically consistent. This new area definition makes it possible to accurately estimate the area of the undulating bilayer, and the area per lipid, by excluding any contributions related to the phospholipid protrusions. We find that the area per phospholipid and the area compressibility modulus features a negligible dependence with system size, making possible their computation using truly small bilayers, involving a few hundred lipids. The area compressibility modulus obtained from the analysis of the CU area fluctuations is fully consistent with the Hooke’s law route. Unlike existing methods, our approach relies on a single simulation, and no a priori knowledge of the bending modulus is required. We illustrate our method by analyzing 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayers using the coarse grained MARTINI force-field. The area per lipid and area compressibility modulus obtained with our method and the MARTINI forcefield are consistent with previous studies of these bilayers

  7. ChemoPy: freely available python package for computational biology and chemoinformatics.

    Science.gov (United States)

    Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng

    2013-04-15

    Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.

  8. Computer-assisted detection of chromosomal aberrations for the purpose of establishing a biological dosimeter

    International Nuclear Information System (INIS)

    Ueberreiter, B.

    1982-01-01

    Using a special high-resolution microscopy apparatus, digital light microscope images of human chromosomes were generated, and specific image processing algorithms were developed. The pattern recognition process for computer-assisted detection of specific, radiation-induced chromosomal aberrations comprises three steps: First, the orientation of the segmented objects is defined and corrected. For date reduction purposes, the individual chromosomes are reduced to a few basic types containing typical information. After a linear transformation step, the characteristic parameters thus derived form a parameter vector for statistical classification. The method was well suited for distinguishing normal chromosomes from chromosomal aberrations. 94% of the objects were identified correctly. To achieve even higher accuracy, quality standards were set by which suspectedly misclassified objects can be re-investigated in dialog by the human observer. Implementation of the program system for parameter extraction on a fast polyprocessor system opens up a realistic chance of reducing the computing time for dose estimates to about one hour. (orig./MG) [de

  9. A Biologically-Based Computational Approach to Drug Repurposing for Anthrax Infection

    Directory of Open Access Journals (Sweden)

    Jane P. F. Bai

    2017-03-01

    Full Text Available Developing drugs to treat the toxic effects of lethal toxin (LT and edema toxin (ET produced by B. anthracis is of global interest. We utilized a computational approach to score 474 drugs/compounds for their ability to reverse the toxic effects of anthrax toxins. For each toxin or drug/compound, we constructed an activity network by using its differentially expressed genes, molecular targets, and protein interactions. Gene expression profiles of drugs were obtained from the Connectivity Map and those of anthrax toxins in human alveolar macrophages were obtained from the Gene Expression Omnibus. Drug rankings were based on the ability of a drug/compound’s mode of action in the form of a signaling network to reverse the effects of anthrax toxins; literature reports were used to verify the top 10 and bottom 10 drugs/compounds identified. Simvastatin and bepridil with reported in vitro potency for protecting cells from LT and ET toxicities were computationally ranked fourth and eighth. The other top 10 drugs were fenofibrate, dihydroergotamine, cotinine, amantadine, mephenytoin, sotalol, ifosfamide, and mefloquine; literature mining revealed their potential protective effects from LT and ET toxicities. These drugs are worthy of investigation for their therapeutic benefits and might be used in combination with antibiotics for treating B. anthracis infection.

  10. Synthesis, biological activity and computational studies of novel azo-compounds

    International Nuclear Information System (INIS)

    Ashraf, J.; Murtaza, S.; Mughal, E.U.; Sadiq, A.

    2017-01-01

    In the present protocol, we report the synthesis and characterization of some novel azo-compounds starting from 4-methoxyaniline and 4-aminophenazone, which were diazotized at low temperature. 4-nitrophenol, 2-aminobenzoic acid, benzamide, 4-aminobenzoic acid, resorcinol, o-bromonitrobenzene and 2-nitroaniline were used as active aromatic coupling compounds for the second step. The synthesized compounds were investigated for their potential antibacterial activities by using disc diffusion method against Escherichia coli, Shigellasonnei, Streptococcus pyrogenes, Staphylococcus aureus and Neisseria gonorrhoeae strains. They were also subjected to antioxidant activities by using DPPH method. Results revealed that the compounds of 4-methoxyaniline and 4-aminophenazone showed good antibacterial activity against all strains, where as some azo-compounds have moderate to good antioxidant activities. Furthermore, these compounds were studied by computational analysis. (author)

  11. A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing

    Directory of Open Access Journals (Sweden)

    Zhaocai Wang

    2015-10-01

    Full Text Available The unbalanced assignment problem (UAP is to optimally resolve the problem of assigning n jobs to m individuals (m < n, such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.

  12. High performance statistical computing with parallel R: applications to biology and climate modelling

    International Nuclear Information System (INIS)

    Samatova, Nagiza F; Branstetter, Marcia; Ganguly, Auroop R; Hettich, Robert; Khan, Shiraj; Kora, Guruprasad; Li, Jiangtian; Ma, Xiaosong; Pan, Chongle; Shoshani, Arie; Yoginath, Srikanth

    2006-01-01

    Ultrascale computing and high-throughput experimental technologies have enabled the production of scientific data about complex natural phenomena. With this opportunity, comes a new problem - the massive quantities of data so produced. Answers to fundamental questions about the nature of those phenomena remain largely hidden in the produced data. The goal of this work is to provide a scalable high performance statistical data analysis framework to help scientists perform interactive analyses of these raw data to extract knowledge. Towards this goal we have been developing an open source parallel statistical analysis package, called Parallel R, that lets scientists employ a wide range of statistical analysis routines on high performance shared and distributed memory architectures without having to deal with the intricacies of parallelizing these routines

  13. uPy: a ubiquitous computer graphics Python API with Biological Modeling Applications

    Science.gov (United States)

    Autin, L.; Johnson, G.; Hake, J.; Olson, A.; Sanner, M.

    2015-01-01

    In this paper we describe uPy, an extension module for the Python programming language that provides a uniform abstraction of the APIs of several 3D computer graphics programs called hosts, including: Blender, Maya, Cinema4D, and DejaVu. A plugin written with uPy is a unique piece of code that will run in all uPy-supported hosts. We demonstrate the creation of complex plug-ins for molecular/cellular modeling and visualization and discuss how uPy can more generally simplify programming for many types of projects (not solely science applications) intended for multi-host distribution. uPy is available at http://upy.scripps.edu PMID:24806987

  14. Rapid Detection of Biological and Chemical Threat Agents Using Physical Chemistry, Active Detection, and Computational Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Myung; Dong, Li; Fu, Rong; Liotta, Lance; Narayanan, Aarthi; Petricoin, Emanuel; Ross, Mark; Russo, Paul; Zhou, Weidong; Luchini, Alessandra; Manes, Nathan; Chertow, Jessica; Han, Suhua; Kidd, Jessica; Senina, Svetlana; Groves, Stephanie

    2007-01-01

    Basic technologies have been successfully developed within this project: rapid collection of aerosols and a rapid ultra-sensitive immunoassay technique. Water-soluble, humidity-resistant polyacrylamide nano-filters were shown to (1) capture aerosol particles as small as 20 nm, (2) work in humid air and (3) completely liberate their captured particles in an aqueous solution compatible with the immunoassay technique. The immunoassay technology developed within this project combines electrophoretic capture with magnetic bead detection. It allows detection of as few as 150-600 analyte molecules or viruses in only three minutes, something no other known method can duplicate. The technology can be used in a variety of applications where speed of analysis and/or extremely low detection limits are of great importance: in rapid analysis of donor blood for hepatitis, HIV and other blood-borne infections in emergency blood transfusions, in trace analysis of pollutants, or in search of biomarkers in biological fluids. Combined in a single device, the water-soluble filter and ultra-sensitive immunoassay technique may solve the problem of early warning type detection of aerosolized pathogens. These two technologies are protected with five patent applications and are ready for commercialization.

  15. Evolution of the rate of biological aging using a phenotype based computational model.

    Science.gov (United States)

    Kittas, Aristotelis

    2010-10-07

    In this work I introduce a simple model to study how natural selection acts upon aging, which focuses on the viability of each individual. It is able to reproduce the Gompertz law of mortality and can make predictions about the relation between the level of mutation rates (beneficial/deleterious/neutral), age at reproductive maturity and the degree of biological aging. With no mutations, a population with low age at reproductive maturity R stabilizes at higher density values, while with mutations it reaches its maximum density, because even for large pre-reproductive periods each individual evolves to survive to maturity. Species with very short pre-reproductive periods can only tolerate a small number of detrimental mutations. The probabilities of detrimental (P(d)) or beneficial (P(b)) mutations are demonstrated to greatly affect the process. High absolute values produce peaks in the viability of the population over time. Mutations combined with low selection pressure move the system towards weaker phenotypes. For low values in the ratio P(d)/P(b), the speed at which aging occurs is almost independent of R, while higher values favor significantly species with high R. The value of R is critical to whether the population survives or dies out. The aging rate is controlled by P(d) and P(b) and the amount of the viability of each individual is modified, with neutral mutations allowing the system more "room" to evolve. The process of aging in this simple model is revealed to be fairly complex, yielding a rich variety of results. 2010 Elsevier Ltd. All rights reserved.

  16. OpenCOR: a modular and interoperable approach to computational biology

    Directory of Open Access Journals (Sweden)

    Alan eGarny

    2015-02-01

    Full Text Available Computational biologists have been developing standards and formats for nearly two decades, with the aim of easing the description and exchange of experimental data, mathematical models, simulation experiments, etc. One of those efforts is CellML (cellml.org, an XML-based markup language for the encoding of mathematical models.Early CellML-based environments include COR and OpenCell. However, both of those tools have limitations and were eventually replaced with OpenCOR (opencor.ws. OpenCOR is an open source modeling environment that is supported on Windows, Linux and OS X. It relies on a modular approach, which means that all of its features come in the form of plugins. Those plugins can be used to organize, edit, simulate and analyze models encoded in the CellML format.We start with an introduction to CellML and two of its early adopters, which limitations eventually led to the development of OpenCOR. We then go onto describing the general philosophy behind OpenCOR, as well as describing its openness and its development process. Next, we illustrate various aspects of OpenCOR, such as its user interface and some of the plugins that come bundled with it (e.g. its editing and simulation plugins. Finally, we discuss some of the advantages and limitations of OpenCOR before drawing some concluding remarks.

  17. Computational and biological characterization of fusion proteins of two insecticidal proteins for control of insect pests.

    Science.gov (United States)

    Javaid, Shaista; Naz, Sehrish; Amin, Imran; Jander, Georg; Ul-Haq, Zaheer; Mansoor, Shahid

    2018-03-19

    Sucking pests pose a serious agricultural challenge, as available transgenic technologies such as Bacillus thuringiensis crystal toxins (Bt) are not effective against them. One approach is to produce fusion protein toxins for the control of these pests. Two protein toxins, Hvt (ω-atracotoxin from Hadronyche versuta) and onion leaf lectin, were translationally fused to evaluate the negative effects of fusion proteins on Phenacoccus solenopsis (mealybug), a phloem-feeding insect pest. Hvt was cloned both N-terminally (HL) and then C-terminally (LH) in the fusion protein constructs, which were expressed transiently in Nicotiana tabacum using a Potato Virus X (PVX) vector. The HL fusion protein was found to be more effective against P. solenopsis, with an 83% mortality rate, as compared to the LH protein, which caused 65% mortality. Hvt and lectin alone caused 42% and 45%, respectively, under the same conditions. Computational studies of both fusion proteins showed that the HL protein is more stable than the LH protein. Together, these results demonstrate that translational fusion of two insecticidal proteins improved the insecticidal activity relative to each protein individually and could be expressed in transgenic plants for effective control of sucking pests.

  18. Notes on stochastic (bio)-logic gates: computing with allosteric cooperativity.

    Science.gov (United States)

    Agliari, Elena; Altavilla, Matteo; Barra, Adriano; Dello Schiavo, Lorenzo; Katz, Evgeny

    2015-05-15

    Recent experimental breakthroughs have finally allowed to implement in-vitro reaction kinetics (the so called enzyme based logic) which code for two-inputs logic gates and mimic the stochastic AND (and NAND) as well as the stochastic OR (and NOR). This accomplishment, together with the already-known single-input gates (performing as YES and NOT), provides a logic base and paves the way to the development of powerful biotechnological devices. However, as biochemical systems are always affected by the presence of noise (e.g. thermal), standard logic is not the correct theoretical reference framework, rather we show that statistical mechanics can work for this scope: here we formulate a complete statistical mechanical description of the Monod-Wyman-Changeaux allosteric model for both single and double ligand systems, with the purpose of exploring their practical capabilities to express noisy logical operators and/or perform stochastic logical operations. Mixing statistical mechanics with logics, and testing quantitatively the resulting findings on the available biochemical data, we successfully revise the concept of cooperativity (and anti-cooperativity) for allosteric systems, with particular emphasis on its computational capabilities, the related ranges and scaling of the involved parameters and its differences with classical cooperativity (and anti-cooperativity).

  19. The Müller-Lyer Illusion in a computational model of biological object recognition.

    Directory of Open Access Journals (Sweden)

    Astrid Zeman

    Full Text Available Studying illusions provides insight into the way the brain processes information. The Müller-Lyer Illusion (MLI is a classical geometrical illusion of size, in which perceived line length is decreased by arrowheads and increased by arrowtails. Many theories have been put forward to explain the MLI, such as misapplied size constancy scaling, the statistics of image-source relationships and the filtering properties of signal processing in primary visual areas. Artificial models of the ventral visual processing stream allow us to isolate factors hypothesised to cause the illusion and test how these affect classification performance. We trained a feed-forward feature hierarchical model, HMAX, to perform a dual category line length judgment task (short versus long with over 90% accuracy. We then tested the system in its ability to judge relative line lengths for images in a control set versus images that induce the MLI in humans. Results from the computational model show an overall illusory effect similar to that experienced by human subjects. No natural images were used for training, implying that misapplied size constancy and image-source statistics are not necessary factors for generating the illusion. A post-hoc analysis of response weights within a representative trained network ruled out the possibility that the illusion is caused by a reliance on information at low spatial frequencies. Our results suggest that the MLI can be produced using only feed-forward, neurophysiological connections.

  20. MODELING HOST-PATHOGEN INTERACTIONS: COMPUTATIONAL BIOLOGY AND BIOINFORMATICS FOR INFECTIOUS DISEASE RESEARCH (Session introduction)

    Energy Technology Data Exchange (ETDEWEB)

    McDermott, Jason E.; Braun, Pascal; Bonneau, Richard A.; Hyduke, Daniel R.

    2011-12-01

    Pathogenic infections are a major cause of both human disease and loss of crop yields and animal stocks and thus cause immense damage to the worldwide economy. The significance of infectious diseases is expected to increase in an ever more connected warming world, in which new viral, bacterial and fungal pathogens can find novel hosts and ecologic niches. At the same time, the complex and sophisticated mechanisms by which diverse pathogenic agents evade defense mechanisms and subvert their hosts networks to suit their lifestyle needs is still very incompletely understood especially from a systems perspective [1]. Thus, understanding host-pathogen interactions is both an important and a scientifically fascinating topic. Recently, technology has offered the opportunity to investigate host-pathogen interactions on a level of detail and scope that offers immense computational and analytical possibilities. Genome sequencing was pioneered on some of these pathogens, and the number of strains and variants of pathogens sequenced to date vastly outnumbers the number of host genomes available. At the same time, for both plant and human hosts more and more data on population level genomic variation becomes available and offers a rich field for analysis into the genetic interactions between host and pathogen.

  1. Multi-objective optimization of a compact pressurized water nuclear reactor computational model for biological shielding design using innovative materials

    Energy Technology Data Exchange (ETDEWEB)

    Tunes, M.A., E-mail: matheus.tunes@usp.br [Department of Metallurgical and Materials Engineering, Escola Politécnica da Universidade de São Paulo, Av. Prof. Mello Moraes, 2463 – CEP 05508 – 030 São Paulo (Brazil); Oliveira, C.R.E. de, E-mail: cassiano@unm.edu [Department of Nuclear Engineering, The University of New Mexico, Farris Engineering Center, 221, Albuquerque, NM 87131-1070 (United States); Schön, C.G., E-mail: schoen@usp.br [Department of Metallurgical and Materials Engineering, Escola Politécnica da Universidade de São Paulo, Av. Prof. Mello Moraes, 2463 – CEP 05508 – 030 São Paulo (Brazil)

    2017-03-15

    Highlights: • Use of two n-γ transport codes leads to optimized model of compact nuclear reactor. • It was possible to safely reduce both weight and volume of the biological shielding. • Best configuration obtained by using new composites for both γ and n attenuation. - Abstract: The aim of the present work is to develop a computational model of a compact pressurized water nuclear reactor (PWR) to investigate the use of innovative materials to enhance the biological shielding effectiveness. Two radiation transport codes were used: the first one – MCNP – for the PWR design and the GEM/EVENT to simulate (in a 1D slab) the behavior of several materials and shielding thickness on gamma and neutron radiation. Additionally MATLAB Optimization Toolbox was used to provide new geometric configurations of the slab aiming at reducing the volume and weight of the walls by means of a cost/objective function. It is demonstrated in the reactor model that the dose rate outside biological shielding has been reduced by one order of magnitude for the optimized model compared with the initial configuration. Volume and weight of the shielding walls were also reduced. The results indicated that one-dimensional deterministic code to reach an optimized geometry and test materials, combined with a three-dimensional model of a compact nuclear reactor in a stochastic code, is a fast and efficient procedure to test shielding performance and optimization before the experimental assessment. A major outcome of this research is that composite materials (ECOMASS 2150TU96) may replace (with advantages) traditional shielding materials without jeopardizing the nuclear power plant safety assurance.

  2. Biologically important conformational features of DNA as interpreted by quantum mechanics and molecular mechanics computations of its simple fragments.

    Science.gov (United States)

    Poltev, V; Anisimov, V M; Dominguez, V; Gonzalez, E; Deriabina, A; Garcia, D; Rivas, F; Polteva, N A

    2018-02-01

    Deciphering the mechanism of functioning of DNA as the carrier of genetic information requires identifying inherent factors determining its structure and function. Following this path, our previous DFT studies attributed the origin of unique conformational characteristics of right-handed Watson-Crick duplexes (WCDs) to the conformational profile of deoxydinucleoside monophosphates (dDMPs) serving as the minimal repeating units of DNA strand. According to those findings, the directionality of the sugar-phosphate chain and the characteristic ranges of dihedral angles of energy minima combined with the geometric differences between purines and pyrimidines determine the dependence on base sequence of the three-dimensional (3D) structure of WCDs. This work extends our computational study to complementary deoxydinucleotide-monophosphates (cdDMPs) of non-standard conformation, including those of Z-family, Hoogsteen duplexes, parallel-stranded structures, and duplexes with mispaired bases. For most of these systems, except Z-conformation, computations closely reproduce experimental data within the tolerance of characteristic limits of dihedral parameters for each conformation family. Computation of cdDMPs with Z-conformation reveals that their experimental structures do not correspond to the internal energy minimum. This finding establishes the leading role of external factors in formation of the Z-conformation. Energy minima of cdDMPs of non-Watson-Crick duplexes demonstrate different sequence-dependence features than those known for WCDs. The obtained results provide evidence that the biologically important regularities of 3D structure distinguish WCDs from duplexes having non-Watson-Crick nucleotide pairing.

  3. Decomposing dendrophilia. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

    Science.gov (United States)

    Honing, Henkjan; Zuidema, Willem

    2014-09-01

    The future of cognitive science will be about bridging neuroscience and behavioral studies, with essential roles played by comparative biology, formal modeling, and the theory of computation. Nowhere will this integration be more strongly needed than in understanding the biological basis of language and music. We thus strongly sympathize with the general framework that Fitch [1] proposes, and welcome the remarkably broad and readable review he presents to support it.

  4. Computational Medicine

    DEFF Research Database (Denmark)

    Nygaard, Jens Vinge

    2017-01-01

    The Health Technology Program at Aarhus University applies computational biology to investigate the heterogeneity of tumours......The Health Technology Program at Aarhus University applies computational biology to investigate the heterogeneity of tumours...

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

    OpenAIRE

    D'Onofrio, David J; An, Gary

    2010-01-01

    Abstract 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 pr...

  6. A counterpoint between computer simulations and biological experiments to train new members of a laboratory of physiological sciences.

    Science.gov (United States)

    Ozu, Marcelo; Dorr, Ricardo A; Gutiérrez, Facundo; Politi, M Teresa; Toriano, Roxana

    2012-12-01

    When new members join a working group dedicated to scientific research, several changes occur in the group's dynamics. From a teaching point of view, a subsequent challenge is to develop innovative strategies to train new staff members in creative thinking, which is the most complex and abstract skill in the cognitive domain according to Bloom's revised taxonomy. In this sense, current technological and digital advances offer new possibilities in the field of education. Computer simulation and biological experiments can be used together as a combined tool for teaching and learning sometimes complex physiological and biophysical concepts. Moreover, creativity can be thought of as a social process that relies on interactions among staff members. In this regard, the acquisition of cognitive abilities coexists with the attainment of other skills from psychomotor and affective domains. Such dynamism in teaching and learning stimulates teamwork and encourages the integration of members of the working group. A practical example, based on the teaching of biophysical subjects such as osmosis, solute transport, and membrane permeability, which are crucial in understanding the physiological concept of homeostasis, is presented.

  7. An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64.

    Science.gov (United States)

    Winkler, Robert

    2015-01-01

    In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models

  8. A Proposed Computed Tomography Contrast Agent Using Carboxybetaine Zwitterionic Tantalum Oxide Nanoparticles: Imaging, Biological, and Physicochemical Performance.

    Science.gov (United States)

    FitzGerald, Paul F; Butts, Matthew D; Roberts, Jeannette C; Colborn, Robert E; Torres, Andrew S; Lee, Brian D; Yeh, Benjamin M; Bonitatibus, Peter J

    2016-12-01

    The aim of this study was to produce and evaluate a proposed computed tomography (CT) contrast agent based on carboxybetaine zwitterionic (CZ)-coated soluble tantalum oxide (TaO) nanoparticles (NPs). We chose tantalum to provide superior imaging performance compared with current iodine-based clinical CT contrast agents. We developed the CZ coating to provide biological and physical performance similar to that of current iodinated contrast agents. In addition, the aim of this study was to evaluate the imaging, biological, and physicochemical performance of this proposed contrast agent compared with clinically used iodinated agents. We evaluated CT imaging performance of our CZ-TaO NPs compared with that of an iodinated agent in live rats, imaged centrally located within a tissue-equivalent plastic phantom that simulated a large patient. To evaluate vascular contrast enhancement, we scanned the rats' great vessels at high temporal resolution during and after contrast agent injection. We performed several in vivo CZ-TaO NP studies in healthy rats to evaluate tolerability. These studies included injecting the agent at the anticipated clinical dose (ACD) and at 3 times and 6 times the ACD, followed by longitudinal hematology to assess impact to blood cells and organ function (from 4 hours to 1 week). Kidney histological analysis was performed 48 hours after injection at 3 times the ACD. We measured the elimination half-life of CZ-TaO NPs from blood, and we monitored acute kidney injury biomarkers with a kidney injury assay using urine collected from 4 hours to 1 week. We measured tantalum retention in individual organs and in the whole carcass 48 hours after injection at ACD. Carboxybetaine zwitterionic TaO NPs were synthesized and analyzed in detail. We used multidimensional nuclear magnetic resonance to determine surface functionality of the NPs. We measured NP size and solution properties (osmolality and viscosity) of the agent over a range of tantalum concentrations

  9. COMPUTING

    CERN Multimedia

    M. Kasemann

    Overview In autumn the main focus was to process and handle CRAFT data and to perform the Summer08 MC production. The operational aspects were well covered by regular Computing Shifts, experts on duty and Computing Run Coordination. At the Computing Resource Board (CRB) in October a model to account for service work at Tier 2s was approved. The computing resources for 2009 were reviewed for presentation at the C-RRB. The quarterly resource monitoring is continuing. Facilities/Infrastructure operations Operations during CRAFT data taking ran fine. This proved to be a very valuable experience for T0 workflows and operations. The transfers of custodial data to most T1s went smoothly. A first round of reprocessing started at the Tier-1 centers end of November; it will take about two weeks. The Computing Shifts procedure was tested full scale during this period and proved to be very efficient: 30 Computing Shifts Persons (CSP) and 10 Computing Resources Coordinators (CRC). The shift program for the shut down w...

  10. 2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

    Science.gov (United States)

    2010-01-01

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

  11. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction CMS distributed computing system performed well during the 2011 start-up. The events in 2011 have more pile-up and are more complex than last year; this results in longer reconstruction times and harder events to simulate. Significant increases in computing capacity were delivered in April for all computing tiers, and the utilisation and load is close to the planning predictions. All computing centre tiers performed their expected functionalities. Heavy-Ion Programme The CMS Heavy-Ion Programme had a very strong showing at the Quark Matter conference. A large number of analyses were shown. The dedicated heavy-ion reconstruction facility at the Vanderbilt Tier-2 is still involved in some commissioning activities, but is available for processing and analysis. Facilities and Infrastructure Operations Facility and Infrastructure operations have been active with operations and several important deployment tasks. Facilities participated in the testing and deployment of WMAgent and WorkQueue+Request...

  12. COMPUTING

    CERN Multimedia

    P. McBride

    The Computing Project is preparing for a busy year where the primary emphasis of the project moves towards steady operations. Following the very successful completion of Computing Software and Analysis challenge, CSA06, last fall, we have reorganized and established four groups in computing area: Commissioning, User Support, Facility/Infrastructure Operations and Data Operations. These groups work closely together with groups from the Offline Project in planning for data processing and operations. Monte Carlo production has continued since CSA06, with about 30M events produced each month to be used for HLT studies and physics validation. Monte Carlo production will continue throughout the year in the preparation of large samples for physics and detector studies ramping to 50 M events/month for CSA07. Commissioning of the full CMS computing system is a major goal for 2007. Site monitoring is an important commissioning component and work is ongoing to devise CMS specific tests to be included in Service Availa...

  13. COMPUTING

    CERN Multimedia

    M. Kasemann

    Overview During the past three months activities were focused on data operations, testing and re-enforcing shift and operational procedures for data production and transfer, MC production and on user support. Planning of the computing resources in view of the new LHC calendar in ongoing. Two new task forces were created for supporting the integration work: Site Commissioning, which develops tools helping distributed sites to monitor job and data workflows, and Analysis Support, collecting the user experience and feedback during analysis activities and developing tools to increase efficiency. The development plan for DMWM for 2009/2011 was developed at the beginning of the year, based on the requirements from the Physics, Computing and Offline groups (see Offline section). The Computing management meeting at FermiLab on February 19th and 20th was an excellent opportunity discussing the impact and for addressing issues and solutions to the main challenges facing CMS computing. The lack of manpower is particul...

  14. Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland

    Energy Technology Data Exchange (ETDEWEB)

    Arkin, Adam [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bader, David C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hack, James [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States); Riley, Katherine [Argonne National Lab. (ANL), Argonne, IL (United States); Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Aluru, Srinivas [Georgia Inst. of Technology, Atlanta, GA (United States); Andersen, Amity [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Aprá, Edoardo [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Azad, Ariful [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bates, Susan [National Center for Atmospheric Research, Boulder, CO (United States); Blaby, Ian [Brookhaven National Lab. (BNL), Upton, NY (United States); Blaby-Haas, Crysten [Brookhaven National Lab. (BNL), Upton, NY (United States); Bonneau, Rich [New York Univ. (NYU), NY (United States); Bowen, Ben [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bradford, Mark A. [Yale Univ., New Haven, CT (United States); Brodie, Eoin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, James (Ben) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bernholdt, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bylaska, Eric [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Calvin, Kate [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cannon, Bill [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, Xingyuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cheng, Xiaolin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cheung, Margaret [Univ. of Houston, Houston, TX (United States); Chowdhary, Kenny [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Colella, Phillip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Collins, Bill [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Compo, Gil [National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States); Crowley, Mike [National Renewable Energy Lab. (NREL), Golden, CO (United States); Debusschere, Bert [Sandia National Lab. (SNL-CA), Livermore, CA (United States); D’Imperio, Nicholas [Brookhaven National Lab. (BNL), Upton, NY (United States); Dror, Ron [Stanford Univ., Stanford, CA (United States); Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Evans, Katherine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Friedberg, Iddo [Iowa State Univ., Ames, IA (United States); Fyke, Jeremy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gao, Zheng [Stony Brook Univ., Stony Brook, NY (United States); Georganas, Evangelos [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Giraldo, Frank [Naval Postgraduate School, Monterey, CA (United States); Gnanakaran, Gnana [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Govind, Niri [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Grandy, Stuart [Univ. of New Hampshire, Durham, NH (United States); Gustafson, Bill [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hammond, Glenn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hargrove, William [USDA Forest Service, Washington, D.C. (United States); Heroux, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hoffman, Forrest [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hofmeyr, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hunke, Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Jackson, Charles [Univ. of Texas-Austin, Austin, TX (United States); Jacob, Rob [Argonne National Lab. (ANL), Argonne, IL (United States); Jacobson, Dan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jacobson, Matt [Univ. of California, San Francisco, CA (United States); Jain, Chirag [Georgia Inst. of Technology, Atlanta, GA (United States); Johansen, Hans [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Johnson, Jeff [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jones, Andy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jones, Phil [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kalyanaraman, Ananth [Washington State Univ., Pullman, WA (United States); Kang, Senghwa [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); King, Eric [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koanantakool, Penporn [Univ. of California, Berkeley, CA (United States); Kollias, Pavlos [Stony Brook Univ., Stony Brook, NY (United States); Kopera, Michal [Univ. of California, Santa Cruz, CA (United States); Kotamarthi, Rao [Argonne National Lab. (ANL), Argonne, IL (United States); Kowalski, Karol [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Kumar, Jitendra [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kyrpides, Nikos [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Leung, Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Li, Xiaolin [Stony Brook Univ., Stony Brook, NY (United States); Lin, Wuyin [Brookhaven National Lab. (BNL), Upton, NY (United States); Link, Robert [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Yangang [Brookhaven National Lab. (BNL), Upton, NY (United States); Loew, Leslie [Univ. of Connecticut, Storrs, CT (United States); Luke, Edward [Brookhaven National Lab. (BNL), Upton, NY (United States); Ma, Hsi -Yen [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mahadevan, Radhakrishnan [Univ. of Toronto, Toronto, ON (Canada); Maranas, Costas [Pennsylvania State Univ., University Park, PA (United States); Martin, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States); McCue, Lee Ann [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); McInnes, Lois Curfman [Argonne National Lab. (ANL), Argonne, IL (United States); Mills, Richard [Intel Corp., Santa Clara, CA (United States); Molins Rafa, Sergi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitriy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mostafavi, Sara [Center for Molecular Medicine and Therapeutics, Vancouver, BC (Canada); Moulton, David J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mourao, Zenaida [Univ. of Cambridge (United Kingdom); Najm, Habib [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ng, Bernard [Center for Molecular Medicine and Therapeutics, Vancouver, BC (Canada); Ng, Esmond [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Norman, Matt [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oh, Sang -Yun [Univ. of California, Santa Barbara, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pan, Chongle [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pass, Rebecca [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pau, George S. H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Petridis, Loukas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Prakash, Giri [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Price, Stephen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Randall, David [Colorado State Univ., Fort Collins, CO (United States); Renslow, Ryan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Riihimaki, Laura [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ringler, Todd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States); Rokhsar, Dan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ruebel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Salinger, Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Scheibe, Tim [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Schulz, Roland [Intel, Mountain View, CA (United States); Sivaraman, Chitra [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sreepathi, Sarat [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Steefel, Carl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Talbot, Jenifer [Boston Univ., Boston, MA (United States); Tantillo, D. J. [Univ. of California, Davis, CA (United States); Tartakovsky, Alex [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Taylor, Mark [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Taylor, Ronald [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Trebotich, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Urban, Nathan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Valiev, Marat [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Wagner, Allon [Univ. of California, Berkeley, CA (United States); Wainwright, Haruko [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wieder, Will [NCAR/Univ. of Colorado, Boulder, CO (United States); Wiley, Steven [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Dean [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Worley, Pat [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Yelick, Kathy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yoo, Shinjae [Brookhaven National Lab. (BNL), Upton, NY (United States); Yosef, Niri [Univ. of California, Berkeley, CA (United States); Zhang, Minghua [Stony Brook Univ., Stony Brook, NY (United States)

    2016-03-31

    Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOE began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.

  15. A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks

    Directory of Open Access Journals (Sweden)

    Thomas eEissing

    2011-02-01

    Full Text Available Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multi-scale by nature, project work and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug-drug or drug-metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

  16. Computational Model Prediction and Biological Validation Using Simplified Mixed Field Exposures for the Development of a GCR Reference Field

    Science.gov (United States)

    Hada, M.; Rhone, J.; Beitman, A.; Saganti, P.; Plante, I.; Ponomarev, A.; Slaba, T.; Patel, Z.

    2018-01-01

    The yield of chromosomal aberrations has been shown to increase in the lymphocytes of astronauts after long-duration missions of several months in space. Chromosome exchanges, especially translocations, are positively correlated with many cancers and are therefore a potential biomarker of cancer risk associated with radiation exposure. Although extensive studies have been carried out on the induction of chromosomal aberrations by low- and high-LET radiation in human lymphocytes, fibroblasts, and epithelial cells exposed in vitro, there is a lack of data on chromosome aberrations induced by low dose-rate chronic exposure and mixed field beams such as those expected in space. Chromosome aberration studies at NSRL will provide the biological validation needed to extend the computational models over a broader range of experimental conditions (more complicated mixed fields leading up to the galactic cosmic rays (GCR) simulator), helping to reduce uncertainties in radiation quality effects and dose-rate dependence in cancer risk models. These models can then be used to answer some of the open questions regarding requirements for a full GCR reference field, including particle type and number, energy, dose rate, and delivery order. In this study, we designed a simplified mixed field beam with a combination of proton, helium, oxygen, and iron ions with shielding or proton, helium, oxygen, and titanium without shielding. Human fibroblasts cells were irradiated with these mixed field beam as well as each single beam with acute and chronic dose rate, and chromosome aberrations (CA) were measured with 3-color fluorescent in situ hybridization (FISH) chromosome painting methods. Frequency and type of CA induced with acute dose rate and chronic dose rates with single and mixed field beam will be discussed. A computational chromosome and radiation-induced DNA damage model, BDSTRACKS (Biological Damage by Stochastic Tracks), was updated to simulate various types of CA induced by

  17. COMPUTING

    CERN Multimedia

    I. Fisk

    2013-01-01

    Computing activity had ramped down after the completion of the reprocessing of the 2012 data and parked data, but is increasing with new simulation samples for analysis and upgrade studies. Much of the Computing effort is currently involved in activities to improve the computing system in preparation for 2015. Operations Office Since the beginning of 2013, the Computing Operations team successfully re-processed the 2012 data in record time, not only by using opportunistic resources like the San Diego Supercomputer Center which was accessible, to re-process the primary datasets HTMHT and MultiJet in Run2012D much earlier than planned. The Heavy-Ion data-taking period was successfully concluded in February collecting almost 500 T. Figure 3: Number of events per month (data) In LS1, our emphasis is to increase efficiency and flexibility of the infrastructure and operation. Computing Operations is working on separating disk and tape at the Tier-1 sites and the full implementation of the xrootd federation ...

  18. COMPUTING

    CERN Multimedia

    I. Fisk

    2010-01-01

    Introduction It has been a very active quarter in Computing with interesting progress in all areas. The activity level at the computing facilities, driven by both organised processing from data operations and user analysis, has been steadily increasing. The large-scale production of simulated events that has been progressing throughout the fall is wrapping-up and reprocessing with pile-up will continue. A large reprocessing of all the proton-proton data has just been released and another will follow shortly. The number of analysis jobs by users each day, that was already hitting the computing model expectations at the time of ICHEP, is now 33% higher. We are expecting a busy holiday break to ensure samples are ready in time for the winter conferences. Heavy Ion An activity that is still in progress is computing for the heavy-ion program. The heavy-ion events are collected without zero suppression, so the event size is much large at roughly 11 MB per event of RAW. The central collisions are more complex and...

  19. COMPUTING

    CERN Multimedia

    M. Kasemann P. McBride Edited by M-C. Sawley with contributions from: P. Kreuzer D. Bonacorsi S. Belforte F. Wuerthwein L. Bauerdick K. Lassila-Perini M-C. Sawley

    Introduction More than seventy CMS collaborators attended the Computing and Offline Workshop in San Diego, California, April 20-24th to discuss the state of readiness of software and computing for collisions. Focus and priority were given to preparations for data taking and providing room for ample dialog between groups involved in Commissioning, Data Operations, Analysis and MC Production. Throughout the workshop, aspects of software, operating procedures and issues addressing all parts of the computing model were discussed. Plans for the CMS participation in STEP’09, the combined scale testing for all four experiments due in June 2009, were refined. The article in CMS Times by Frank Wuerthwein gave a good recap of the highly collaborative atmosphere of the workshop. Many thanks to UCSD and to the organizers for taking care of this workshop, which resulted in a long list of action items and was definitely a success. A considerable amount of effort and care is invested in the estimate of the comput...

  20. COMPUTING

    CERN Multimedia

    P. McBride

    It has been a very active year for the computing project with strong contributions from members of the global community. The project has focused on site preparation and Monte Carlo production. The operations group has begun processing data from P5 as part of the global data commissioning. Improvements in transfer rates and site availability have been seen as computing sites across the globe prepare for large scale production and analysis as part of CSA07. Preparations for the upcoming Computing Software and Analysis Challenge CSA07 are progressing. Ian Fisk and Neil Geddes have been appointed as coordinators for the challenge. CSA07 will include production tests of the Tier-0 production system, reprocessing at the Tier-1 sites and Monte Carlo production at the Tier-2 sites. At the same time there will be a large analysis exercise at the Tier-2 centres. Pre-production simulation of the Monte Carlo events for the challenge is beginning. Scale tests of the Tier-0 will begin in mid-July and the challenge it...

  1. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction During the past six months, Computing participated in the STEP09 exercise, had a major involvement in the October exercise and has been working with CMS sites on improving open issues relevant for data taking. At the same time operations for MC production, real data reconstruction and re-reconstructions and data transfers at large scales were performed. STEP09 was successfully conducted in June as a joint exercise with ATLAS and the other experiments. It gave good indication about the readiness of the WLCG infrastructure with the two major LHC experiments stressing the reading, writing and processing of physics data. The October Exercise, in contrast, was conducted as an all-CMS exercise, where Physics, Computing and Offline worked on a common plan to exercise all steps to efficiently access and analyze data. As one of the major results, the CMS Tier-2s demonstrated to be fully capable for performing data analysis. In recent weeks, efforts were devoted to CMS Computing readiness. All th...

  2. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction It has been a very active quarter in Computing with interesting progress in all areas. The activity level at the computing facilities, driven by both organised processing from data operations and user analysis, has been steadily increasing. The large-scale production of simulated events that has been progressing throughout the fall is wrapping-up and reprocessing with pile-up will continue. A large reprocessing of all the proton-proton data has just been released and another will follow shortly. The number of analysis jobs by users each day, that was already hitting the computing model expectations at the time of ICHEP, is now 33% higher. We are expecting a busy holiday break to ensure samples are ready in time for the winter conferences. Heavy Ion The Tier 0 infrastructure was able to repack and promptly reconstruct heavy-ion collision data. Two copies were made of the data at CERN using a large CASTOR disk pool, and the core physics sample was replicated ...

  3. COMPUTING

    CERN Multimedia

    I. Fisk

    2012-01-01

    Introduction Computing continued with a high level of activity over the winter in preparation for conferences and the start of the 2012 run. 2012 brings new challenges with a new energy, more complex events, and the need to make the best use of the available time before the Long Shutdown. We expect to be resource constrained on all tiers of the computing system in 2012 and are working to ensure the high-priority goals of CMS are not impacted. Heavy ions After a successful 2011 heavy-ion run, the programme is moving to analysis. During the run, the CAF resources were well used for prompt analysis. Since then in 2012 on average 200 job slots have been used continuously at Vanderbilt for analysis workflows. Operations Office As of 2012, the Computing Project emphasis has moved from commissioning to operation of the various systems. This is reflected in the new organisation structure where the Facilities and Data Operations tasks have been merged into a common Operations Office, which now covers everything ...

  4. COMPUTING

    CERN Multimedia

    M. Kasemann

    CCRC’08 challenges and CSA08 During the February campaign of the Common Computing readiness challenges (CCRC’08), the CMS computing team had achieved very good results. The link between the detector site and the Tier0 was tested by gradually increasing the number of parallel transfer streams well beyond the target. Tests covered the global robustness at the Tier0, processing a massive number of very large files and with a high writing speed to tapes.  Other tests covered the links between the different Tiers of the distributed infrastructure and the pre-staging and reprocessing capacity of the Tier1’s: response time, data transfer rate and success rate for Tape to Buffer staging of files kept exclusively on Tape were measured. In all cases, coordination with the sites was efficient and no serious problem was found. These successful preparations prepared the ground for the second phase of the CCRC’08 campaign, in May. The Computing Software and Analysis challen...

  5. COMPUTING

    CERN Multimedia

    I. Fisk

    2010-01-01

    Introduction The first data taking period of November produced a first scientific paper, and this is a very satisfactory step for Computing. It also gave the invaluable opportunity to learn and debrief from this first, intense period, and make the necessary adaptations. The alarm procedures between different groups (DAQ, Physics, T0 processing, Alignment/calibration, T1 and T2 communications) have been reinforced. A major effort has also been invested into remodeling and optimizing operator tasks in all activities in Computing, in parallel with the recruitment of new Cat A operators. The teams are being completed and by mid year the new tasks will have been assigned. CRB (Computing Resource Board) The Board met twice since last CMS week. In December it reviewed the experience of the November data-taking period and could measure the positive improvements made for the site readiness. It also reviewed the policy under which Tier-2 are associated with Physics Groups. Such associations are decided twice per ye...

  6. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction More than seventy CMS collaborators attended the Computing and Offline Workshop in San Diego, California, April 20-24th to discuss the state of readiness of software and computing for collisions. Focus and priority were given to preparations for data taking and providing room for ample dialog between groups involved in Commissioning, Data Operations, Analysis and MC Production. Throughout the workshop, aspects of software, operating procedures and issues addressing all parts of the computing model were discussed. Plans for the CMS participation in STEP’09, the combined scale testing for all four experiments due in June 2009, were refined. The article in CMS Times by Frank Wuerthwein gave a good recap of the highly collaborative atmosphere of the workshop. Many thanks to UCSD and to the organizers for taking care of this workshop, which resulted in a long list of action items and was definitely a success. A considerable amount of effort and care is invested in the estimate of the co...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    D'Onofrio, David J; An, Gary

    2010-01-21

    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. 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. 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 systems do not have an

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

    Directory of Open Access Journals (Sweden)

    D'Onofrio David J

    2010-01-01

    Full Text Available Abstract 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

  10. COMPUTING

    CERN Multimedia

    2010-01-01

    Introduction Just two months after the “LHC First Physics” event of 30th March, the analysis of the O(200) million 7 TeV collision events in CMS accumulated during the first 60 days is well under way. The consistency of the CMS computing model has been confirmed during these first weeks of data taking. This model is based on a hierarchy of use-cases deployed between the different tiers and, in particular, the distribution of RECO data to T1s, who then serve data on request to T2s, along a topology known as “fat tree”. Indeed, during this period this model was further extended by almost full “mesh” commissioning, meaning that RECO data were shipped to T2s whenever possible, enabling additional physics analyses compared with the “fat tree” model. Computing activities at the CMS Analysis Facility (CAF) have been marked by a good time response for a load almost evenly shared between ALCA (Alignment and Calibration tasks - highest p...

  11. COMPUTING

    CERN Multimedia

    Contributions from I. Fisk

    2012-01-01

    Introduction The start of the 2012 run has been busy for Computing. We have reconstructed, archived, and served a larger sample of new data than in 2011, and we are in the process of producing an even larger new sample of simulations at 8 TeV. The running conditions and system performance are largely what was anticipated in the plan, thanks to the hard work and preparation of many people. Heavy ions Heavy Ions has been actively analysing data and preparing for conferences.  Operations Office Figure 6: Transfers from all sites in the last 90 days For ICHEP and the Upgrade efforts, we needed to produce and process record amounts of MC samples while supporting the very successful data-taking. This was a large burden, especially on the team members. Nevertheless the last three months were very successful and the total output was phenomenal, thanks to our dedicated site admins who keep the sites operational and the computing project members who spend countless hours nursing the...

  12. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction A large fraction of the effort was focused during the last period into the preparation and monitoring of the February tests of Common VO Computing Readiness Challenge 08. CCRC08 is being run by the WLCG collaboration in two phases, between the centres and all experiments. The February test is dedicated to functionality tests, while the May challenge will consist of running at all centres and with full workflows. For this first period, a number of functionality checks of the computing power, data repositories and archives as well as network links are planned. This will help assess the reliability of the systems under a variety of loads, and identifying possible bottlenecks. Many tests are scheduled together with other VOs, allowing the full scale stress test. The data rates (writing, accessing and transfer¬ring) are being checked under a variety of loads and operating conditions, as well as the reliability and transfer rates of the links between Tier-0 and Tier-1s. In addition, the capa...

  13. COMPUTING

    CERN Multimedia

    Matthias Kasemann

    Overview The main focus during the summer was to handle data coming from the detector and to perform Monte Carlo production. The lessons learned during the CCRC and CSA08 challenges in May were addressed by dedicated PADA campaigns lead by the Integration team. Big improvements were achieved in the stability and reliability of the CMS Tier1 and Tier2 centres by regular and systematic follow-up of faults and errors with the help of the Savannah bug tracking system. In preparation for data taking the roles of a Computing Run Coordinator and regular computing shifts monitoring the services and infrastructure as well as interfacing to the data operations tasks are being defined. The shift plan until the end of 2008 is being put together. User support worked on documentation and organized several training sessions. The ECoM task force delivered the report on “Use Cases for Start-up of pp Data-Taking” with recommendations and a set of tests to be performed for trigger rates much higher than the ...

  14. COMPUTING

    CERN Multimedia

    P. MacBride

    The Computing Software and Analysis Challenge CSA07 has been the main focus of the Computing Project for the past few months. Activities began over the summer with the preparation of the Monte Carlo data sets for the challenge and tests of the new production system at the Tier-0 at CERN. The pre-challenge Monte Carlo production was done in several steps: physics generation, detector simulation, digitization, conversion to RAW format and the samples were run through the High Level Trigger (HLT). The data was then merged into three "Soups": Chowder (ALPGEN), Stew (Filtered Pythia) and Gumbo (Pythia). The challenge officially started when the first Chowder events were reconstructed on the Tier-0 on October 3rd. The data operations teams were very busy during the the challenge period. The MC production teams continued with signal production and processing while the Tier-0 and Tier-1 teams worked on splitting the Soups into Primary Data Sets (PDS), reconstruction and skimming. The storage sys...

  15. COMPUTING

    CERN Multimedia

    I. Fisk

    2013-01-01

    Computing operation has been lower as the Run 1 samples are completing and smaller samples for upgrades and preparations are ramping up. Much of the computing activity is focusing on preparations for Run 2 and improvements in data access and flexibility of using resources. Operations Office Data processing was slow in the second half of 2013 with only the legacy re-reconstruction pass of 2011 data being processed at the sites.   Figure 1: MC production and processing was more in demand with a peak of over 750 Million GEN-SIM events in a single month.   Figure 2: The transfer system worked reliably and efficiently and transferred on average close to 520 TB per week with peaks at close to 1.2 PB.   Figure 3: The volume of data moved between CMS sites in the last six months   The tape utilisation was a focus for the operation teams with frequent deletion campaigns from deprecated 7 TeV MC GEN-SIM samples to INVALID datasets, which could be cleaned up...

  16. COMPUTING

    CERN Multimedia

    I. Fisk

    2012-01-01

      Introduction Computing activity has been running at a sustained, high rate as we collect data at high luminosity, process simulation, and begin to process the parked data. The system is functional, though a number of improvements are planned during LS1. Many of the changes will impact users, we hope only in positive ways. We are trying to improve the distributed analysis tools as well as the ability to access more data samples more transparently.  Operations Office Figure 2: Number of events per month, for 2012 Since the June CMS Week, Computing Operations teams successfully completed data re-reconstruction passes and finished the CMSSW_53X MC campaign with over three billion events available in AOD format. Recorded data was successfully processed in parallel, exceeding 1.2 billion raw physics events per month for the first time in October 2012 due to the increase in data-parking rate. In parallel, large efforts were dedicated to WMAgent development and integrati...

  17. Computer Simulation of Embryonic Systems: What can a virtual embryo teach us about developmental toxicity? (LA Conference on Computational Biology & Bioinformatics)

    Science.gov (United States)

    This presentation will cover work at EPA under the CSS program for: (1) Virtual Tissue Models built from the known biology of an embryological system and structured to recapitulate key cell signals and responses; (2) running the models with real (in vitro) or synthetic (in silico...

  18. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction The Computing Team successfully completed the storage, initial processing, and distribution for analysis of proton-proton data in 2011. There are still a variety of activities ongoing to support winter conference activities and preparations for 2012. Heavy ions The heavy-ion run for 2011 started in early November and has already demonstrated good machine performance and success of some of the more advanced workflows planned for 2011. Data collection will continue until early December. Facilities and Infrastructure Operations Operational and deployment support for WMAgent and WorkQueue+Request Manager components, routinely used in production by Data Operations, are provided. The GlideInWMS and components installation are now deployed at CERN, which is added to the GlideInWMS factory placed in the US. There has been new operational collaboration between the CERN team and the UCSD GlideIn factory operators, covering each others time zones by monitoring/debugging pilot jobs sent from the facto...

  19. COMPUTING

    CERN Multimedia

    M. Kasemann

    CMS relies on a well functioning, distributed computing infrastructure. The Site Availability Monitoring (SAM) and the Job Robot submission have been very instrumental for site commissioning in order to increase availability of more sites such that they are available to participate in CSA07 and are ready to be used for analysis. The commissioning process has been further developed, including "lessons learned" documentation via the CMS twiki. Recently the visualization, presentation and summarizing of SAM tests for sites has been redesigned, it is now developed by the central ARDA project of WLCG. Work to test the new gLite Workload Management System was performed; a 4 times increase in throughput with respect to LCG Resource Broker is observed. CMS has designed and launched a new-generation traffic load generator called "LoadTest" to commission and to keep exercised all data transfer routes in the CMS PhE-DEx topology. Since mid-February, a transfer volume of about 12 P...

  20. Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

    Directory of Open Access Journals (Sweden)

    Guégan Jean-François

    2008-10-01

    Full Text Available Abstract Background Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems. Results Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment. Conclusion Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.

  1. And So It Grows: Using a Computer-Based Simulation of a Population Growth Model to Integrate Biology & Mathematics

    Science.gov (United States)

    Street, Garrett M.; Laubach, Timothy A.

    2013-01-01

    We provide a 5E structured-inquiry lesson so that students can learn more of the mathematics behind the logistic model of population biology. By using models and mathematics, students understand how population dynamics can be influenced by relatively simple changes in the environment.

  2. Progress in Computational Physics (PiCP) Vol 2 Coupled Fluid Flow in Energy, Biology and Environmental Research

    CERN Document Server

    Ehrhardt, Matthias

    2012-01-01

    This second volume contains both, the mathematical analysis of the coupling between fluid flow and porous media flow and state-of-the art numerical techniques, like tailor-made finite element and finite volume methods. Readers will come across articles devoted to concrete applications of these models in the field of energy, biology and environmental research.

  3. Synthesis and biological evaluation of the progenitor of a new class of cephalosporin analogues, with a particular focus on structure-based computational analysis.

    Directory of Open Access Journals (Sweden)

    Anna Verdino

    Full Text Available We present the synthesis and biological evaluation of the prototype of a new class of cephalosporins, containing an additional isolated beta lactam ring with two phenyl substituents. This new compound is effective against Gram positive microorganisms, with a potency similar to that of ceftriaxone, a cephalosporin widely used in clinics and taken as a reference, and with no cytotoxicity against two different human cell lines, even at a concentration much higher than the minimal inhibitory concentration tested. Additionally, a deep computational analysis has been conducted with the aim of understanding the contribution of its moieties to the binding energy towards several penicillin-binding proteins from both Gram positive and Gram negative bacteria. All these results will help us developing derivatives of this compound with improved chemical and biological properties, such as a broader spectrum of action and/or an increased affinity towards their molecular targets.

  4. Automated interpretable computational biology in the clinic: a framework to predict disease severity and stratify patients from clinical data

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2017-10-01

    Full Text Available We outline an automated computational and machine learning framework that predicts disease severity and stratifies patients. We apply our framework to available clinical data. Our algorithm automatically generates insights and predicts disease severity with minimal operator intervention. The computational framework presented here can be used to stratify patients, predict disease severity and propose novel biomarkers for disease. Insights from machine learning algorithms coupled with clinical data may help guide therapy, personalize treatment and help clinicians understand the change in disease over time. Computational techniques like these can be used in translational medicine in close collaboration with clinicians and healthcare providers. Our models are also interpretable, allowing clinicians with minimal machine learning experience to engage in model building. This work is a step towards automated machine learning in the clinic.

  5. Computer-aided discovery of biological activity spectra for anti-aging and anti-cancer olive oil oleuropeins

    OpenAIRE

    Menendez, J.A.; García, J.; Segura-Carretero, A.; Ariza, X.; Joven, J.; Micol, V.; Cuyàs, E.; Santangelo, E.; Corominas-Faja, B.

    2014-01-01

    Aging is associated with common conditions, including cancer, diabetes, cardiovascular disease, and Alzheimer's disease. The type of multi-targeted pharmacological approach necessary to address a complex multifaceted disease such as aging might take advantage of pleiotropic natural polyphenols affecting a wide variety of biological processes. We have recently postulated that the secoiridoids oleuropein aglycone (OA) and decarboxymethyl oleuropein aglycone (DOA), two complex polyphenols presen...

  6. Computer-aided discovery of biological activity spectra for anti-aging and anti-cancer olive oil oleuropeins.

    Science.gov (United States)

    Corominas-Faja, Bruna; Santangelo, Elvira; Cuyàs, Elisabet; Micol, Vicente; Joven, Jorge; Ariza, Xavier; Segura-Carretero, Antonio; García, Jordi; Menendez, Javier A

    2014-09-01

    Aging is associated with common conditions, including cancer, diabetes, cardiovascular disease, and Alzheimer's disease. The type of multi-targeted pharmacological approach necessary to address a complex multifaceted disease such as aging might take advantage of pleiotropic natural polyphenols affecting a wide variety of biological processes. We have recently postulated that the secoiridoids oleuropein aglycone (OA) and decarboxymethyl oleuropein aglycone (DOA), two complex polyphenols present in health-promoting extra virgin olive oil (EVOO), might constitute a new family of plant-produced gerosuppressant agents. This paper describes an analysis of the biological activity spectra (BAS) of OA and DOA using PASS (Prediction of Activity Spectra for Substances) software. PASS can predict thousands of biological activities, as the BAS of a compound is an intrinsic property that is largely dependent on the compound's structure and reflects pharmacological effects, physiological and biochemical mechanisms of action, and specific toxicities. Using Pharmaexpert, a tool that analyzes the PASS-predicted BAS of substances based on thousands of "mechanism-effect" and "effect-mechanism" relationships, we illuminate hypothesis-generating pharmacological effects, mechanisms of action, and targets that might underlie the anti-aging/anti-cancer activities of the gerosuppressant EVOO oleuropeins.

  7. Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches.

    Directory of Open Access Journals (Sweden)

    Abbas Khan

    Full Text Available High-risk human papillomaviruses (hrHPVs are the most prevalent viruses in human diseases including cervical cancers. Expression of E6 protein has already been reported in cervical cancer cases, excluding normal tissues. Continuous expression of E6 protein is making it ideal to develop therapeutic vaccines against hrHPVs infection and cervical cancer. Therefore, we carried out a meta-analysis of multiple hrHPVs to predict the most potential prophylactic peptide vaccines. In this study, immunoinformatics approach was employed to predict antigenic epitopes of hrHPVs E6 proteins restricted to 12 Human HLAs to aid the development of peptide vaccines against hrHPVs. Conformational B-cell and CTL epitopes were predicted for hrHPVs E6 proteins using ElliPro and NetCTL. The potential of the predicted peptides were tested and validated by using systems biology approach considering experimental concentration. We also investigated the binding interactions of the antigenic CTL epitopes by using docking. The stability of the resulting peptide-MHC I complexes was further studied by molecular dynamics simulations. The simulation results highlighted the regions from 46-62 and 65-76 that could be the first choice for the development of prophylactic peptide vaccines against hrHPVs. To overcome the worldwide distribution, the predicted epitopes restricted to different HLAs could cover most of the vaccination and would help to explore the possibility of these epitopes for adaptive immunotherapy against HPVs infections.

  8. A computer program for monitoring the biological treatment of waste waters (CDBAR); Programa informatico para el control de la depuracion biologica de aguas residuales (CDBAR)

    Energy Technology Data Exchange (ETDEWEB)

    Bove Porta, J.; Milan Cabre, D.

    2001-07-01

    The problems, such as bulking, foaming, etc., involved in managing a waste water treatment plant (WWTP) employing an activated sludge biological process have a biochemical origin. Correcting them requires identifying the micro-organisms responsible for the pathology in question, whether the problems are due to there being too many or too few of these organisms. It is therefore necessary to have a good microscope and staff trained in identifying such micro-organisms. Never the less, to attain speed and efficiency, it is necessary to have more means. That is why the CDBAR project was carried out. This is a simple computer application that includes numerous photographs of microscopic organisms from samples taken in Spain and Portugal. Once the anomaly has been identified, the computer application it-self includes a program of corrective actions that will allow the biological reactor, the most important part of a WWTP, to function normally. Finally, a glossary has been prepared so that the meaning of any term can be looked up quickly and easily. (Author) 16 refs.

  9. COMPUTER TESTING AS A METHOD FOR ESTIMATION OF ACADEMIC ACHIEVEMENTS OF STUDENTS ON BIOLOGICAL CHEMISTRY IN MEDICAL UNIVERSITIES

    Directory of Open Access Journals (Sweden)

    Petushok N. E.

    2018-05-01

    Full Text Available Background. Assessment of students' knowledge is one of the key tasks of any educational system. The aim of the study is to identify the significance of testing in a multipurpose system of means of assessing students' knowledge. Material and methods. Statistic analysis of the relationship of the results of computer testing, the examination score and the average annual score. Results. A positive correlation was revealed between all pairs of the compared indicators. For students of the Faculty of General Medicine high strength of relationship was noted for the average annual score ↔ examination score and testing ↔ examination score. For students of the Medical Faculty for International Students, the tendencies of interdependence of the indicators are similar, the strength of relationship is less pronounced. Conclusions. Computer testing should be used in complex with other tools of assessment of academic achievements.

  10. Synthesis of N-(6-Arylbenzo[d]thiazole-2-acetamide Derivatives and Their Biological Activities: An Experimental and Computational Approach.

    Science.gov (United States)

    Gull, Yasmeen; Rasool, Nasir; Noreen, Mnaza; Altaf, Ataf Ali; Musharraf, Syed Ghulam; Zubair, Muhammad; Nasim, Faiz-Ul-Hassan; Yaqoob, Asma; DeFeo, Vincenzo; Zia-Ul-Haq, Muhammad

    2016-02-25

    A new series of N-(6-arylbenzo[d]thiazol-2-yl)acetamides were synthesized by C-C coupling methodology in the presence of Pd(0) using various aryl boronic pinacol ester/acids. The newly synthesized compounds were evaluated for various biological activities like antioxidant, haemolytic, antibacterial and urease inhibition. In bioassays these compounds were found to have moderate to good activities. Among the tested biological activities screened these compounds displayed the most significant activity for urease inhibition. In urease inhibition, all compounds were found more active than the standard used. The compound N-(6-(p-tolyl)benzo[d]thiazol-2-yl)acetamide was found to be the most active. To understand this urease inhibition, molecular docking studies were performed. The in silico studies showed that these acetamide derivatives bind to the non-metallic active site of the urease enzyme. Structure-activity studies revealed that H-bonding of compounds with the enzyme is important for its inhibition.

  11. Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

    Science.gov (United States)

    Nadkarni, P M; Miller, P L

    1991-01-01

    A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

  12. BioWires: Conductive DNA Nanowires in a Computationally-Optimized, Synthetic Biological Platform for Nanoelectronic Fabrication

    Science.gov (United States)

    Vecchioni, Simon; Toomey, Emily; Capece, Mark C.; Rothschild, Lynn; Wind, Shalom

    2017-01-01

    DNA is an ideal template for a biological nanowire-it has a linear structure several atoms thick; it possesses addressable nucleobase geometry that can be precisely defined; and it is massively scalable into branched networks. Until now, the drawback of DNA as a conducting nanowire been, simply put, its low conductance. To address this deficiency, we extensively characterize a chemical variant of canonical DNA that exploits the affinity of natural cytosine bases for silver ions. We successfully construct chains of single silver ions inside double-stranded DNA, confirm the basic dC-Ag+-dC bond geometry and kinetics, and show length-tunability dependent on mismatch distribution, ion availability and enzyme activity. An analysis of the absorbance spectra of natural DNA and silver-binding, poly-cytosine DNA demonstrates the heightened thermostability of the ion chain and its resistance to aqueous stresses such as precipitation, dialysis and forced reduction. These chemically critical traits lend themselves to an increase in electrical conductivity of over an order of magnitude for 11-base silver-paired duplexes over natural strands when assayed by STM break junction. We further construct and implement a genetic pathway in the E. coli bacterium for the biosynthesis of highly ionizable DNA sequences. Toward future circuits, we construct a model of transcription network architectures to determine the most efficient and robust connectivity for cell-based fabrication, and we perform sequence optimization with a genetic algorithm to identify oligonucleotides robust to changes in the base-pairing energy landscape. We propose that this system will serve as a synthetic biological fabrication platform for more complex DNA nanotechnology and nanoelectronics with applications to deep space and low resource environments.

  13. Computational biomechanics

    International Nuclear Information System (INIS)

    Ethier, C.R.

    2004-01-01

    Computational biomechanics is a fast-growing field that integrates modern biological techniques and computer modelling to solve problems of medical and biological interest. Modelling of blood flow in the large arteries is the best-known application of computational biomechanics, but there are many others. Described here is work being carried out in the laboratory on the modelling of blood flow in the coronary arteries and on the transport of viral particles in the eye. (author)

  14. Computational investigation and synthesis of a sol-gel imprinted material for sensing application of some biologically active molecules

    Energy Technology Data Exchange (ETDEWEB)

    Atta, Nada F., E-mail: Nada_fah1@yahoo.com [Department of Chemistry, Faculty of Science, University of Cairo, Post Code 12613, Giza (Egypt); Hamed, Maher M.; Abdel-Mageed, Ali M. [Department of Chemistry, Faculty of Science, University of Cairo, Post Code 12613, Giza (Egypt)

    2010-05-14

    A hybrid sol-gel material was molecularly imprinted with a group of neurotransmitters. Imprinted material is a sol-gel thin film that is spin coated on the surface of a glassy carbon electrode. Imprinted films were characterized electrochemically using cyclic voltammetry (CV) and the encapsulated molecules were extracted from the films and complementary molecular cavities are formed that enable their rebind. The films were tested in their corresponding template solutions for rebinding using square wave voltammetry (SWV). Computational approach for exploring the primary intermolecular forces between templates and hydrolyzed form of the precursor monomer, tetraethylorthosilicate (TEOS), were carried out using Hartree-Fock method (HF). Interaction energy values were computed for each adduct formed between a monomer and a template. Analysis of the optimized conformations of various adducts could explain the mode of interaction between the templates and the monomer units. We found that interaction via the amino group is the common mode among the studied compounds and the results are in good agreement with the electrochemical measurements.

  15. Trial-by-Trial Modulation of Associative Memory Formation by Reward Prediction Error and Reward Anticipation as Revealed by a Biologically Plausible Computational Model.

    Science.gov (United States)

    Aberg, Kristoffer C; Müller, Julia; Schwartz, Sophie

    2017-01-01

    Anticipation and delivery of rewards improves memory formation, but little effort has been made to disentangle their respective contributions to memory enhancement. Moreover, it has been suggested that the effects of reward on memory are mediated by dopaminergic influences on hippocampal plasticity. Yet, evidence linking memory improvements to actual reward computations reflected in the activity of the dopaminergic system, i.e., prediction errors and expected values, is scarce and inconclusive. For example, different previous studies reported that the magnitude of prediction errors during a reinforcement learning task was a positive, negative, or non-significant predictor of successfully encoding simultaneously presented images. Individual sensitivities to reward and punishment have been found to influence the activation of the dopaminergic reward system and could therefore help explain these seemingly discrepant results. Here, we used a novel associative memory task combined with computational modeling and showed independent effects of reward-delivery and reward-anticipation on memory. Strikingly, the computational approach revealed positive influences from both reward delivery, as mediated by prediction error magnitude, and reward anticipation, as mediated by magnitude of expected value, even in the absence of behavioral effects when analyzed using standard methods, i.e., by collapsing memory performance across trials within conditions. We additionally measured trait estimates of reward and punishment sensitivity and found that individuals with increased reward (vs. punishment) sensitivity had better memory for associations encoded during positive (vs. negative) prediction errors when tested after 20 min, but a negative trend when tested after 24 h. In conclusion, modeling trial-by-trial fluctuations in the magnitude of reward, as we did here for prediction errors and expected value computations, provides a comprehensive and biologically plausible description of

  16. Catabolite regulation analysis of Escherichia coli for acetate overflow mechanism and co-consumption of multiple sugars based on systems biology approach using computer simulation.

    Science.gov (United States)

    Matsuoka, Yu; Shimizu, Kazuyuki

    2013-10-20

    It is quite important to understand the basic principle embedded in the main metabolism for the interpretation of the fermentation data. For this, it may be useful to understand the regulation mechanism based on systems biology approach. In the present study, we considered the perturbation analysis together with computer simulation based on the models which include the effects of global regulators on the pathway activation for the main metabolism of Escherichia coli. Main focus is the acetate overflow metabolism and the co-fermentation of multiple carbon sources. The perturbation analysis was first made to understand the nature of the feed-forward loop formed by the activation of Pyk by FDP (F1,6BP), and the feed-back loop formed by the inhibition of Pfk by PEP in the glycolysis. Those together with the effect of transcription factor Cra caused by FDP level affected the glycolysis activity. The PTS (phosphotransferase system) acts as the feed-back system by repressing the glucose uptake rate for the increase in the glucose uptake rate. It was also shown that the increased PTS flux (or glucose consumption rate) causes PEP/PYR ratio to be decreased, and EIIA-P, Cya, cAMP-Crp decreased, where cAMP-Crp in turn repressed TCA cycle and more acetate is formed. This was further verified by the detailed computer simulation. In the case of multiple carbon sources such as glucose and xylose, it was shown that the sequential utilization of carbon sources was observed for wild type, while the co-consumption of multiple carbon sources with slow consumption rates were observed for the ptsG mutant by computer simulation, and this was verified by experiments. Moreover, the effect of a specific gene knockout such as Δpyk on the metabolic characteristics was also investigated based on the computer simulation. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. Stereoselective synthesis, X-ray analysis, computational studies and biological evaluation of new thiazole derivatives as potential anticancer agents.

    Science.gov (United States)

    Mabkhot, Yahia N; Alharbi, Mohammed M; Al-Showiman, Salim S; Ghabbour, Hazem A; Kheder, Nabila A; Soliman, Saied M; Frey, Wolfgang

    2018-05-11

    The synthesis of new thiazole derivatives is very important because of their diverse biological activities. Also , many drugs containing thiazole ring in their skeletons are available in the market such as Abafungin, Acotiamide, Alagebrium, Amiphenazole, Brecanavir, Carumonam, Cefepime, and Cefmatilen. Ethyl cyanoacetate reacted with phenylisothiocyanate, chloroacetone, in two different basic mediums to afford the thiazole derivative 6, which reacted with dimethylformamide- dimethyl acetal in the presence of DMF to afford the unexpected thiazole derivative 11. The structures of the thiazoles 6 and 11 were optimized using B3LYP/6-31G(d,p) method. The experimentally and theoretically geometric parameters agreed very well. Also, the natural charges at the different atomic sites were predicted. HOMO and LUMO demands were discussed. The anticancer activity of the prepared compounds was evaluated and showed moderate activity. Synthesis of novel thiazole derivatives was done. The structure was established using X-ray and spectral analysis. Optimized molecular structures at the B3LYP/6-31G(d,p) level were investigated. Thiazole derivative 11 has more electropositive S-atom than thiazole 6. The HOMO-LUMO energy gap is lower in the former compared to the latter. The synthesized compounds showed moderate anticancer activity.

  18. Experimental verification of stopping-power prediction from single- and dual-energy computed tomography in biological tissues

    Science.gov (United States)

    Möhler, Christian; Russ, Tom; Wohlfahrt, Patrick; Elter, Alina; Runz, Armin; Richter, Christian; Greilich, Steffen

    2018-01-01

    An experimental setup for consecutive measurement of ion and x-ray absorption in tissue or other materials is introduced. With this setup using a 3D-printed sample container, the reference stopping-power ratio (SPR) of materials can be measured with an uncertainty of below 0.1%. A total of 65 porcine and bovine tissue samples were prepared for measurement, comprising five samples each of 13 tissue types representing about 80% of the total body mass (three different muscle and fatty tissues, liver, kidney, brain, heart, blood, lung and bone). Using a standard stoichiometric calibration for single-energy CT (SECT) as well as a state-of-the-art dual-energy CT (DECT) approach, SPR was predicted for all tissues and then compared to the measured reference. With the SECT approach, the SPRs of all tissues were predicted with a mean error of (-0.84  ±  0.12)% and a mean absolute error of (1.27  ±  0.12)%. In contrast, the DECT-based SPR predictions were overall consistent with the measured reference with a mean error of (-0.02  ±  0.15)% and a mean absolute error of (0.10  ±  0.15)%. Thus, in this study, the potential of DECT to decrease range uncertainty could be confirmed in biological tissue.

  19. Application of a computer model to predict optimum slaughter end points for different biological types of feeder cattle.

    Science.gov (United States)

    Williams, C B; Bennett, G L

    1995-10-01

    A bioeconomic model was developed to predict slaughter end points of different genotypes of feeder cattle, where profit/rotation and profit/day were maximized. Growth, feed intake, and carcass weight and composition were simulated for 17 biological types of steers. Distribution of carcass weight and proportion in four USDA quality and five USDA yield grades were obtained from predicted carcass weights and composition. Average carcass value for each genotype was calculated from these distributions under four carcass pricing systems that varied from value determined on quality grade alone to value determined on yield grade alone. Under profitable market conditions, rotation length was shorter and carcass weights lighter when the producer's goal was maximum profit/day, compared with maximum profit/rotation. A carcass value system based on yield grade alone resulted in greater profit/rotation and in lighter and leaner carcasses than a system based on quality grade alone. High correlations ( > .97) were obtained between breed profits obtained with different sets of input/output prices and carcass price discount weight ranges. This suggests that breed rankings on the basis of breed profits may not be sensitive to changes in input/output market prices. Steers that were on a grower-stocker system had leaner carcasses, heavier optimum carcass weight, greater profits, and less variation in optimum carcass weights between genotypes than steers that were started on a high-energy finishing diet at weaning. Overall results suggest that breed choices may change with different carcass grading and value systems and postweaning production systems. This model has potential to provide decision support in marketing fed cattle.

  20. Effects of degraded sensory input on memory for speech: behavioral data and a test of biologically constrained computational models.

    Science.gov (United States)

    Piquado, Tepring; Cousins, Katheryn A Q; Wingfield, Arthur; Miller, Paul

    2010-12-13

    Poor hearing acuity reduces memory for spoken words, even when the words are presented with enough clarity for correct recognition. An "effortful hypothesis" suggests that the perceptual effort needed for recognition draws from resources that would otherwise be available for encoding the word in memory. To assess this hypothesis, we conducted a behavioral task requiring immediate free recall of word-lists, some of which contained an acoustically masked word that was just above perceptual threshold. Results show that masking a word reduces the recall of that word and words prior to it, as well as weakening the linking associations between the masked and prior words. In contrast, recall probabilities of words following the masked word are not affected. To account for this effect we conducted computational simulations testing two classes of models: Associative Linking Models and Short-Term Memory Buffer Models. Only a model that integrated both contextual linking and buffer components matched all of the effects of masking observed in our behavioral data. In this Linking-Buffer Model, the masked word disrupts a short-term memory buffer, causing associative links of words in the buffer to be weakened, affecting memory for the masked word and the word prior to it, while allowing links of words following the masked word to be spared. We suggest that these data account for the so-called "effortful hypothesis", where distorted input has a detrimental impact on prior information stored in short-term memory. Copyright © 2010 Elsevier B.V. All rights reserved.

  1. Advanced computational biology methods identify molecular switches for malignancy in an EGF mouse model of liver cancer.

    Directory of Open Access Journals (Sweden)

    Philip Stegmaier

    Full Text Available The molecular causes by which the epidermal growth factor receptor tyrosine kinase induces malignant transformation are largely unknown. To better understand EGFs' transforming capacity whole genome scans were applied to a transgenic mouse model of liver cancer and subjected to advanced methods of computational analysis to construct de novo gene regulatory networks based on a combination of sequence analysis and entrained graph-topological algorithms. Here we identified transcription factors, processes, key nodes and molecules to connect as yet unknown interacting partners at the level of protein-DNA interaction. Many of those could be confirmed by electromobility band shift assay at recognition sites of gene specific promoters and by western blotting of nuclear proteins. A novel cellular regulatory circuitry could therefore be proposed that connects cell cycle regulated genes with components of the EGF signaling pathway. Promoter analysis of differentially expressed genes suggested the majority of regulated transcription factors to display specificity to either the pre-tumor or the tumor state. Subsequent search for signal transduction key nodes upstream of the identified transcription factors and their targets suggested the insulin-like growth factor pathway to render the tumor cells independent of EGF receptor activity. Notably, expression of IGF2 in addition to many components of this pathway was highly upregulated in tumors. Together, we propose a switch in autocrine signaling to foster tumor growth that was initially triggered by EGF and demonstrate the knowledge gain form promoter analysis combined with upstream key node identification.

  2. Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C. [Case Western Reserve Univ., Cleveland, OH (United States)

    1991-11-01

    This thesis involved the construction of (1) a grammar that incorporates knowledge on base invariancy and secondary structure in a molecule and (2) a parser engine that uses the grammar to position bases into the structural subunits of the molecule. These concepts were combined with a novel pinning technique to form a tool that semi-automates insertion of a new species into the alignment for the 16S rRNA molecule (a component of the ribosome) maintained by Dr. Carl Woese`s group at the University of Illinois at Urbana. The tool was tested on species extracted from the alignment and on a group of entirely new species. The results were very encouraging, and the tool should be substantial aid to the curators of the 16S alignment. The construction of the grammar was itself automated, allowing application of the tool to alignments for other molecules. The logic programming language Prolog was used to construct all programs involved. The computational linguistics approach used here was found to be a useful way to attach the problem of insertion into an alignment.

  3. Automated insertion of sequences into a ribosomal RNA alignment: An application of computational linguistics in molecular biology

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, R.C.

    1991-11-01

    This thesis involved the construction of (1) a grammar that incorporates knowledge on base invariancy and secondary structure in a molecule and (2) a parser engine that uses the grammar to position bases into the structural subunits of the molecule. These concepts were combined with a novel pinning technique to form a tool that semi-automates insertion of a new species into the alignment for the 16S rRNA molecule (a component of the ribosome) maintained by Dr. Carl Woese's group at the University of Illinois at Urbana. The tool was tested on species extracted from the alignment and on a group of entirely new species. The results were very encouraging, and the tool should be substantial aid to the curators of the 16S alignment. The construction of the grammar was itself automated, allowing application of the tool to alignments for other molecules. The logic programming language Prolog was used to construct all programs involved. The computational linguistics approach used here was found to be a useful way to attach the problem of insertion into an alignment.

  4. Spectro Analytical, Computational and In Vitro Biological Studies of Novel Substituted Quinolone Hydrazone and it's Metal Complexes.

    Science.gov (United States)

    Nagula, Narsimha; Kunche, Sudeepa; Jaheer, Mohmed; Mudavath, Ravi; Sivan, Sreekanth; Ch, Sarala Devi

    2018-01-01

    Some novel transition metal [Cu (II), Ni (II) and Co (II)] complexes of nalidixic acid hydrazone have been prepared and characterized by employing spectro-analytical techniques viz: elemental analysis, 1 H-NMR, Mass, UV-Vis, IR, TGA-DTA, SEM-EDX, ESR and Spectrophotometry studies. The HyperChem 7.5 software was used for geometry optimization of title compound in its molecular and ionic forms. Quantum mechanical parameters, contour maps of highest occupied molecular orbitals (HOMO) and lowest unoccupied molecular orbitals (LUMO) and corresponding binding energy values were computed using semi empirical single point PM3 method. The stoichiometric equilibrium studies of metal complexes carried out spectrophotometrically using Job's continuous variation and mole ratio methods inferred formation of 1:2 (ML 2 ) metal complexes in respective systems. The title compound and its metal complexes screened for antibacterial and antifungal properties, exemplified improved activity in metal complexes. The studies of nuclease activity for the cleavage of CT- DNA and MTT assay for in vitro cytotoxic properties involving metal complexes exhibited high activity. In addition, the DNA binding properties of Cu (II), Ni (II) and Co (II) complexes investigated by electronic absorption and fluorescence measurements revealed their good binding ability and commended agreement of K b values obtained from both the techniques. Molecular docking studies were also performed to find the binding affinity of synthesized compounds with DNA (PDB ID: 1N37) and "Thymidine phosphorylase from E.coli" (PDB ID: 4EAF) protein targets.

  5. A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

    Science.gov (United States)

    Zhao, Lei; Gossmann, Toni I; Waxman, David

    2016-03-21

    The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have

  6. An integrated methodological approach to the computer-assisted gas chromatographic screening of basic drugs in biological fluids using nitrogen selective detection.

    Science.gov (United States)

    Dugal, R; Massé, R; Sanchez, G; Bertrand, M J

    1980-01-01

    This paper presents the methodological aspects of a computerized system for the gas-chromatographic screening and primary identification of central nervous system stimulants and narcotic analgesics (including some of their respective metabolites) extracted from urine. The operating conditions of a selective nitrogen detector for optimized analytical functions are discussed, particularly the effect of carrier and fuel gas on the detector's sensitivity to nitrogen-containing molecules and discriminating performance toward biological matrix interferences. Application of simple extraction techniques, combined with rapid derivatization procedures, computer data acquisition, and reduction of chromatographic data are presented. Results show that this system approach allows for the screening of several drugs and their metabolites in a short amount of time. The reliability and stability of the system have been tested by analyzing several thousand samples for doping control at major international sporting events and for monitoring drug intake in addicts participating in a rehabilitation program. Results indicate that these techniques can be used and adapted to many different analytical toxicology situations.

  7. Impacts of biological and procedural factors on semiquantification uptake value of liver in fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography imaging.

    Science.gov (United States)

    Mahmud, Mohd Hafizi; Nordin, Abdul Jalil; Ahmad Saad, Fathinul Fikri; Azman, Ahmad Zaid Fattah

    2015-10-01

    Increased metabolic activity of fluorodeoxyglucose (FDG) in tissue is not only resulting of pathological uptake, but due to physiological uptake as well. This study aimed to determine the impacts of biological and procedural factors on FDG uptake of liver in whole body positron emission tomography/computed tomography (PET/CT) imaging. Whole body fluorine-18 ((18)F) FDG PET/CT scans of 51 oncology patients have been reviewed. Maximum standardized uptake value (SUVmax) of lesion-free liver was quantified in each patient. Pearson correlation was performed to determine the association between the factors of age, body mass index (BMI), blood glucose level, FDG dose and incubation period and liver SUVmax. Multivariate regression analysis was established to determine the significant factors that best predicted the liver SUVmax. Then the subjects were dichotomised into four BMI groups. Analysis of variance (ANOVA) was established for mean difference of SUVmax of liver between those BMI groups. BMI and incubation period were significantly associated with liver SUVmax. These factors were accounted for 29.6% of the liver SUVmax variance. Statistically significant differences were observed in the mean SUVmax of liver among those BMI groups (Pvalue for physiological liver SUVmax as a reference standard for different BMI of patients in PET/CT interpretation and use a standard protocol for incubation period of patient to reduce variation in physiological FDG uptake of liver in PET/CT study.

  8. Organic Computing

    CERN Document Server

    Würtz, Rolf P

    2008-01-01

    Organic Computing is a research field emerging around the conviction that problems of organization in complex systems in computer science, telecommunications, neurobiology, molecular biology, ethology, and possibly even sociology can be tackled scientifically in a unified way. From the computer science point of view, the apparent ease in which living systems solve computationally difficult problems makes it inevitable to adopt strategies observed in nature for creating information processing machinery. In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system, insect swarms, and ant colonies. Applications are as diverse as system design, optimization, artificial growth, task allocation, clustering, routing, face recognition, and sign language understanding.

  9. The Anatomical Biological Value on Pretreatment (18)F-fluorodeoxyglucose Positron Emission Tomography Computed Tomography Predicts Response and Survival in Locally Advanced Head and Neck Cancer.

    Science.gov (United States)

    Ashamalla, Hani; Mattes, Malcolm; Guirguis, Adel; Zaidi, Arifa; Mokhtar, Bahaa; Tejwani, Ajay

    2014-05-01

    (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) has become increasingly relevant in the staging of head and neck cancers, but its prognostic value is controversial. The objective of this study was to evaluate different PET/CT parameters for their ability to predict response to therapy and survival in patients treated for head and neck cancer. A total of 28 consecutive patients with a variety of newly diagnosed head and neck cancers underwent PET/CT scanning at our institution before initiating definitive radiation therapy. All underwent a posttreatment PET/CT to gauge tumor response. Pretreatment PET/CT parameters calculated include the standardized uptake value (SUV) and the anatomical biological value (ABV), which is the product of SUV and greatest tumor diameter. Maximum and mean values were studied for both SUV and ABV, and correlated with response rate and survival. The mean pretreatment tumor ABVmax decreased from 35.5 to 7.9 (P = 0.0001). Of the parameters tested, only pretreatment ABVmax was significantly different among those patients with a complete response (CR) and incomplete response (22.8 vs. 65, respectively, P = 0.021). This difference was maximized at a cut-off ABVmax of 30 and those patients with ABVmax < 30 were significantly more likely to have a CR compared to those with ABVmax of ≥ 30 (93.8% vs. 50%, respectively, P = 0.023). The 5-year overall survival was 80% compared to 36%, respectively, (P = 0.028). Multivariate analysis confirmed that ABVmax was an independent prognostic factor. Our data supports the use of PET/CT, and specifically ABVmax, as a prognostic factor in head and neck cancer. Patients who have an ABVmax ≥ 30 were more likely to have a poor outcome with chemoradiation alone, and a more aggressive trimodality approach may be indicated in these patients.

  10. Micro-computed tomography of pulmonary fibrosis in mice induced by adenoviral gene transfer of biologically active transforming growth factor-β1

    Directory of Open Access Journals (Sweden)

    Gauldie Jack

    2010-12-01

    Full Text Available Abstract Background Micro-computed tomography (micro-CT is a novel tool for monitoring acute and chronic disease states in small laboratory animals. Its value for assessing progressive lung fibrosis in mice has not been reported so far. Here we examined the importance of in vivo micro-CT as non-invasive tool to assess progression of pulmonary fibrosis in mice over time. Methods Pulmonary fibrosis was induced in mice by intratracheal delivery of an adenoviral gene vector encoding biologically active TGF-ß1 (AdTGF-ß1. Respiratory gated and ungated micro-CT scans were performed at 1, 2, 3, and 4 weeks post pulmonary adenoviral gene or control vector delivery, and were then correlated with respective histopathology-based Ashcroft scoring of pulmonary fibrosis in mice. Visual assessment of image quality and consolidation was performed by 3 observers and a semi-automated quantification algorithm was applied to quantify aerated pulmonary volume as an inverse surrogate marker for pulmonary fibrosis. Results We found a significant correlation between classical Ashcroft scoring and micro-CT assessment using both visual assessment and the semi-automated quantification algorithm. Pulmonary fibrosis could be clearly detected in micro-CT, image quality values were higher for respiratory gated exams, although differences were not significant. For assessment of fibrosis no significant difference between respiratory gated and ungated exams was observed. Conclusions Together, we show that micro-CT is a powerful tool to assess pulmonary fibrosis in mice, using both visual assessment and semi-automated quantification algorithms. These data may be important in view of pre-clinical pharmacologic interventions for the treatment of lung fibrosis in small laboratory animals.

  11. Spatial Modeling Tools for Cell Biology

    National Research Council Canada - National Science Library

    Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

    2006-01-01

    .... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

  12. Multiscale Biological Materials

    DEFF Research Database (Denmark)

    Frølich, Simon

    of multiscale biological systems have been investigated and new research methods for automated Rietveld refinement and diffraction scattering computed tomography developed. The composite nature of biological materials was investigated at the atomic scale by looking at the consequences of interactions between...

  13. Computer prediction of biological activity of 2-methyl(phenyl-6,9-epoksybenzo[g]quinoline-4,5,10-Trion and 5-methyl-(1,2,4-triazolo[4,3-a] quinoline

    Directory of Open Access Journals (Sweden)

    Yu. V. Karpenko

    2015-04-01

    Full Text Available , One of the priority measures, which are evaluated in the creation of new effective medicines, is their high selective effect and lack of side effects. A considerable interest is the possibility of combining several structures of heterocycles in one molecule, such as quinoline and furan, which may cause an increase in biological activity of these combined compounds or an emergence of new properties. It is known that derivatives of 1,2,4-triazolo[4,3-a]quinoline have anticonvulsant effect and treat the syndrome of disorders with the nervous system. The aim of research. The main purpose of this work was an establishment of combinatorial library of bioregulators, which combines structures 5,8-dioksoquinoline and furan (1-8, quinoline and triazole (9-12, using computer program PASS (Prediction Activitity Spectra for Substances. Virtual screening of heterocycles derivatives was conducted to determine the direction of their bioactivity researches. Materials and methods. The virtual screening of compounds was performed by using the computer program PASS (Prediction Activity Spectra for Substances. For the specific activity the increase of Pa quantity and the decrease of the Pi quantity, helps to get the greater chance to detect this activity in the experiment. Predicting the probability of substance manifestation of specific types of biological activity determines which tests are the most appropriate for studying the biological activity of specific chemical substances and which substances of those that are available to the researcher likely will show the desired effect. With theoretical prediction the most likely basic structures of new compounds with desired biological effect, which best suits the task will be selected. Results. Analysis of computer prediction demonstrates the promising search of antineoplastic, antibiotic, analgesic and other types of activity in some of these compounds. An important instant of prediction of these substances is

  14. Quantum biological information theory

    CERN Document Server

    Djordjevic, Ivan B

    2016-01-01

    This book is a self-contained, tutorial-based introduction to quantum information theory and quantum biology. It serves as a single-source reference to the topic for researchers in bioengineering, communications engineering, electrical engineering, applied mathematics, biology, computer science, and physics. The book provides all the essential principles of the quantum biological information theory required to describe the quantum information transfer from DNA to proteins, the sources of genetic noise and genetic errors as well as their effects. Integrates quantum information and quantum biology concepts; Assumes only knowledge of basic concepts of vector algebra at undergraduate level; Provides a thorough introduction to basic concepts of quantum information processing, quantum information theory, and quantum biology; Includes in-depth discussion of the quantum biological channel modelling, quantum biological channel capacity calculation, quantum models of aging, quantum models of evolution, quantum models o...

  15. ACToR-AGGREGATED COMPUTATIONAL TOXICOLOGY ...

    Science.gov (United States)

    One goal of the field of computational toxicology is to predict chemical toxicity by combining computer models with biological and toxicological data. predict chemical toxicity by combining computer models with biological and toxicological data

  16. COMPUTATIONAL SCIENCE CENTER

    Energy Technology Data Exchange (ETDEWEB)

    DAVENPORT,J.

    2004-11-01

    The Brookhaven Computational Science Center brings together researchers in biology, chemistry, physics, and medicine with applied mathematicians and computer scientists to exploit the remarkable opportunities for scientific discovery which have been enabled by modern computers. These opportunities are especially great in computational biology and nanoscience, but extend throughout science and technology and include for example, nuclear and high energy physics, astrophysics, materials and chemical science, sustainable energy, environment, and homeland security.

  17. Biological Agents

    Science.gov (United States)

    ... E-Tools Safety and Health Topics / Biological Agents Biological Agents This page requires that javascript be enabled ... 202) 693-2300 if additional assistance is required. Biological Agents Menu Overview In Focus: Ebola Frederick A. ...

  18. Plant synthetic biology.

    Science.gov (United States)

    Liu, Wusheng; Stewart, C Neal

    2015-05-01

    Plant synthetic biology is an emerging field that combines engineering principles with plant biology toward the design and production of new devices. This emerging field should play an important role in future agriculture for traditional crop improvement, but also in enabling novel bioproduction in plants. In this review we discuss the design cycles of synthetic biology as well as key engineering principles, genetic parts, and computational tools that can be utilized in plant synthetic biology. Some pioneering examples are offered as a demonstration of how synthetic biology can be used to modify plants for specific purposes. These include synthetic sensors, synthetic metabolic pathways, and synthetic genomes. We also speculate about the future of synthetic biology of plants. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Development of a Systems Computational Model to Investigate Early Biological Events in Hepatic Activation of Constitutive Androstane Receptor (CAR) by Phenobarbital

    Science.gov (United States)

    Activation of the nuclear receptor CAR (constitutive active/androstane receptor) is implicated in the control several key biological events such as metabolic pathways. Here, we combined data from literature with information obtained from in vitro assays in the US EPA ToxCast dat...

  20. 7th Annual Systems Biology Symposium: Systems Biology and Engineering

    Energy Technology Data Exchange (ETDEWEB)

    Galitski, Timothy P.

    2008-04-01

    Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering are now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."

  1. Learning, epigenetics, and computation: An extension on Fitch's proposal. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

    Science.gov (United States)

    Okanoya, Kazuo

    2014-09-01

    The comparative computational approach of Fitch [1] attempts to renew the classical David Marr paradigm of computation, algorithm, and implementation, by introducing evolutionary view of the relationship between neural architecture and cognition. This comparative evolutionary view provides constraints useful in narrowing down the problem space for both cognition and neural mechanisms. I will provide two examples from our own studies that reinforce and extend Fitch's proposal.

  2. Standard biological parts knowledgebase.

    Directory of Open Access Journals (Sweden)

    Michal Galdzicki

    2011-02-01

    Full Text Available We have created the Knowledgebase of Standard Biological Parts (SBPkb as a publically accessible Semantic Web resource for synthetic biology (sbolstandard.org. The SBPkb allows researchers to query and retrieve standard biological parts for research and use in synthetic biology. Its initial version includes all of the information about parts stored in the Registry of Standard Biological Parts (partsregistry.org. SBPkb transforms this information so that it is computable, using our semantic framework for synthetic biology parts. This framework, known as SBOL-semantic, was built as part of the Synthetic Biology Open Language (SBOL, a project of the Synthetic Biology Data Exchange Group. SBOL-semantic represents commonly used synthetic biology entities, and its purpose is to improve the distribution and exchange of descriptions of biological parts. In this paper, we describe the data, our methods for transformation to SBPkb, and finally, we demonstrate the value of our knowledgebase with a set of sample queries. We use RDF technology and SPARQL queries to retrieve candidate "promoter" parts that are known to be both negatively and positively regulated. This method provides new web based data access to perform searches for parts that are not currently possible.

  3. Standard Biological Parts Knowledgebase

    Science.gov (United States)

    Galdzicki, Michal; Rodriguez, Cesar; Chandran, Deepak; Sauro, Herbert M.; Gennari, John H.

    2011-01-01

    We have created the Knowledgebase of Standard Biological Parts (SBPkb) as a publically accessible Semantic Web resource for synthetic biology (sbolstandard.org). The SBPkb allows researchers to query and retrieve standard biological parts for research and use in synthetic biology. Its initial version includes all of the information about parts stored in the Registry of Standard Biological Parts (partsregistry.org). SBPkb transforms this information so that it is computable, using our semantic framework for synthetic biology parts. This framework, known as SBOL-semantic, was built as part of the Synthetic Biology Open Language (SBOL), a project of the Synthetic Biology Data Exchange Group. SBOL-semantic represents commonly used synthetic biology entities, and its purpose is to improve the distribution and exchange of descriptions of biological parts. In this paper, we describe the data, our methods for transformation to SBPkb, and finally, we demonstrate the value of our knowledgebase with a set of sample queries. We use RDF technology and SPARQL queries to retrieve candidate “promoter” parts that are known to be both negatively and positively regulated. This method provides new web based data access to perform searches for parts that are not currently possible. PMID:21390321

  4. Standard biological parts knowledgebase.

    Science.gov (United States)

    Galdzicki, Michal; Rodriguez, Cesar; Chandran, Deepak; Sauro, Herbert M; Gennari, John H

    2011-02-24

    We have created the Knowledgebase of Standard Biological Parts (SBPkb) as a publically accessible Semantic Web resource for synthetic biology (sbolstandard.org). The SBPkb allows researchers to query and retrieve standard biological parts for research and use in synthetic biology. Its initial version includes all of the information about parts stored in the Registry of Standard Biological Parts (partsregistry.org). SBPkb transforms this information so that it is computable, using our semantic framework for synthetic biology parts. This framework, known as SBOL-semantic, was built as part of the Synthetic Biology Open Language (SBOL), a project of the Synthetic Biology Data Exchange Group. SBOL-semantic represents commonly used synthetic biology entities, and its purpose is to improve the distribution and exchange of descriptions of biological parts. In this paper, we describe the data, our methods for transformation to SBPkb, and finally, we demonstrate the value of our knowledgebase with a set of sample queries. We use RDF technology and SPARQL queries to retrieve candidate "promoter" parts that are known to be both negatively and positively regulated. This method provides new web based data access to perform searches for parts that are not currently possible.

  5. Brains are not just neurons. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by Fitch

    Science.gov (United States)

    Huber, Ludwig

    2014-09-01

    This comment addresses the first component of Fitch's framework: the computational power of single neurons [3]. Although I agree that traditional models of neural computation have vastly underestimated the computational power of single neurons, I am hesitant to follow him completely. The exclusive focus on neurons is likely to underestimate the importance of other cells in the brain. In the last years, two such cell types have received appropriate attention by neuroscientists: interneurons and glia. Interneurons are small, tightly packed cells involved in the control of information processing in learning and memory. Rather than transmitting externally (like motor or sensory neurons), these neurons process information within internal circuits of the brain (therefore also called 'relay neurons'). Some specialized interneuron subtypes temporally regulate the flow of information in a given cortical circuit during relevant behavioral events [4]. In the human brain approx. 100 billion interneurons control information processing and are implicated in disorders such as epilepsy and Parkinson's.

  6. COMPUTATIONAL SCIENCE CENTER

    Energy Technology Data Exchange (ETDEWEB)

    DAVENPORT, J.

    2005-11-01

    The Brookhaven Computational Science Center brings together researchers in biology, chemistry, physics, and medicine with applied mathematicians and computer scientists to exploit the remarkable opportunities for scientific discovery which have been enabled by modern computers. These opportunities are especially great in computational biology and nanoscience, but extend throughout science and technology and include, for example, nuclear and high energy physics, astrophysics, materials and chemical science, sustainable energy, environment, and homeland security. To achieve our goals we have established a close alliance with applied mathematicians and computer scientists at Stony Brook and Columbia Universities.

  7. Computer algebra applications

    International Nuclear Information System (INIS)

    Calmet, J.

    1982-01-01

    A survey of applications based either on fundamental algorithms in computer algebra or on the use of a computer algebra system is presented. Recent work in biology, chemistry, physics, mathematics and computer science is discussed. In particular, applications in high energy physics (quantum electrodynamics), celestial mechanics and general relativity are reviewed. (Auth.)

  8. Modern Biology

    OpenAIRE

    ALEKSIC, Branko

    2014-01-01

    The purpose of this course is to learn the philosophy, principles, and techniques of modern biology. The course is particularly designed for those who have not learned biology previously or whose major is other than biology, and who may think that they do not need to know any biology at all. The topics are covered in a rather general, overview manner, but certain level of diligence in grasping concepts and memorizing the terminology is expected.

  9. Computational Streetscapes

    Directory of Open Access Journals (Sweden)

    Paul M. Torrens

    2016-09-01

    Full Text Available Streetscapes have presented a long-standing interest in many fields. Recently, there has been a resurgence of attention on streetscape issues, catalyzed in large part by computing. Because of computing, there is more understanding, vistas, data, and analysis of and on streetscape phenomena than ever before. This diversity of lenses trained on streetscapes permits us to address long-standing questions, such as how people use information while mobile, how interactions with people and things occur on streets, how we might safeguard crowds, how we can design services to assist pedestrians, and how we could better support special populations as they traverse cities. Amid each of these avenues of inquiry, computing is facilitating new ways of posing these questions, particularly by expanding the scope of what-if exploration that is possible. With assistance from computing, consideration of streetscapes now reaches across scales, from the neurological interactions that form among place cells in the brain up to informatics that afford real-time views of activity over whole urban spaces. For some streetscape phenomena, computing allows us to build realistic but synthetic facsimiles in computation, which can function as artificial laboratories for testing ideas. In this paper, I review the domain science for studying streetscapes from vantages in physics, urban studies, animation and the visual arts, psychology, biology, and behavioral geography. I also review the computational developments shaping streetscape science, with particular emphasis on modeling and simulation as informed by data acquisition and generation, data models, path-planning heuristics, artificial intelligence for navigation and way-finding, timing, synthetic vision, steering routines, kinematics, and geometrical treatment of collision detection and avoidance. I also discuss the implications that the advances in computing streetscapes might have on emerging developments in cyber

  10. Parametric scaling from species relative abundances to absolute abundances in the computation of biological diversity: a first proposal using Shannon's entropy.

    Science.gov (United States)

    Ricotta, Carlo

    2003-01-01

    Traditional diversity measures such as the Shannon entropy are generally computed from the species' relative abundance vector of a given community to the exclusion of species' absolute abundances. In this paper, I first mention some examples where the total information content associated with a given community may be more adequate than Shannon's average information content for a better understanding of ecosystem functioning. Next, I propose a parametric measure of statistical information that contains both Shannon's entropy and total information content as special cases of this more general function.

  11. Implementation is crucial but must be neurobiologically grounded. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

    Science.gov (United States)

    Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias; Small, Steven L.

    2014-09-01

    From the perspective of language, Fitch's [1] claim that theories of cognitive computation should not be separated from those of implementation surely deserves applauding. Recent developments in the Cognitive Neuroscience of Language, leading to the new field of the Neurobiology of Language [2-4], emphasise precisely this point: rather than attempting to simply map cognitive theories of language onto the brain, we should aspire to understand how the brain implements language. This perspective resonates with many of the points raised by Fitch in his review, such as the discussion of unhelpful dichotomies (e.g., Nature versus Nurture). Cognitive dichotomies and debates have repeatedly turned out to be of limited usefulness when it comes to understanding language in the brain. The famous modularity-versus-interactivity and dual route-versus-connectionist debates are cases in point: in spite of hundreds of experiments using neuroimaging (or other techniques), or the construction of myriad computer models, little progress has been made in their resolution. This suggests that dichotomies proposed at a purely cognitive (or computational) level without consideration of biological grounding appear to be "asking the wrong questions" about the neurobiology of language. In accordance with these developments, several recent proposals explicitly consider neurobiological constraints while seeking to explain language processing at a cognitive level (e.g. [5-7]).

  12. Analyzing the Biology on the System Level

    OpenAIRE

    Tong, Wei

    2016-01-01

    Although various genome projects have provided us enormous static sequence information, understanding of the sophisticated biology continues to require integrating the computational modeling, system analysis, technology development for experiments, and quantitative experiments all together to analyze the biology architecture on various levels, which is just the origin of systems biology subject. This review discusses the object, its characteristics, and research attentions in systems biology,...

  13. Engineering a Biological Revolution.

    Science.gov (United States)

    Matheson, Susan

    2017-01-26

    The new field of synthetic biology promises to change health care, computer technology, the production of biofuels, and more. Students participating in the International Genetically Engineered Machine (iGEM) competition are on the front lines of this revolution. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Mathematical biology

    CERN Document Server

    Murray, James D

    1993-01-01

    The book is a textbook (with many exercises) giving an in-depth account of the practical use of mathematical modelling in the biomedical sciences. The mathematical level required is generally not high and the emphasis is on what is required to solve the real biological problem. The subject matter is drawn, e.g. from population biology, reaction kinetics, biological oscillators and switches, Belousov-Zhabotinskii reaction, reaction-diffusion theory, biological wave phenomena, central pattern generators, neural models, spread of epidemics, mechanochemical theory of biological pattern formation and importance in evolution. Most of the models are based on real biological problems and the predictions and explanations offered as a direct result of mathematical analysis of the models are important aspects of the book. The aim is to provide a thorough training in practical mathematical biology and to show how exciting and novel mathematical challenges arise from a genuine interdisciplinary involvement with the biosci...

  15. Opportunities in plant synthetic biology.

    Science.gov (United States)

    Cook, Charis; Martin, Lisa; Bastow, Ruth

    2014-05-01

    Synthetic biology is an emerging field uniting scientists from all disciplines with the aim of designing or re-designing biological processes. Initially, synthetic biology breakthroughs came from microbiology, chemistry, physics, computer science, materials science, mathematics, and engineering disciplines. A transition to multicellular systems is the next logical step for synthetic biologists and plants will provide an ideal platform for this new phase of research. This meeting report highlights some of the exciting plant synthetic biology projects, and tools and resources, presented and discussed at the 2013 GARNet workshop on plant synthetic biology.

  16. Computational Psychiatry

    Science.gov (United States)

    Wang, Xiao-Jing; Krystal, John H.

    2014-01-01

    Psychiatric disorders such as autism and schizophrenia arise from abnormalities in brain systems that underlie cognitive, emotional and social functions. The brain is enormously complex and its abundant feedback loops on multiple scales preclude intuitive explication of circuit functions. In close interplay with experiments, theory and computational modeling are essential for understanding how, precisely, neural circuits generate flexible behaviors and their impairments give rise to psychiatric symptoms. This Perspective highlights recent progress in applying computational neuroscience to the study of mental disorders. We outline basic approaches, including identification of core deficits that cut across disease categories, biologically-realistic modeling bridging cellular and synaptic mechanisms with behavior, model-aided diagnosis. The need for new research strategies in psychiatry is urgent. Computational psychiatry potentially provides powerful tools for elucidating pathophysiology that may inform both diagnosis and treatment. To achieve this promise will require investment in cross-disciplinary training and research in this nascent field. PMID:25442941

  17. Synthesis, characterization, computational studies and biological evaluation of S-benzyl-β-N-[3-(4-hydroxy-3-methoxy-phenylallylidene)]dithiocarbazate

    Science.gov (United States)

    Bhat, Rayees A.; Kumar, D.; Malla, Manzoor A.; Bhat, Sami U.; Khan, Md Shahzad; Manzoor, Ovais; Srivastava, Anurag; Naikoo, Rawoof A.; Mohsin, Mohd; Mir, Muzzaffar A.

    2018-03-01

    S-Benzyl-β-N-[3-(4-hydroxy-3-methoxy-phenylallylidene)]dithiocarbazate (HL1), Schiff base of S-benzyl dithiocarbazate, was synthesized by 1:1 condensation between S-benzyl dithiocarbazate and 4-hydroxy-3-methoxy cinnamaldehyde. The nitrogen-sulfur Schiff base (HL1) was characterized by Mass, FT-IR, H1-NMR, Raman, and UV-VIS spectroscopic techniques. Theoretical quantum chemical calculations were performed using DFT in combination with B3LYP exchange correlation functional and 6-311++ G (d, p) basis sets level. The calculated values of chemical potential (μ), HOMO-LUMO energy gap, chemical hardness, softness (S), ionization energy (IE), electron affinity (EA), dipole moment (D) and relative stabilization energy of the compound were 0.14881 eV, 0.12542 eV, 0.06271 eV, 3.37299 eV, -0.21152 eV, -0.08610 eV, 4.4090 Debye and -1753.350 eV respectively. Theoretically calculated parameters like H1-NMR, FT-IR, UV-VIS, Raman, electrostatic potential and HOMO-LUMO energy gap are in good agreement with experimental results. Also, in-vitro cytotoxicity studies were done against two habitually infection causing bacteria strains including gram-positive (S. aureus) and gram-negative (E. coli) for antibacterial activity. The results showed appreciable biological activity and the activity increased with increase in dose.

  18. Essential numerical computer methods

    CERN Document Server

    Johnson, Michael L

    2010-01-01

    The use of computers and computational methods has become ubiquitous in biological and biomedical research. During the last 2 decades most basic algorithms have not changed, but what has is the huge increase in computer speed and ease of use, along with the corresponding orders of magnitude decrease in cost. A general perception exists that the only applications of computers and computer methods in biological and biomedical research are either basic statistical analysis or the searching of DNA sequence data bases. While these are important applications they only scratch the surface of the current and potential applications of computers and computer methods in biomedical research. The various chapters within this volume include a wide variety of applications that extend far beyond this limited perception. As part of the Reliable Lab Solutions series, Essential Numerical Computer Methods brings together chapters from volumes 210, 240, 321, 383, 384, 454, and 467 of Methods in Enzymology. These chapters provide ...

  19. Advances in unconventional computing

    CERN Document Server

    2017-01-01

    The unconventional computing is a niche for interdisciplinary science, cross-bred of computer science, physics, mathematics, chemistry, electronic engineering, biology, material science and nanotechnology. The aims of this book are to uncover and exploit principles and mechanisms of information processing in and functional properties of physical, chemical and living systems to develop efficient algorithms, design optimal architectures and manufacture working prototypes of future and emergent computing devices. This first volume presents theoretical foundations of the future and emergent computing paradigms and architectures. The topics covered are computability, (non-)universality and complexity of computation; physics of computation, analog and quantum computing; reversible and asynchronous devices; cellular automata and other mathematical machines; P-systems and cellular computing; infinity and spatial computation; chemical and reservoir computing. The book is the encyclopedia, the first ever complete autho...

  20. Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues

    International Nuclear Information System (INIS)

    Yang, M; Zhu, X R; Mohan, R; Dong, L; Virshup, G; Clayton, J

    2010-01-01

    We discovered an empirical relationship between the logarithm of mean excitation energy (ln I m ) and the effective atomic number (EAN) of human tissues, which allows for computing patient-specific proton stopping power ratios (SPRs) using dual-energy CT (DECT) imaging. The accuracy of the DECT method was evaluated for 'standard' human tissues as well as their variance. The DECT method was compared to the existing standard clinical practice-a procedure introduced by Schneider et al at the Paul Scherrer Institute (the stoichiometric calibration method). In this simulation study, SPRs were derived from calculated CT numbers of known material compositions, rather than from measurement. For standard human tissues, both methods achieved good accuracy with the root-mean-square (RMS) error well below 1%. For human tissues with small perturbations from standard human tissue compositions, the DECT method was shown to be less sensitive than the stoichiometric calibration method. The RMS error remained below 1% for most cases using the DECT method, which implies that the DECT method might be more suitable for measuring patient-specific tissue compositions to improve the accuracy of treatment planning for charged particle therapy. In this study, the effects of CT imaging artifacts due to the beam hardening effect, scatter, noise, patient movement, etc were not analyzed. The true potential of the DECT method achieved in theoretical conditions may not be fully achievable in clinical settings. Further research and development may be needed to take advantage of the DECT method to characterize individual human tissues.

  1. The Computational Sensorimotor Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Computational Sensorimotor Systems Lab focuses on the exploration, analysis, modeling and implementation of biological sensorimotor systems for both scientific...

  2. Biological therapeutics

    National Research Council Canada - National Science Library

    Greenstein, Ben; Brook, Daniel A

    2011-01-01

    This introductory textbook covers all the main categories of biological medicines, including vaccines, hormonal preparations, drugs for rheumatoid arthritis and other connective tissue diseases, drugs...

  3. Analyses of insulin-potentiating fragments of human growth hormone by computative simulation; essential unit for insulin-involved biological responses.

    Science.gov (United States)

    Ohkura, K; Hori, H

    2000-07-01

    We analyzed the structural features of insulin-potentiating fragments of human growth hormone by computative simulations. The peptides were designated from the N-terminus sequences of the hormone positions at 1-15 (hGH(1-15); H2N-Phe1-Pro2-Thr3-Ile4-Pro5-Leu6-Ser7-Arg8-L eu9-Phe10-Asp11-Asn12-Ala13-Met14-Leu15 -COOH), 6-13 (hGH(6-13)), 7-13 (hGH(7-13)) and 8-13 (hGH(8-13)), which enhanced insulin-producing hypoglycemia. In these peptide molecules, ionic bonds were predicted to form between 8th-arginyl residue and 11th-aspartic residue, and this intramolecular interaction caused the formation of a macrocyclic structure containing a tetrapeptide Arg8-Leu9-Phe10-Asp11. The peptide positions at 6-10 (hGH(6-10)), 9-13 (hGH(9-13)) and 10-13 (hGH(10-13)) did not lead to a macrocyclic formation in the molecules, and had no effect on the insulin action. Although beta-Ala13hGH(1-15), in which the 13th-alanine was replaced by a beta-alanyl residue, had no effect on insulin-producing hypoglycemia, the macrocyclic region (Arg8-Leu9-Phe10-Asp11) was observed by the computative simulation. An isothermal vibration analysis of both of beta-Ala13hGH(1-15) and hGH(1-15) peptide suggested that beta-Ala13hGH(1-15) is molecule was more flexible than hGH(1-15); C-terminal carboxyl group of Leu15 easily accessed to Arg8 and inhibited the ionic bond formation between Arg8 and Asp11 in beta-Ala13hGH(1-15). The peptide of hGH(8-13) dose-dependently enhanced the insulin-involved fatty acid synthesis in rat white adipocytes, and stabilized the C6-NBD-PC (1-acyl-2-[6-[(7-nitro-2,1,3benzoxadiazol-4-yl)amino]-caproyl]-sn- glycero-3-phosphatidylcholine) model membranes. In contrast, hGH(9-13) had no effect both on the fatty acid synthesis and the membrane stability. In the same culture conditions as the fatty acid synthesis assay, hGH(8-13) had no effect on the transcript levels of glucose transporter isoforms (GLUT 1, 4) and hexokinase isozymes (HK I, II) in rat white adipocytes. Judging from

  4. Biophysics and systems biology.

    Science.gov (United States)

    Noble, Denis

    2010-03-13

    Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights.

  5. Computer Center: Software Review.

    Science.gov (United States)

    Duhrkopf, Richard, Ed.; Belshe, John F., Ed.

    1988-01-01

    Reviews a software package, "Mitosis-Meiosis," available for Apple II or IBM computers with colorgraphics capabilities. Describes the documentation, presentation and flexibility of the program. Rates the program based on graphics and usability in a biology classroom. (CW)

  6. Computing the functional proteome

    DEFF Research Database (Denmark)

    O'Brien, Edward J.; Palsson, Bernhard

    2015-01-01

    Constraint-based models enable the computation of feasible, optimal, and realized biological phenotypes from reaction network reconstructions and constraints on their operation. To date, stoichiometric reconstructions have largely focused on metabolism, resulting in genome-scale metabolic models (M...

  7. Is synthetic biology mechanical biology?

    Science.gov (United States)

    Holm, Sune

    2015-12-01

    A widespread and influential characterization of synthetic biology emphasizes that synthetic biology is the application of engineering principles to living systems. Furthermore, there is a strong tendency to express the engineering approach to organisms in terms of what seems to be an ontological claim: organisms are machines. In the paper I investigate the ontological and heuristic significance of the machine analogy in synthetic biology. I argue that the use of the machine analogy and the aim of producing rationally designed organisms does not necessarily imply a commitment to mechanical biology. The ideal of applying engineering principles to biology is best understood as expressing recognition of the machine-unlikeness of natural organisms and the limits of human cognition. The paper suggests an interpretation of the identification of organisms with machines in synthetic biology according to which it expresses a strategy for representing, understanding, and constructing living systems that are more machine-like than natural organisms.

  8. Mesoscopic biology

    Indian Academy of Sciences (India)

    In this paper we present a qualitative outlook of mesoscopic biology where the typical length scale is of the order of nanometers and the energy scales comparable to thermal energy. Novel biomolecular machines, governed by coded information at the level of DNA and proteins, operate at these length scales in biological ...

  9. Teaching Molecular Biology with Microcomputers.

    Science.gov (United States)

    Reiss, Rebecca; Jameson, David

    1984-01-01

    Describes a series of computer programs that use simulation and gaming techniques to present the basic principles of the central dogma of molecular genetics, mutation, and the genetic code. A history of discoveries in molecular biology is presented and the evolution of these computer assisted instructional programs is described. (MBR)

  10. Programming in biomolecular computation

    DEFF Research Database (Denmark)

    Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

    2011-01-01

    Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem...... conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined...... by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways...

  11. Analog synthetic biology.

    Science.gov (United States)

    Sarpeshkar, R

    2014-03-28

    We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.

  12. Mathematical modeling of biological processes

    CERN Document Server

    Friedman, Avner

    2014-01-01

    This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

  13. Computational neuroscience

    CERN Document Server

    Blackwell, Kim L

    2014-01-01

    Progress in Molecular Biology and Translational Science provides a forum for discussion of new discoveries, approaches, and ideas in molecular biology. It contains contributions from leaders in their fields and abundant references. This volume brings together different aspects of, and approaches to, molecular and multi-scale modeling, with applications to a diverse range of neurological diseases. Mathematical and computational modeling offers a powerful approach for examining the interaction between molecular pathways and ionic channels in producing neuron electrical activity. It is well accepted that non-linear interactions among diverse ionic channels can produce unexpected neuron behavior and hinder a deep understanding of how ion channel mutations bring about abnormal behavior and disease. Interactions with the diverse signaling pathways activated by G protein coupled receptors or calcium influx adds an additional level of complexity. Modeling is an approach to integrate myriad data sources into a cohesiv...

  14. Quantum Biology

    Directory of Open Access Journals (Sweden)

    Alessandro Sergi

    2009-06-01

    Full Text Available A critical assessment of the recent developmentsof molecular biology is presented.The thesis that they do not lead to a conceptualunderstanding of life and biological systems is defended.Maturana and Varela's concept of autopoiesis is briefly sketchedand its logical circularity avoided by postulatingthe existence of underlying living processes,entailing amplification from the microscopic to the macroscopic scale,with increasing complexity in the passage from one scale to the other.Following such a line of thought, the currently accepted model of condensed matter, which is based on electrostatics and short-ranged forces,is criticized. It is suggested that the correct interpretationof quantum dispersion forces (van der Waals, hydrogen bonding, and so onas quantum coherence effects hints at the necessity of includinglong-ranged forces (or mechanisms for them incondensed matter theories of biological processes.Some quantum effects in biology are reviewedand quantum mechanics is acknowledged as conceptually important to biology since withoutit most (if not all of the biological structuresand signalling processes would not even exist. Moreover, it is suggested that long-rangequantum coherent dynamics, including electron polarization,may be invoked to explain signal amplificationprocess in biological systems in general.

  15. Biological desulfurisation

    Energy Technology Data Exchange (ETDEWEB)

    Arena, B.J. [UOP LLC (United States); Benschop, A.; Janssen, A. [Paques Natural Solutions (Netherlands); Kijlstra, S. [Shell Global Solutions (Netherlands)

    2001-03-01

    This article focuses on the biological THIOPAQ process for removing hydrogen sulphide from refinery gases and recovering elemental sulphur. Details are given of the process which absorbs hydrogen sulphide-containing gas in alkaline solution prior to oxidation of the dissolved sulphur to elemental sulphur in a THIOPAQ aerobic biological reactor, with regeneration of the caustic solution. Sulphur handling options including sulphur wash, the drying of the sulphur cake, and sulphur smelting by pressure liquefaction are described. Agricultural applications of the biologically recovered sulphur, and application of the THIOPAQ process to sulphur recovery are discussed.

  16. Telemetry System of Biological Parameters

    Directory of Open Access Journals (Sweden)

    Jan Spisak

    2005-01-01

    Full Text Available The mobile telemetry system of biological parameters serves for reading and wireless data transfer of measured values of selected biological parameters to an outlying computer. It concerns basically long time monitoring of vital function of car pilot.The goal of this projects is to propose mobile telemetry system for reading, wireless transfer and processing of biological parameters of car pilot during physical and psychical stress. It has to be made with respect to minimal consumption, weight and maximal device mobility. This system has to eliminate signal noise, which is created by biological artifacts and disturbances during the data transfer.

  17. Systems Biology

    Indian Academy of Sciences (India)

    IAS Admin

    study and understand the function of biological systems, particu- larly, the response of such .... understand the organisation and behaviour of prokaryotic sys- tems. ... relationship of the structure of a target molecule to its ability to bind a certain ...

  18. Emission computed tomography

    International Nuclear Information System (INIS)

    Budinger, T.F.; Gullberg, G.T.; Huesman, R.H.

    1979-01-01

    This chapter is devoted to the methods of computer assisted tomography for determination of the three-dimensional distribution of gamma-emitting radionuclides in the human body. The major applications of emission computed tomography are in biological research and medical diagnostic procedures. The objectives of these procedures are to make quantitative measurements of in vivo biochemical and hemodynamic functions

  19. Nature, computation and complexity

    International Nuclear Information System (INIS)

    Binder, P-M; Ellis, G F R

    2016-01-01

    The issue of whether the unfolding of events in the world can be considered a computation is explored in this paper. We come to different conclusions for inert and for living systems (‘no’ and ‘qualified yes’, respectively). We suggest that physical computation as we know it exists only as a tool of complex biological systems: us. (paper)

  20. Bayes in biological anthropology.

    Science.gov (United States)

    Konigsberg, Lyle W; Frankenberg, Susan R

    2013-12-01

    In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available. Copyright © 2013 Wiley Periodicals, Inc.

  1. Development of a computational system for management of risks in radiosterilization processes of biological tissues; Desenvolvimento de um sistema computacional de gerenciamento de riscos em processos de radioesterilizacao de tecidos biologicos

    Energy Technology Data Exchange (ETDEWEB)

    Montoya, Cynara Viterbo

    2009-07-01

    Risk management can be understood to be a systematic management which aims to identify record and control the risks of a process. Applying risk management becomes a complex activity, due to the variety of professionals involved. In order to execute risk management the following are requirements of paramount importance: the experience, discernment and judgment of a multidisciplinary team, guided by means of quality tools, so as to provide standardization in the process of investigating the cause and effects of risks and dynamism in obtaining the objective desired, i.e. the reduction and control of the risk. This work aims to develop a computational system of risk management (software) which makes it feasible to diagnose the risks of the processes of radiosterilization of biological tissues. The methodology adopted was action-research, according to which the researcher performs an active role in the establishment of the problems found, in the follow-up and in the evaluation of the actions taken owing to the problems. The scenario of this action-research was the Laboratory of Biological Tissues (LTB) in the Radiation Technology Center IPEN/CNEN-SP - Sao Paulo/Brazil. The software developed was executed in PHP and Flash/MySQL language, the server (hosting), the software is available on the Internet (www.vcrisk.com.br), which the user can access from anywhere by means of the login/access password previously sent by email to the team responsible for the tissue to be analyzed. The software presents friendly navigability whereby the user is directed step-by-step in the process of investigating the risk up to the means of reducing it. The software 'makes' the user comply with the term and present the effectiveness of the actions taken to reduce the risk. Applying this system provided the organization (LTB/CTR/IPEN) with dynamic communication, effective between the members of the multidisciplinary team: a) in decision-making; b) in lessons learned; c) in knowing

  2. Parallel computing works!

    CERN Document Server

    Fox, Geoffrey C; Messina, Guiseppe C

    2014-01-01

    A clear illustration of how parallel computers can be successfully appliedto large-scale scientific computations. This book demonstrates how avariety of applications in physics, biology, mathematics and other scienceswere implemented on real parallel computers to produce new scientificresults. It investigates issues of fine-grained parallelism relevant forfuture supercomputers with particular emphasis on hypercube architecture. The authors describe how they used an experimental approach to configuredifferent massively parallel machines, design and implement basic systemsoftware, and develop

  3. Trusted computation through biologically inspired processes

    Science.gov (United States)

    Anderson, Gustave W.

    2013-05-01

    Due to supply chain threats it is no longer a reasonable assumption that traditional protections alone will provide sufficient security for enterprise systems. The proposed cognitive trust model architecture extends the state-of-the-art in enterprise anti-exploitation technologies by providing collective immunity through backup and cross-checking, proactive health monitoring and adaptive/autonomic threat response, and network resource diversity.

  4. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-01

    In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information

  5. High performance computing on biological sequence alignment

    OpenAIRE

    Orobitg Cortada, Miquel

    2013-01-01

    L'Alineament Múltiple de Seqüències (MSA) és una eina molt potent per a aplicacions biològiques importants. Els MSA són computacionalment complexos de calcular, i la majoria de les formulacions porten a problemes d'optimització NP-Hard. Per a dur a terme alineaments de milers de seqüències, nous desafiaments necessiten ser resolts per adaptar els algoritmes a l'era de la computació d'altes prestacions. En aquesta tesi es proposen tres aportacions diferents per resoldre algunes limitacion...

  6. [Biological agents].

    Science.gov (United States)

    Amano, Koichi

    2009-03-01

    There are two types of biological agents for the treatment of rheumatoid arthritis (RA); monoclonal antibodies and recombinant proteins. Among the latter, etanercept, a recombinant fusion protein of soluble TNF receptor and IgG was approved in 2005 in Japan. The post-marketing surveillance of 13,894 RA patients revealed the efficacy and safety profiles of etanercept in the Japanese population, as well as overseas studies. Abatacept, a recombinant fusion protein of CTLA4 and IgG, is another biological agent for RA. Two clinical trials disclosed the efficacy of abatacept for difficult-to-treat patients: the AIM for MTX-resistant cases and the ATTAIN for patients who are resistant to anti-TNF. The ATTEST trial suggested abatacept might have more acceptable safety profile than infliximab. These biologics are also promising for the treatment of RA for not only relieving clinical symptoms and signs but retarding structural damage.

  7. Biological preconcentrator

    Science.gov (United States)

    Manginell, Ronald P [Albuquerque, NM; Bunker, Bruce C [Albuquerque, NM; Huber, Dale L [Albuquerque, NM

    2008-09-09

    A biological preconcentrator comprises a stimulus-responsive active film on a stimulus-producing microfabricated platform. The active film can comprise a thermally switchable polymer film that can be used to selectively absorb and desorb proteins from a protein mixture. The biological microfabricated platform can comprise a thin membrane suspended on a substrate with an integral resistive heater and/or thermoelectric cooler for thermal switching of the active polymer film disposed on the membrane. The active polymer film can comprise hydrogel-like polymers, such as poly(ethylene oxide) or poly(n-isopropylacrylamide), that are tethered to the membrane. The biological preconcentrator can be fabricated with semiconductor materials and technologies.

  8. Synthetic biology: an emerging engineering discipline.

    Science.gov (United States)

    Cheng, Allen A; Lu, Timothy K

    2012-01-01

    Over the past decade, synthetic biology has emerged as an engineering discipline for biological systems. Compared with other substrates, biology poses a unique set of engineering challenges resulting from an incomplete understanding of natural biological systems and tools for manipulating them. To address these challenges, synthetic biology is advancing from developing proof-of-concept designs to focusing on core platforms for rational and high-throughput biological engineering. These platforms span the entire biological design cycle, including DNA construction, parts libraries, computational design tools, and interfaces for manipulating and probing synthetic circuits. The development of these enabling technologies requires an engineering mindset to be applied to biology, with an emphasis on generalizable techniques in addition to application-specific designs. This review aims to discuss the progress and challenges in synthetic biology and to illustrate areas where synthetic biology may impact biomedical engineering and human health.

  9. Heuristic Strategies in Systems Biology

    Directory of Open Access Journals (Sweden)

    Fridolin Gross

    2016-06-01

    Full Text Available Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic tools. These models rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences.

  10. Environmental biology

    International Nuclear Information System (INIS)

    Tschumi, P.A.

    1981-01-01

    Environmental biology illustrates the functioning of ecosystems and the dynamics of populations with many examples from limnology and terrestrial ecology. On this basis, present environmental problems are analyzed. The present environmental crisis is seen as a result of the failure to observe ecological laws. (orig.) [de

  11. Biological timekeeping

    DEFF Research Database (Denmark)

    Lloyd, David

    2016-01-01

    , the networks that connect differenttime domains and the oscillations, rhythms and biological clocks that coordinate andsynchronise the complexity of the living state.“It is the pattern maintained by this homeostasis, which is the touchstone ofour personal identity. Our tissues change as we live: the food we...

  12. Scaffolded biology.

    Science.gov (United States)

    Minelli, Alessandro

    2016-09-01

    Descriptions and interpretations of the natural world are dominated by dichotomies such as organism vs. environment, nature vs. nurture, genetic vs. epigenetic, but in the last couple of decades strong dissatisfaction with those partitions has been repeatedly voiced and a number of alternative perspectives have been suggested, from perspectives such as Dawkins' extended phenotype, Turner's extended organism, Oyama's Developmental Systems Theory and Odling-Smee's niche construction theory. Last in time is the description of biological phenomena in terms of hybrids between an organism (scaffolded system) and a living or non-living scaffold, forming unit systems to study processes such as reproduction and development. As scaffold, eventually, we can define any resource used by the biological system, especially in development and reproduction, without incorporating it as happens in the case of resources fueling metabolism. Addressing biological systems as functionally scaffolded systems may help pointing to functional relationships that can impart temporal marking to the developmental process and thus explain its irreversibility; revisiting the boundary between development and metabolism and also regeneration phenomena, by suggesting a conceptual framework within which to investigate phenomena of regular hypermorphic regeneration such as characteristic of deer antlers; fixing a periodization of development in terms of the times at which a scaffolding relationship begins or is terminated; and promoting plant galls to legitimate study objects of developmental biology.

  13. Biological digestion

    International Nuclear Information System (INIS)

    Rosevear, A.

    1988-01-01

    This paper discusses the biological degradation of non-radioactive organic material occurring in radioactive wastes. The biochemical steps are often performed using microbes or isolated enzymes in combination with chemical steps and the aim is to oxidise the carbon, hydrogen, nitrogen and sulphur to their respective oxides. (U.K.)

  14. Marine Biology

    Science.gov (United States)

    Dewees, Christopher M.; Hooper, Jon K.

    1976-01-01

    A variety of informational material for a course in marine biology or oceanology at the secondary level is presented. Among the topics discussed are: food webs and pyramids, planktonic blooms, marine life, plankton nets, food chains, phytoplankton, zooplankton, larval plankton and filter feeders. (BT)

  15. Programming in biomolecular computation

    DEFF Research Database (Denmark)

    Hartmann, Lars Røeboe; Jones, Neil; Simonsen, Jakob Grue

    2010-01-01

    in a strong sense: a universal algorithm exists, that is able to execute any program, and is not asymptotically inefficient. A prototype model has been implemented (for now in silico on a conventional computer). This work opens new perspectives on just how computation may be specified at the biological level......., by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only...... executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways and without arcane encodings of data and algorithm); it is also uniform: new “hardware” is not needed to solve new problems; and (last but not least) it is Turing complete...

  16. Biological radioprotector

    International Nuclear Information System (INIS)

    Stefanescu, Ioan; Titescu, Gheorghe; Tamaian, Radu; Haulica, Ion; Bild, Walther

    2002-01-01

    According to the patent description, the biological radioprotector is deuterium depleted water, DDW, produced by vacuum distillation with an isotopic content lower than natural value. It appears as such or in a mixture with natural water and carbon dioxide. It can be used for preventing and reducing the ionizing radiation effects upon humans or animal organisms, exposed therapeutically, professionally or accidentally to radiation. The most significant advantage of using DDW as biological radioprotector results from its way of administration. Indeed no one of the radioprotectors currently used today can be orally administrated, what reduces the patients' compliance to prophylactic administrations. The biological radioprotector is an unnoxious product obtained from natural water, which can be administrated as food additive instead of drinking water. Dose modification factor is according to initial estimates around 1.9, what is a remarkable feature when one takes into account that the product is toxicity-free and side effect-free and can be administrated prophylactically as a food additive. A net radioprotective action of the deuterium depletion was evidenced experimentally in laboratory animals (rats) hydrated with DDW of 30 ppm D/(D+H) concentration as compared with normally hydrated control animals. Knowing the effects of irradiation and mechanisms of the acute radiation disease as well as the effects of administration of radiomimetic chemicals upon cellular lines of fast cell division, it appears that the effects of administrating DDW result from stimulation of the immunity system. In conclusion, the biological radioprotector DDW presents the following advantages: - it is obtained from natural products without toxicity; - it is easy to be administrated as a food additive, replacing the drinking water; - besides radioprotective effects, the product has also immunostimulative and antitumoral effects

  17. Marine biology

    International Nuclear Information System (INIS)

    Thurman, H.V.; Webber, H.H.

    1984-01-01

    This book discusses both taxonomic and ecological topics on marine biology. Full coverage of marine organisms of all five kingdoms is provided, along with interesting and thorough discussion of all major marine habitats. Organization into six major parts allows flexibility. It also provides insight into important topics such as disposal of nuclear waste at sea, the idea that life began on the ocean floor, and how whales, krill, and people interact. A full-color photo chapter reviews questions, and exercises. The contents are: an overview marine biology: fundamental concepts/investigating life in the ocean; the physical ocean, the ocean floor, the nature of water, the nature and motion of ocean water; general ecology, conditions for life in the sea, biological productivity and energy transfer; marine organisms; monera, protista, mycota and metaphyta; the smaller marine animals, the large animals marine habitats, the intertidal zone/benthos of the continental shelf, the photic zone, the deep ocean, the ocean under stress, marine pollution, appendix a: the metric system and conversion factors/ appendix b: prefixes and suffixes/ appendix c: taxonomic classification of common marine organisms, and glossary, and index

  18. Topology in Molecular Biology

    CERN Document Server

    Monastyrsky, Michail Ilych

    2007-01-01

    The book presents a class of new results in molecular biology for which topological methods and ideas are important. These include: the large-scale conformation properties of DNA; computational methods (Monte Carlo) allowing the simulation of large-scale properties of DNA; the tangle model of DNA recombination and other applications of Knot theory; dynamics of supercoiled DNA and biocatalitic properties of DNA; the structure of proteins; and other very recent problems in molecular biology. The text also provides a short course of modern topology intended for the broad audience of biologists and physicists. The authors are renowned specialists in their fields and some of the new results presented here are documented for the first time in monographic form.

  19. Structural Biology Fact Sheet

    Science.gov (United States)

    ... NIGMS NIGMS Home > Science Education > Structural Biology Structural Biology Tagline (Optional) Middle/Main Content Area PDF Version (688 KB) Other Fact Sheets What is structural biology? Structural biology is the study of how biological ...

  20. Biology Branch

    Energy Technology Data Exchange (ETDEWEB)

    Baldwin, W F

    1974-12-31

    Progress is reported on the following studies in biochemistry and molecular biology: study of long pyrimidine polynucleotides in DNA; isolation of thymine dimers from Schizosaccharomyces pombe; thermal stability of high molecular weight RNA; nucleases of Micrococcus radiodurans; effect of ionizing radiation on M. radiodurans cell walls and cell membranes; chemical modification of nucleotides; exonucleases of M. radiodurans; and enzymatic basis of repair of radioinduced damage in M. radiodurans. Genetics, development, and population studies include repair pathways and mutation induction in yeast; induction of pure mutant clones in yeast; radiosensitivity of bacteriophage T4; polyacrylamide gel electrophoresis of bacteriophage T4; radiation genetics of Dahibominus; and radiation studies on bitting flies. (HLW)

  1. Biological biomaterials

    Energy Technology Data Exchange (ETDEWEB)

    Jorge-Herrero, E. [Servicio de Cirugia Experimental. Clinica Puerta de Hierro, Madrid (Spain)

    1997-05-01

    There are a number of situations in which substances of biological origin are employed as biomaterials. Most of them are macromolecules derived from isolated connective tissue or the connective tissue itself in membrane form, in both cases, the tissue can be used in its natural form or be chemically treated. In other cases, certain blood vessels can be chemically pretreated and used as vascular prostheses. Proteins such as albumin, collagen and fibrinogen are employed to coat vascular prostheses. Certain polysaccharides have also been tested for use in controlled drug release systems. Likewise, a number of tissues, such as dura mater, bovine pericardium, procine valves and human valves, are used in the preparation of cardiac prostheses. We also use veins from animals or humans in arterial replacement. In none of these cases are the tissues employed dissimilar to the native tissues as they have been chemically modified, becoming a new bio material with different physical and biochemical properties. In short, we find that natural products are being utilized as biomaterials and must be considered as such; thus, it is necessary to study both their chemicobiological and physicomechanical properties. In the present report, we review the current applications, problems and future prospects of some of these biological biomaterials. (Author) 84 refs.

  2. Fundamentals of natural computing basic concepts, algorithms, and applications

    CERN Document Server

    de Castro, Leandro Nunes

    2006-01-01

    Introduction A Small Sample of Ideas The Philosophy of Natural Computing The Three Branches: A Brief Overview When to Use Natural Computing Approaches Conceptualization General Concepts PART I - COMPUTING INSPIRED BY NATURE Evolutionary Computing Problem Solving as a Search Task Hill Climbing and Simulated Annealing Evolutionary Biology Evolutionary Computing The Other Main Evolutionary Algorithms From Evolutionary Biology to Computing Scope of Evolutionary Computing Neurocomputing The Nervous System Artif

  3. Introduction to morphogenetic computing

    CERN Document Server

    Resconi, Germano; Xu, Guanglin

    2017-01-01

    This book offers a concise introduction to morphogenetic computing, showing that its use makes global and local relations, defects in crystal non-Euclidean geometry databases with source and sink, genetic algorithms, and neural networks more stable and efficient. It also presents applications to database, language, nanotechnology with defects, biological genetic structure, electrical circuit, and big data structure. In Turing machines, input and output states form a system – when the system is in one state, the input is transformed into output. This computation is always deterministic and without any possible contradiction or defects. In natural computation there are defects and contradictions that have to be solved to give a coherent and effective computation. The new computation generates the morphology of the system that assumes different forms in time. Genetic process is the prototype of the morphogenetic computing. At the Boolean logic truth value, we substitute a set of truth (active sets) values with...

  4. Internet vis-a-vis marine biology

    Digital Repository Service at National Institute of Oceanography (India)

    Chavan, V.S.

    Internet is an amalgum of networks which reaches to more than 100 million people across the globe. The satellite-telecommunication based computer network web hosts information on every aspect of life. Marine biology related information too is being...

  5. How do biological systems escape 'chaotic' state?

    Indian Academy of Sciences (India)

    B J Rao

    2018-02-13

    Feb 13, 2018 ... Lorencova 2016), sociology, physics, computer science, economics and even biology ... dynamic complexity associated with them at multiple levels? .... Social anthropology and the science of chaos (Oxford: Berghahn Books).

  6. Computer vision for an autonomous mobile robot

    CSIR Research Space (South Africa)

    Withey, Daniel J

    2015-10-01

    Full Text Available Computer vision systems are essential for practical, autonomous, mobile robots – machines that employ artificial intelligence and control their own motion within an environment. As with biological systems, computer vision systems include the vision...

  7. Biological effects

    International Nuclear Information System (INIS)

    Trott, K.R.

    1973-01-01

    Following an introduction into the field of cellular radiation effect considering the most important experimental results, the biological significance of the colony formation ability is brought out. The inactivation concept of stem cells does not only prove to be good, according to the present results, in the interpretation of the pathogenesis of acute radiation effects on moult tissue, it also enables chronicle radiation injuries to be interpreted through changes in the fibrous part of the organs. Radiation therapy of tumours can also be explained to a large extent by the radiation effect on the unlimited reproductiveness of tumour cells. The more or less similar dose effect curves for healthy and tumour tissue in practice lead to intermittent irradiation. The dependence of the intermittent doses and intervals on factors such as Elkind recovery, synchronisation, redistribution, reoxygenation, repopulation and regeneration are reviewed. (ORU/LH) [de

  8. Model checking biological systems described using ambient calculus

    DEFF Research Database (Denmark)

    Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola

    2005-01-01

    Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....

  9. 7th International Workshop on Natural Computing

    CERN Document Server

    Hagiya, Masami

    2015-01-01

    This book highlights recent advances in natural computing, including biology and its theory, bio-inspired computing, computational aesthetics, computational models and theories, computing with natural media, philosophy of natural computing and educational technology. It presents extended versions of the best papers selected from the symposium “7th International Workshop on Natural Computing” (IWNC7), held in Tokyo, Japan, in 2013. The target audience is not limited to researchers working in natural computing but also those active in biological engineering, fine/media art design, aesthetics and philosophy.

  10. 8th International Workshop on Natural Computing

    CERN Document Server

    Hagiya, Masami

    2016-01-01

    This book highlights recent advances in natural computing, including biology and its theory, bio-inspired computing, computational aesthetics, computational models and theories, computing with natural media, philosophy of natural computing, and educational technology. It presents extended versions of the best papers selected from the “8th International Workshop on Natural Computing” (IWNC8), a symposium held in Hiroshima, Japan, in 2014. The target audience is not limited to researchers working in natural computing but also includes those active in biological engineering, fine/media art design, aesthetics, and philosophy.

  11. Probabilistic biological network alignment.

    Science.gov (United States)

    Todor, Andrei; Dobra, Alin; Kahveci, Tamer

    2013-01-01

    Interactions between molecules are probabilistic events. An interaction may or may not happen with some probability, depending on a variety of factors such as the size, abundance, or proximity of the interacting molecules. In this paper, we consider the problem of aligning two biological networks. Unlike existing methods, we allow one of the two networks to contain probabilistic interactions. Allowing interaction probabilities makes the alignment more biologically relevant at the expense of explosive growth in the number of alternative topologies that may arise from different subsets of interactions that take place. We develop a novel method that efficiently and precisely characterizes this massive search space. We represent the topological similarity between pairs of aligned molecules (i.e., proteins) with the help of random variables and compute their expected values. We validate our method showing that, without sacrificing the running time performance, it can produce novel alignments. Our results also demonstrate that our method identifies biologically meaningful mappings under a comprehensive set of criteria used in the literature as well as the statistical coherence measure that we developed to analyze the statistical significance of the similarity of the functions of the aligned protein pairs.

  12. Creating biological nanomaterials using synthetic biology

    International Nuclear Information System (INIS)

    Rice, MaryJoe K; Ruder, Warren C

    2014-01-01

    Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems. (review)

  13. Creating biological nanomaterials using synthetic biology.

    Science.gov (United States)

    Rice, MaryJoe K; Ruder, Warren C

    2014-02-01

    Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems.

  14. Quantifying electron transfer reactions in biological systems

    DEFF Research Database (Denmark)

    Sjulstok, Emil Sjulstok; Olsen, Jógvan Magnus Haugaard; Solov'yov, Ilia A

    2015-01-01

    which for example occur in photosynthesis, cellular respiration, DNA repair, and possibly magnetic field sensing. Quantum biology uses computation to model biological interactions in light of quantum mechanical effects and has primarily developed over the past decade as a result of convergence between...

  15. A Brief Introduction to Chinese Biological Biological

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Chinese Biological Abstracts sponsored by the Library, the Shanghai Institutes for Biological Sciences, the Biological Documentation and Information Network, all of the Chinese Academy of Sciences, commenced publication in 1987 and was initiated to provide access to the Chinese information in the field of biology.

  16. Optical Computing

    OpenAIRE

    Woods, Damien; Naughton, Thomas J.

    2008-01-01

    We consider optical computers that encode data using images and compute by transforming such images. We give an overview of a number of such optical computing architectures, including descriptions of the type of hardware commonly used in optical computing, as well as some of the computational efficiencies of optical devices. We go on to discuss optical computing from the point of view of computational complexity theory, with the aim of putting some old, and some very recent, re...

  17. Mapping biological systems to network systems

    CERN Document Server

    Rathore, Heena

    2016-01-01

    The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

  18. From computer to brain foundations of computational neuroscience

    CERN Document Server

    Lytton, William W

    2002-01-01

    Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

  19. Computational challenges in modeling gene regulatory events.

    Science.gov (United States)

    Pataskar, Abhijeet; Tiwari, Vijay K

    2016-10-19

    Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating "omics" data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology.

  20. Computer group

    International Nuclear Information System (INIS)

    Bauer, H.; Black, I.; Heusler, A.; Hoeptner, G.; Krafft, F.; Lang, R.; Moellenkamp, R.; Mueller, W.; Mueller, W.F.; Schati, C.; Schmidt, A.; Schwind, D.; Weber, G.

    1983-01-01

    The computer groups has been reorganized to take charge for the general purpose computers DEC10 and VAX and the computer network (Dataswitch, DECnet, IBM - connections to GSI and IPP, preparation for Datex-P). (orig.)

  1. Computer Engineers.

    Science.gov (United States)

    Moncarz, Roger

    2000-01-01

    Looks at computer engineers and describes their job, employment outlook, earnings, and training and qualifications. Provides a list of resources related to computer engineering careers and the computer industry. (JOW)

  2. Computer Music

    Science.gov (United States)

    Cook, Perry R.

    This chapter covers algorithms, technologies, computer languages, and systems for computer music. Computer music involves the application of computers and other digital/electronic technologies to music composition, performance, theory, history, and the study of perception. The field combines digital signal processing, computational algorithms, computer languages, hardware and software systems, acoustics, psychoacoustics (low-level perception of sounds from the raw acoustic signal), and music cognition (higher-level perception of musical style, form, emotion, etc.).

  3. Data integration in biological research: an overview.

    Science.gov (United States)

    Lapatas, Vasileios; Stefanidakis, Michalis; Jimenez, Rafael C; Via, Allegra; Schneider, Maria Victoria

    2015-12-01

    Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.

  4. On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

    Science.gov (United States)

    Gomez-Ramirez, Jaime; Sanz, Ricardo

    2013-09-01

    One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Genomes, Phylogeny, and Evolutionary Systems Biology

    Energy Technology Data Exchange (ETDEWEB)

    Medina, Monica

    2005-03-25

    With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics and computer science are now known as systems biology. Here I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.

  6. Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

    NARCIS (Netherlands)

    He, F.; Murabito, E.; Westerhoff, H.V.

    2016-01-01

    Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out throughin silicotheoretical studies with the aim to guide and complement furtherin vitroandin vivoexperimental

  7. Crosscut report: Exascale Requirements Reviews, March 9–10, 2017 – Tysons Corner, Virginia. An Office of Science review sponsored by: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Hack, James [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Riley, Katherine [Argonne National Lab., IL (United States). Argonne Leadership Computing Facility (ALCF); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). ESnet; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). ESnet; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility; Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). ESnet

    2018-01-22

    The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain

  8. Systems Biology of the Fluxome

    Directory of Open Access Journals (Sweden)

    Miguel A. Aon

    2015-07-01

    Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

  9. Biological effects of radiation

    International Nuclear Information System (INIS)

    2013-01-01

    This fourth chapter presents: cell structure and metabolism; radiation interaction with biological tissues; steps of the production of biological effect of radiation; radiosensitivity of tissues; classification of biological effects; reversibility, transmissivity and influence factors; pre-natal biological effects; biological effects in therapy and syndrome of acute irradiation

  10. Synthetic Biology: Knowledge Accessed by Everyone (Open Sources)

    Science.gov (United States)

    Sánchez Reyes, Patricia Margarita

    2016-01-01

    Using the principles of biology, along with engineering and with the help of computer, scientists manage to copy. DNA sequences from nature and use them to create new organisms. DNA is created through engineering and computer science managing to create life inside a laboratory. We cannot dismiss the role that synthetic biology could lead in…

  11. Analog computing

    CERN Document Server

    Ulmann, Bernd

    2013-01-01

    This book is a comprehensive introduction to analog computing. As most textbooks about this powerful computing paradigm date back to the 1960s and 1970s, it fills a void and forges a bridge from the early days of analog computing to future applications. The idea of analog computing is not new. In fact, this computing paradigm is nearly forgotten, although it offers a path to both high-speed and low-power computing, which are in even more demand now than they were back in the heyday of electronic analog computers.

  12. Computational composites

    DEFF Research Database (Denmark)

    Vallgårda, Anna K. A.; Redström, Johan

    2007-01-01

    Computational composite is introduced as a new type of composite material. Arguing that this is not just a metaphorical maneuver, we provide an analysis of computational technology as material in design, which shows how computers share important characteristics with other materials used in design...... and architecture. We argue that the notion of computational composites provides a precise understanding of the computer as material, and of how computations need to be combined with other materials to come to expression as material. Besides working as an analysis of computers from a designer’s point of view......, the notion of computational composites may also provide a link for computer science and human-computer interaction to an increasingly rapid development and use of new materials in design and architecture....

  13. COMPUTATIONAL SCIENCE CENTER

    International Nuclear Information System (INIS)

    DAVENPORT, J.

    2006-01-01

    Computational Science is an integral component of Brookhaven's multi science mission, and is a reflection of the increased role of computation across all of science. Brookhaven currently has major efforts in data storage and analysis for the Relativistic Heavy Ion Collider (RHIC) and the ATLAS detector at CERN, and in quantum chromodynamics. The Laboratory is host for the QCDOC machines (quantum chromodynamics on a chip), 10 teraflop/s computers which boast 12,288 processors each. There are two here, one for the Riken/BNL Research Center and the other supported by DOE for the US Lattice Gauge Community and other scientific users. A 100 teraflop/s supercomputer will be installed at Brookhaven in the coming year, managed jointly by Brookhaven and Stony Brook, and funded by a grant from New York State. This machine will be used for computational science across Brookhaven's entire research program, and also by researchers at Stony Brook and across New York State. With Stony Brook, Brookhaven has formed the New York Center for Computational Science (NYCCS) as a focal point for interdisciplinary computational science, which is closely linked to Brookhaven's Computational Science Center (CSC). The CSC has established a strong program in computational science, with an emphasis on nanoscale electronic structure and molecular dynamics, accelerator design, computational fluid dynamics, medical imaging, parallel computing and numerical algorithms. We have been an active participant in DOES SciDAC program (Scientific Discovery through Advanced Computing). We are also planning a major expansion in computational biology in keeping with Laboratory initiatives. Additional laboratory initiatives with a dependence on a high level of computation include the development of hydrodynamics models for the interpretation of RHIC data, computational models for the atmospheric transport of aerosols, and models for combustion and for energy utilization. The CSC was formed to bring together

  14. COMPUTATIONAL SCIENCE CENTER

    Energy Technology Data Exchange (ETDEWEB)

    DAVENPORT, J.

    2006-11-01

    Computational Science is an integral component of Brookhaven's multi science mission, and is a reflection of the increased role of computation across all of science. Brookhaven currently has major efforts in data storage and analysis for the Relativistic Heavy Ion Collider (RHIC) and the ATLAS detector at CERN, and in quantum chromodynamics. The Laboratory is host for the QCDOC machines (quantum chromodynamics on a chip), 10 teraflop/s computers which boast 12,288 processors each. There are two here, one for the Riken/BNL Research Center and the other supported by DOE for the US Lattice Gauge Community and other scientific users. A 100 teraflop/s supercomputer will be installed at Brookhaven in the coming year, managed jointly by Brookhaven and Stony Brook, and funded by a grant from New York State. This machine will be used for computational science across Brookhaven's entire research program, and also by researchers at Stony Brook and across New York State. With Stony Brook, Brookhaven has formed the New York Center for Computational Science (NYCCS) as a focal point for interdisciplinary computational science, which is closely linked to Brookhaven's Computational Science Center (CSC). The CSC has established a strong program in computational science, with an emphasis on nanoscale electronic structure and molecular dynamics, accelerator design, computational fluid dynamics, medical imaging, parallel computing and numerical algorithms. We have been an active participant in DOES SciDAC program (Scientific Discovery through Advanced Computing). We are also planning a major expansion in computational biology in keeping with Laboratory initiatives. Additional laboratory initiatives with a dependence on a high level of computation include the development of hydrodynamics models for the interpretation of RHIC data, computational models for the atmospheric transport of aerosols, and models for combustion and for energy utilization. The CSC was formed to

  15. Genome Annotation in a Community College Cell Biology Lab

    Science.gov (United States)

    Beagley, C. Timothy

    2013-01-01

    The Biology Department at Salt Lake Community College has used the IMG-ACT toolbox to introduce a genome mapping and annotation exercise into the laboratory portion of its Cell Biology course. This project provides students with an authentic inquiry-based learning experience while introducing them to computational biology and contemporary learning…

  16. Quantum Computing

    OpenAIRE

    Scarani, Valerio

    1998-01-01

    The aim of this thesis was to explain what quantum computing is. The information for the thesis was gathered from books, scientific publications, and news articles. The analysis of the information revealed that quantum computing can be broken down to three areas: theories behind quantum computing explaining the structure of a quantum computer, known quantum algorithms, and the actual physical realizations of a quantum computer. The thesis reveals that moving from classical memor...

  17. FIRST Quantum-(1980)-Computing DISCOVERY in Siegel-Rosen-Feynman-...A.-I. Neural-Networks: Artificial(ANN)/Biological(BNN) and Siegel FIRST Semantic-Web and Siegel FIRST ``Page''-``Brin'' ``PageRank'' PRE-Google Search-Engines!!!

    Science.gov (United States)

    Rosen, Charles; Siegel, Edward Carl-Ludwig; Feynman, Richard; Wunderman, Irwin; Smith, Adolph; Marinov, Vesco; Goldman, Jacob; Brine, Sergey; Poge, Larry; Schmidt, Erich; Young, Frederic; Goates-Bulmer, William-Steven; Lewis-Tsurakov-Altshuler, Thomas-Valerie-Genot; Ibm/Exxon Collaboration; Google/Uw Collaboration; Microsoft/Amazon Collaboration; Oracle/Sun Collaboration; Ostp/Dod/Dia/Nsa/W.-F./Boa/Ubs/Ub Collaboration

    2013-03-01

    Belew[Finding Out About, Cambridge(2000)] and separately full-decade pre-Page/Brin/Google FIRST Siegel-Rosen(Machine-Intelligence/Atherton)-Feynman-Smith-Marinov(Guzik Enterprises/Exxon-Enterprises/A.-I./Santa Clara)-Wunderman(H.-P.) [IBM Conf. on Computers and Mathematics, Stanford(1986); APS Mtgs.(1980s): Palo Alto/Santa Clara/San Francisco/...(1980s) MRS Spring-Mtgs.(1980s): Palo Alto/San Jose/San Francisco/...(1980-1992) FIRST quantum-computing via Bose-Einstein quantum-statistics(BEQS) Bose-Einstein CONDENSATION (BEC) in artificial-intelligence(A-I) artificial neural-networks(A-N-N) and biological neural-networks(B-N-N) and Siegel[J. Noncrystalline-Solids 40, 453(1980); Symp. on Fractals..., MRS Fall-Mtg., Boston(1989)-5-papers; Symp. on Scaling..., (1990); Symp. on Transport in Geometric-Constraint (1990)

  18. Philosophy of Systems and Synthetic Biology

    DEFF Research Database (Denmark)

    Green, Sara

    2017-01-01

    This entry aims to clarify how systems and synthetic biology contribute to and extend discussions within philosophy of science. Unlike fields such as developmental biology or molecular biology, systems and synthetic biology are not easily demarcated by a focus on a specific subject area or level...... of organization. Rather, they are characterized by the development and application of mathematical, computational, and synthetic modeling strategies in response to complex problems and challenges within the life sciences. Proponents of systems and synthetic biology often stress the necessity of a perspective...... that goes beyond the scope of molecular biology and genetic engineering, respectively. With the emphasis on systems and interaction networks, the approaches explicitly engage in one of the oldest philosophical discussions on the relationship between parts and wholes, or between reductionism and holism...

  19. Inverse problems in systems biology

    International Nuclear Information System (INIS)

    Engl, Heinz W; Lu, James; Müller, Stefan; Flamm, Christoph; Schuster, Peter; Kügler, Philipp

    2009-01-01

    Systems biology is a new discipline built upon the premise that an understanding of how cells and organisms carry out their functions cannot be gained by looking at cellular components in isolation. Instead, consideration of the interplay between the parts of systems is indispensable for analyzing, modeling, and predicting systems' behavior. Studying biological processes under this premise, systems biology combines experimental techniques and computational methods in order to construct predictive models. Both in building and utilizing models of biological systems, inverse problems arise at several occasions, for example, (i) when experimental time series and steady state data are used to construct biochemical reaction networks, (ii) when model parameters are identified that capture underlying mechanisms or (iii) when desired qualitative behavior such as bistability or limit cycle oscillations is engineered by proper choices of parameter combinations. In this paper we review principles of the modeling process in systems biology and illustrate the ill-posedness and regularization of parameter identification problems in that context. Furthermore, we discuss the methodology of qualitative inverse problems and demonstrate how sparsity enforcing regularization allows the determination of key reaction mechanisms underlying the qualitative behavior. (topical review)

  20. Quantum computing based on semiconductor nanowires

    NARCIS (Netherlands)

    Frolov, S.M.; Plissard, S.R.; Nadj-Perge, S.; Kouwenhoven, L.P.; Bakkers, E.P.A.M.

    2013-01-01

    A quantum computer will have computational power beyond that of conventional computers, which can be exploited for solving important and complex problems, such as predicting the conformations of large biological molecules. Materials play a major role in this emerging technology, as they can enable

  1. Dyneins: structure, biology and disease

    National Research Council Canada - National Science Library

    King, Stephen M

    2012-01-01

    .... From bench to bedside, Dynein: Structure, Biology and Disease offers research on fundamental cellular processes to researchers and clinicians across developmental biology, cell biology, molecular biology, biophysics, biomedicine...

  2. Grid Computing

    Indian Academy of Sciences (India)

    A computing grid interconnects resources such as high performancecomputers, scientific databases, and computercontrolledscientific instruments of cooperating organizationseach of which is autonomous. It precedes and is quitedifferent from cloud computing, which provides computingresources by vendors to customers ...

  3. Green Computing

    Directory of Open Access Journals (Sweden)

    K. Shalini

    2013-01-01

    Full Text Available Green computing is all about using computers in a smarter and eco-friendly way. It is the environmentally responsible use of computers and related resources which includes the implementation of energy-efficient central processing units, servers and peripherals as well as reduced resource consumption and proper disposal of electronic waste .Computers certainly make up a large part of many people lives and traditionally are extremely damaging to the environment. Manufacturers of computer and its parts have been espousing the green cause to help protect environment from computers and electronic waste in any way.Research continues into key areas such as making the use of computers as energy-efficient as Possible, and designing algorithms and systems for efficiency-related computer technologies.

  4. Biological conversion system

    Science.gov (United States)

    Scott, C.D.

    A system for bioconversion of organic material comprises a primary bioreactor column wherein a biological active agent (zymomonas mobilis) converts the organic material (sugar) to a product (alcohol), a rejuvenator column wherein the biological activity of said biological active agent is enhanced, and means for circulating said biological active agent between said primary bioreactor column and said rejuvenator column.

  5. Translational environmental biology: cell biology informing conservation.

    Science.gov (United States)

    Traylor-Knowles, Nikki; Palumbi, Stephen R

    2014-05-01

    Typically, findings from cell biology have been beneficial for preventing human disease. However, translational applications from cell biology can also be applied to conservation efforts, such as protecting coral reefs. Recent efforts to understand the cell biological mechanisms maintaining coral health such as innate immunity and acclimatization have prompted new developments in conservation. Similar to biomedicine, we urge that future efforts should focus on better frameworks for biomarker development to protect coral reefs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Quantum computers and quantum computations

    International Nuclear Information System (INIS)

    Valiev, Kamil' A

    2005-01-01

    This review outlines the principles of operation of quantum computers and their elements. The theory of ideal computers that do not interact with the environment and are immune to quantum decohering processes is presented. Decohering processes in quantum computers are investigated. The review considers methods for correcting quantum computing errors arising from the decoherence of the state of the quantum computer, as well as possible methods for the suppression of the decohering processes. A brief enumeration of proposed quantum computer realizations concludes the review. (reviews of topical problems)

  7. Quantum Computing for Computer Architects

    CERN Document Server

    Metodi, Tzvetan

    2011-01-01

    Quantum computers can (in theory) solve certain problems far faster than a classical computer running any known classical algorithm. While existing technologies for building quantum computers are in their infancy, it is not too early to consider their scalability and reliability in the context of the design of large-scale quantum computers. To architect such systems, one must understand what it takes to design and model a balanced, fault-tolerant quantum computer architecture. The goal of this lecture is to provide architectural abstractions for the design of a quantum computer and to explore

  8. Pervasive Computing

    NARCIS (Netherlands)

    Silvis-Cividjian, N.

    This book provides a concise introduction to Pervasive Computing, otherwise known as Internet of Things (IoT) and Ubiquitous Computing (Ubicomp) which addresses the seamless integration of computing systems within everyday objects. By introducing the core topics and exploring assistive pervasive

  9. Computational vision

    CERN Document Server

    Wechsler, Harry

    1990-01-01

    The book is suitable for advanced courses in computer vision and image processing. In addition to providing an overall view of computational vision, it contains extensive material on topics that are not usually covered in computer vision texts (including parallel distributed processing and neural networks) and considers many real applications.

  10. Spatial Computation

    Science.gov (United States)

    2003-12-01

    Computation and today’s microprocessors with the approach to operating system architecture, and the controversy between microkernels and monolithic kernels...Both Spatial Computation and microkernels break away a relatively monolithic architecture into in- dividual lightweight pieces, well specialized...for their particular functionality. Spatial Computation removes global signals and control, in the same way microkernels remove the global address

  11. Integrating biological redesign: where synthetic biology came from and where it needs to go.

    Science.gov (United States)

    Way, Jeffrey C; Collins, James J; Keasling, Jay D; Silver, Pamela A

    2014-03-27

    Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Computational Embryology and Predictive Toxicology of Cleft Palate

    Science.gov (United States)

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

  13. Parallel computations

    CERN Document Server

    1982-01-01

    Parallel Computations focuses on parallel computation, with emphasis on algorithms used in a variety of numerical and physical applications and for many different types of parallel computers. Topics covered range from vectorization of fast Fourier transforms (FFTs) and of the incomplete Cholesky conjugate gradient (ICCG) algorithm on the Cray-1 to calculation of table lookups and piecewise functions. Single tridiagonal linear systems and vectorized computation of reactive flow are also discussed.Comprised of 13 chapters, this volume begins by classifying parallel computers and describing techn

  14. Human Computation

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    What if people could play computer games and accomplish work without even realizing it? What if billions of people collaborated to solve important problems for humanity or generate training data for computers? My work aims at a general paradigm for doing exactly that: utilizing human processing power to solve computational problems in a distributed manner. In particular, I focus on harnessing human time and energy for addressing problems that computers cannot yet solve. Although computers have advanced dramatically in many respects over the last 50 years, they still do not possess the basic conceptual intelligence or perceptual capabilities...

  15. Quantum computation

    International Nuclear Information System (INIS)

    Deutsch, D.

    1992-01-01

    As computers become ever more complex, they inevitably become smaller. This leads to a need for components which are fabricated and operate on increasingly smaller size scales. Quantum theory is already taken into account in microelectronics design. This article explores how quantum theory will need to be incorporated into computers in future in order to give them their components functionality. Computation tasks which depend on quantum effects will become possible. Physicists may have to reconsider their perspective on computation in the light of understanding developed in connection with universal quantum computers. (UK)

  16. Computer software.

    Science.gov (United States)

    Rosenthal, L E

    1986-10-01

    Software is the component in a computer system that permits the hardware to perform the various functions that a computer system is capable of doing. The history of software and its development can be traced to the early nineteenth century. All computer systems are designed to utilize the "stored program concept" as first developed by Charles Babbage in the 1850s. The concept was lost until the mid-1940s, when modern computers made their appearance. Today, because of the complex and myriad tasks that a computer system can perform, there has been a differentiation of types of software. There is software designed to perform specific business applications. There is software that controls the overall operation of a computer system. And there is software that is designed to carry out specialized tasks. Regardless of types, software is the most critical component of any computer system. Without it, all one has is a collection of circuits, transistors, and silicone chips.

  17. Computer sciences

    Science.gov (United States)

    Smith, Paul H.

    1988-01-01

    The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

  18. Computational Protein Design

    DEFF Research Database (Denmark)

    Johansson, Kristoffer Enøe

    Proteins are the major functional group of molecules in biology. The impact of protein science on medicine and chemical productions is rapidly increasing. However, the greatest potential remains to be realized. The fi eld of protein design has advanced computational modeling from a tool of support...... to a central method that enables new developments. For example, novel enzymes with functions not found in natural proteins have been de novo designed to give enough activity for experimental optimization. This thesis presents the current state-of-the-art within computational design methods together...... with a novel method based on probability theory. With the aim of assembling a complete pipeline for protein design, this work touches upon several aspects of protein design. The presented work is the computational half of a design project where the other half is dedicated to the experimental part...

  19. Models for synthetic biology.

    Science.gov (United States)

    Kaznessis, Yiannis N

    2007-11-06

    Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior. The objective is the design and construction of new biological devices and systems to deliver useful applications. Numerous synthetic gene circuits have been created in the past decade, including bistable switches, oscillators, and logic gates, and possible applications abound, including biofuels, detectors for biochemical and chemical weapons, disease diagnosis, and gene therapies. More than fifty years after the discovery of the molecular structure of DNA, molecular biology is mature enough for real quantification that is useful for biological engineering applications, similar to the revolution in modeling in chemistry in the 1950s. With the excitement that synthetic biology is generating, the engineering and biological science communities appear remarkably willing to cross disciplinary boundaries toward a common goal.

  20. Computational biomechanics for medicine imaging, modeling and computing

    CERN Document Server

    Doyle, Barry; Wittek, Adam; Nielsen, Poul; Miller, Karol

    2016-01-01

    The Computational Biomechanics for Medicine titles provide an opportunity for specialists in computational biomechanics to present their latest methodologies and advancements. This volume comprises eighteen of the newest approaches and applications of computational biomechanics, from researchers in Australia, New Zealand, USA, UK, Switzerland, Scotland, France and Russia. Some of the interesting topics discussed are: tailored computational models; traumatic brain injury; soft-tissue mechanics; medical image analysis; and clinically-relevant simulations. One of the greatest challenges facing the computational engineering community is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences, and medicine. We hope the research presented within this book series will contribute to overcoming this grand challenge.

  1. Mammalian synthetic biology for studying the cell.

    Science.gov (United States)

    Mathur, Melina; Xiang, Joy S; Smolke, Christina D

    2017-01-02

    Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

  2. Micro-separation toward systems biology.

    Science.gov (United States)

    Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

    2006-02-17

    Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

  3. Computer programming and computer systems

    CERN Document Server

    Hassitt, Anthony

    1966-01-01

    Computer Programming and Computer Systems imparts a "reading knowledge? of computer systems.This book describes the aspects of machine-language programming, monitor systems, computer hardware, and advanced programming that every thorough programmer should be acquainted with. This text discusses the automatic electronic digital computers, symbolic language, Reverse Polish Notation, and Fortran into assembly language. The routine for reading blocked tapes, dimension statements in subroutines, general-purpose input routine, and efficient use of memory are also elaborated.This publication is inten

  4. Integrative Systems Biology Applied to Toxicology

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning

    associated with combined exposure to multiple chemicals. Testing all possible combinations of the tens of thousands environmental chemicals is impractical. This PhD project was launched to apply existing computational systems biology methods to toxicological research. In this thesis, I present in three...... of a system thereby suggesting new ways of thinking specific toxicological endpoints. Furthermore, computational methods can serve as valuable input for the hypothesis generating phase of the preparations of a research project....

  5. Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

    Science.gov (United States)

    Jalili, Mahdi

    2018-03-01

    I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

  6. Berkeley Lab Computing Sciences: Accelerating Scientific Discovery

    International Nuclear Information System (INIS)

    Hules, John A.

    2008-01-01

    Scientists today rely on advances in computer science, mathematics, and computational science, as well as large-scale computing and networking facilities, to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences organization researches, develops, and deploys new tools and technologies to meet these needs and to advance research in such areas as global climate change, combustion, fusion energy, nanotechnology, biology, and astrophysics

  7. Computational neuroscience a first course

    CERN Document Server

    Mallot, Hanspeter A

    2013-01-01

    Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and  equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.

  8. Toward synthesizing executable models in biology.

    Science.gov (United States)

    Fisher, Jasmin; Piterman, Nir; Bodik, Rastislav

    2014-01-01

    Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell's behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions), even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modeling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

  9. Towards Synthesizing Executable Models in Biology

    Directory of Open Access Journals (Sweden)

    Jasmin eFisher

    2014-12-01

    Full Text Available Over the last decade, executable models of biological behaviors have repeatedly provided new scientific discoveries, uncovered novel insights, and directed new experimental avenues. These models are computer programs whose execution mechanistically simulates aspects of the cell’s behaviors. If the observed behavior of the program agrees with the observed biological behavior, then the program explains the phenomena. This approach has proven beneficial for gaining new biological insights and directing new experimental avenues. One advantage of this approach is that techniques for analysis of computer programs can be applied to the analysis of executable models. For example, one can confirm that a model agrees with experiments for all possible executions of the model (corresponding to all environmental conditions, even if there are a huge number of executions. Various formal methods have been adapted for this context, for example, model checking or symbolic analysis of state spaces. To avoid manual construction of executable models, one can apply synthesis, a method to produce programs automatically from high-level specifications. In the context of biological modelling, synthesis would correspond to extracting executable models from experimental data. We survey recent results about the usage of the techniques underlying synthesis of computer programs for the inference of biological models from experimental data. We describe synthesis of biological models from curated mutation experiment data, inferring network connectivity models from phosphoproteomic data, and synthesis of Boolean networks from gene expression data. While much work has been done on automated analysis of similar datasets using machine learning and artificial intelligence, using synthesis techniques provides new opportunities such as efficient computation of disambiguating experiments, as well as the ability to produce different kinds of models automatically from biological data.

  10. Industrial systems biology and its impact on synthetic biology of yeast cell factories.

    Science.gov (United States)

    Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

    2016-06-01

    Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  11. Industrial systems biology and its impact on synthetic biology of yeast cell factories

    DEFF Research Database (Denmark)

    Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

    2016-01-01

    Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...

  12. Computational Composites

    DEFF Research Database (Denmark)

    Vallgårda, Anna K. A.

    to understand the computer as a material like any other material we would use for design, like wood, aluminum, or plastic. That as soon as the computer forms a composition with other materials it becomes just as approachable and inspiring as other smart materials. I present a series of investigations of what...... Computational Composite, and Telltale). Through the investigations, I show how the computer can be understood as a material and how it partakes in a new strand of materials whose expressions come to be in context. I uncover some of their essential material properties and potential expressions. I develop a way...

  13. When cloud computing meets bioinformatics: a review.

    Science.gov (United States)

    Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong

    2013-10-01

    In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.

  14. Cellular computing

    National Research Council Canada - National Science Library

    Amos, Martyn

    2004-01-01

    ... 120 Ron Weiss, Thomas F. Knight Jr., and Gerald Sussman 8 The Biology of Integration of Cells into Microscale and Nanoscale Systems 148 Michael L. Simpson, Timothy E. McKnight, Michael A. Guillor...

  15. Biology of Blood

    Science.gov (United States)

    ... switch to the Professional version Home Blood Disorders Biology of Blood Overview of Blood Resources In This ... Version. DOCTORS: Click here for the Professional Version Biology of Blood Overview of Blood Components of Blood ...

  16. Biological basis of detoxication

    National Research Council Canada - National Science Library

    Caldwell, John; Jakoby, William B

    1983-01-01

    This volume considers that premise that most of the major patterns of biological conversion of foreign compounds are known and may have predictive value in assessing the biological course for novel compounds...

  17. Bringing Advanced Computational Techniques to Energy Research

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, Julie C

    2012-11-17

    Please find attached our final technical report for the BACTER Institute award. BACTER was created as a graduate and postdoctoral training program for the advancement of computational biology applied to questions of relevance to bioenergy research.

  18. Fusion of biological membranes

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics; Volume 64; Issue 6. Fusion of biological membranes. K Katsov M Müller M Schick. Invited Talks:- Topic 11. Biologically motivated problems (protein-folding models, dynamics at the scale of the cell; biological networks, evolution models, etc.) Volume 64 Issue 6 June 2005 pp ...

  19. Biology Myth-Killers

    Science.gov (United States)

    Lampert, Evan

    2014-01-01

    "Biology Myth-Killers" is an activity designed to identify and correct common misconceptions for high school and college introductory biology courses. Students identify common myths, which double as biology misconceptions, and use appropriate sources to share the "truth" about the myths. This learner-centered activity is a fun…

  20. Designing synthetic biology.

    Science.gov (United States)

    Agapakis, Christina M

    2014-03-21

    Synthetic biology is frequently defined as the application of engineering design principles to biology. Such principles are intended to streamline the practice of biological engineering, to shorten the time required to design, build, and test synthetic gene networks. This streamlining of iterative design cycles can facilitate the future construction of biological systems for a range of applications in the production of fuels, foods, materials, and medicines. The promise of these potential applications as well as the emphasis on design has prompted critical reflection on synthetic biology from design theorists and practicing designers from many fields, who can bring valuable perspectives to the discipline. While interdisciplinary connections between biologists and engineers have built synthetic biology via the science and the technology of biology, interdisciplinary collaboration with artists, designers, and social theorists can provide insight on the connections between technology and society. Such collaborations can open up new avenues and new principles for research and design, as well as shed new light on the challenging context-dependence-both biological and social-that face living technologies at many scales. This review is inspired by the session titled "Design and Synthetic Biology: Connecting People and Technology" at Synthetic Biology 6.0 and covers a range of literature on design practice in synthetic biology and beyond. Critical engagement with how design is used to shape the discipline opens up new possibilities for how we might design the future of synthetic biology.

  1. Radiation biology. Chapter 20

    Energy Technology Data Exchange (ETDEWEB)

    Wondergem, J. [International Atomic Energy Agency, Vienna (Austria)

    2014-09-15

    Radiation biology (radiobiology) is the study of the action of ionizing radiations on living matter. This chapter gives an overview of the biological effects of ionizing radiation and discusses the physical, chemical and biological variables that affect dose response at the cellular, tissue and whole body levels at doses and dose rates relevant to diagnostic radiology.

  2. General Biology Syllabus.

    Science.gov (United States)

    Hunter, Scott; Watthews, Thomas

    This syllabus has been developed as an alternative to Regents biology and is intended for the average student who could benefit from an introductory biology course. It is divided into seven major units dealing with, respectively: (1) similarities among living things; (2) human biology (focusing on nutrition, transport, respiration, excretion, and…

  3. Upgrading Undergraduate Biology Education

    Science.gov (United States)

    Musante, Susan

    2011-01-01

    On many campuses throughout the country, undergraduate biology education is in serious need of an upgrade. During the past few decades, the body of biological knowledge has grown exponentially, and as a research endeavor, the practice of biology has evolved. Education research has also made great strides, revealing many new insights into how…

  4. Chemistry and Biology

    Science.gov (United States)

    Wigston, David L.

    1970-01-01

    Discusses the relationship between chemisty and biology in the science curriculum. Points out the differences in perception of the disciplines, which the physical scientists favoring reductionism. Suggests that biology departments offer a special course for chemistry students, just as the chemistry departments have done for biology students.…

  5. GPGPU COMPUTING

    Directory of Open Access Journals (Sweden)

    BOGDAN OANCEA

    2012-05-01

    Full Text Available Since the first idea of using GPU to general purpose computing, things have evolved over the years and now there are several approaches to GPU programming. GPU computing practically began with the introduction of CUDA (Compute Unified Device Architecture by NVIDIA and Stream by AMD. These are APIs designed by the GPU vendors to be used together with the hardware that they provide. A new emerging standard, OpenCL (Open Computing Language tries to unify different GPU general computing API implementations and provides a framework for writing programs executed across heterogeneous platforms consisting of both CPUs and GPUs. OpenCL provides parallel computing using task-based and data-based parallelism. In this paper we will focus on the CUDA parallel computing architecture and programming model introduced by NVIDIA. We will present the benefits of the CUDA programming model. We will also compare the two main approaches, CUDA and AMD APP (STREAM and the new framwork, OpenCL that tries to unify the GPGPU computing models.

  6. Quantum Computing

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 5; Issue 9. Quantum Computing - Building Blocks of a Quantum Computer. C S Vijay Vishal Gupta. General Article Volume 5 Issue 9 September 2000 pp 69-81. Fulltext. Click here to view fulltext PDF. Permanent link:

  7. Platform computing

    CERN Multimedia

    2002-01-01

    "Platform Computing releases first grid-enabled workload management solution for IBM eServer Intel and UNIX high performance computing clusters. This Out-of-the-box solution maximizes the performance and capability of applications on IBM HPC clusters" (1/2 page) .

  8. Quantum Computing

    Indian Academy of Sciences (India)

    In the first part of this article, we had looked at how quantum physics can be harnessed to make the building blocks of a quantum computer. In this concluding part, we look at algorithms which can exploit the power of this computational device, and some practical difficulties in building such a device. Quantum Algorithms.

  9. Quantum computing

    OpenAIRE

    Burba, M.; Lapitskaya, T.

    2017-01-01

    This article gives an elementary introduction to quantum computing. It is a draft for a book chapter of the "Handbook of Nature-Inspired and Innovative Computing", Eds. A. Zomaya, G.J. Milburn, J. Dongarra, D. Bader, R. Brent, M. Eshaghian-Wilner, F. Seredynski (Springer, Berlin Heidelberg New York, 2006).

  10. Computational Pathology

    Science.gov (United States)

    Louis, David N.; Feldman, Michael; Carter, Alexis B.; Dighe, Anand S.; Pfeifer, John D.; Bry, Lynn; Almeida, Jonas S.; Saltz, Joel; Braun, Jonathan; Tomaszewski, John E.; Gilbertson, John R.; Sinard, John H.; Gerber, Georg K.; Galli, Stephen J.; Golden, Jeffrey A.; Becich, Michael J.

    2016-01-01

    Context We define the scope and needs within the new discipline of computational pathology, a discipline critical to the future of both the practice of pathology and, more broadly, medical practice in general. Objective To define the scope and needs of computational pathology. Data Sources A meeting was convened in Boston, Massachusetts, in July 2014 prior to the annual Association of Pathology Chairs meeting, and it was attended by a variety of pathologists, including individuals highly invested in pathology informatics as well as chairs of pathology departments. Conclusions The meeting made recommendations to promote computational pathology, including clearly defining the field and articulating its value propositions; asserting that the value propositions for health care systems must include means to incorporate robust computational approaches to implement data-driven methods that aid in guiding individual and population health care; leveraging computational pathology as a center for data interpretation in modern health care systems; stating that realizing the value proposition will require working with institutional administrations, other departments, and pathology colleagues; declaring that a robust pipeline should be fostered that trains and develops future computational pathologists, for those with both pathology and non-pathology backgrounds; and deciding that computational pathology should serve as a hub for data-related research in health care systems. The dissemination of these recommendations to pathology and bioinformatics departments should help facilitate the development of computational pathology. PMID:26098131

  11. Synthetic Biology: Putting Synthesis into Biology

    Science.gov (United States)

    Liang, Jing; Luo, Yunzi; Zhao, Huimin

    2010-01-01

    The ability to manipulate living organisms is at the heart of a range of emerging technologies that serve to address important and current problems in environment, energy, and health. However, with all its complexity and interconnectivity, biology has for many years been recalcitrant to engineering manipulations. The recent advances in synthesis, analysis, and modeling methods have finally provided the tools necessary to manipulate living systems in meaningful ways, and have led to the coining of a field named synthetic biology. The scope of synthetic biology is as complicated as life itself – encompassing many branches of science, and across many scales of application. New DNA synthesis and assembly techniques have made routine the customization of very large DNA molecules. This in turn has allowed the incorporation of multiple genes and pathways. By coupling these with techniques that allow for the modeling and design of protein functions, scientists have now gained the tools to create completely novel biological machineries. Even the ultimate biological machinery – a self-replicating organism – is being pursued at this moment. It is the purpose of this review to dissect and organize these various components of synthetic biology into a coherent picture. PMID:21064036

  12. Approximate Bayesian computation.

    Directory of Open Access Journals (Sweden)

    Mikael Sunnåker

    Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.

  13. Cloud Computing

    DEFF Research Database (Denmark)

    Krogh, Simon

    2013-01-01

    with technological changes, the paradigmatic pendulum has swung between increased centralization on one side and a focus on distributed computing that pushes IT power out to end users on the other. With the introduction of outsourcing and cloud computing, centralization in large data centers is again dominating...... the IT scene. In line with the views presented by Nicolas Carr in 2003 (Carr, 2003), it is a popular assumption that cloud computing will be the next utility (like water, electricity and gas) (Buyya, Yeo, Venugopal, Broberg, & Brandic, 2009). However, this assumption disregards the fact that most IT production......), for instance, in establishing and maintaining trust between the involved parties (Sabherwal, 1999). So far, research in cloud computing has neglected this perspective and focused entirely on aspects relating to technology, economy, security and legal questions. While the core technologies of cloud computing (e...

  14. Computability theory

    CERN Document Server

    Weber, Rebecca

    2012-01-01

    What can we compute--even with unlimited resources? Is everything within reach? Or are computations necessarily drastically limited, not just in practice, but theoretically? These questions are at the heart of computability theory. The goal of this book is to give the reader a firm grounding in the fundamentals of computability theory and an overview of currently active areas of research, such as reverse mathematics and algorithmic randomness. Turing machines and partial recursive functions are explored in detail, and vital tools and concepts including coding, uniformity, and diagonalization are described explicitly. From there the material continues with universal machines, the halting problem, parametrization and the recursion theorem, and thence to computability for sets, enumerability, and Turing reduction and degrees. A few more advanced topics round out the book before the chapter on areas of research. The text is designed to be self-contained, with an entire chapter of preliminary material including re...

  15. Synthetic biology advances for pharmaceutical production

    OpenAIRE

    Breitling, Rainer; Takano, Eriko

    2015-01-01

    Synthetic biology enables a new generation of microbial engineering for the biotechnological production of pharmaceuticals and other high-value chemicals. This review presents an overview of recent advances in the field, describing new computational and experimental tools for the discovery, optimization and production of bioactive molecules, and outlining progress towards the application of these tools to pharmaceutical production systems.

  16. Synthetic biology advances for pharmaceutical production

    Science.gov (United States)

    Breitling, Rainer; Takano, Eriko

    2015-01-01

    Synthetic biology enables a new generation of microbial engineering for the biotechnological production of pharmaceuticals and other high-value chemicals. This review presents an overview of recent advances in the field, describing new computational and experimental tools for the discovery, optimization and production of bioactive molecules, and outlining progress towards the application of these tools to pharmaceutical production systems. PMID:25744872

  17. Simple Calculation Programs for Biology Immunological Methods

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Simple Calculation Programs for Biology Immunological Methods. Computation of Ab/Ag Concentration from EISA data. Graphical Method; Raghava et al., 1992, J. Immuno. Methods 153: 263. Determination of affinity of Monoclonal Antibody. Using non-competitive ...

  18. Function-Based Algorithms for Biological Sequences

    Science.gov (United States)

    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…

  19. Synthetic biological networks

    International Nuclear Information System (INIS)

    Archer, Eric; Süel, Gürol M

    2013-01-01

    Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics. (review article)

  20. Computational Intelligence for Engineering Systems

    CERN Document Server

    Madureira, A; Vale, Zita

    2011-01-01

    "Computational Intelligence for Engineering Systems" provides an overview and original analysis of new developments and advances in several areas of computational intelligence. Computational Intelligence have become the road-map for engineers to develop and analyze novel techniques to solve problems in basic sciences (such as physics, chemistry and biology) and engineering, environmental, life and social sciences. The contributions are written by international experts, who provide up-to-date aspects of the topics discussed and present recent, original insights into their own experien