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

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.

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.

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.

Diffraction Techniques in Structural Biology

Science.gov (United States)

Egli, Martin

2016-01-01

A detailed understanding of chemical and biological function and the mechanisms underlying the molecular activities ultimately requires atomic-resolution structural data. Diffraction-based techniques such as single-crystal X-ray crystallography, electron microscopy, and neutron diffraction are well established and they have paved the road to the stunning successes of modern-day structural biology. The major advances achieved in the last 20 years in all aspects of structural research, including sample preparation, crystallization, the construction of synchrotron and spallation sources, phasing approaches, and high-speed computing and visualization, now provide specialists and nonspecialists alike with a steady flow of molecular images of unprecedented detail. The present unit combines a general overview of diffraction methods with a detailed description of the process of a single-crystal X-ray structure determination experiment, from chemical synthesis or expression to phasing and refinement, analysis, and quality control. For novices it may serve as a stepping-stone to more in-depth treatises of the individual topics. Readers relying on structural information for interpreting functional data may find it a useful consumer guide. PMID:27248784

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.

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.

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 ...

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.

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.

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.

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.

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...

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.

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.

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.

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

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.

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.

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.

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

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.

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.

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

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

Hemminger Bradley M

2009-08-01

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

Structural Molecular Biology 2017 | SSRL

Science.gov (United States)

Highlights Training Workshops & Summer Schools Summer Students Structural Molecular Biology Illuminating experimental driver for structural biology research, serving the needs of a large number of academic and — Our Mission The SSRL Structural Molecular Biology program operates as an integrated resource and has

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)

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.

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.

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

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)

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.

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

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

Directory of Open Access Journals (Sweden)

Mihai V. Putz

2016-07-01

Full Text Available Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding and quantitative (for predicting mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD as the revived precursor for comparative molecular field analyses (CoMFA and comparative molecular similarity indices analysis (CoMSIA; all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy-methyl]-6-(phenylthiothymine congeners’ (HEPT ligands antiviral activity against Human Immunodeficiency Virus of first type (HIV-1 and new pharmacophores in treating severe genetic disorders (like depression and psychosis, respectively, all involving 3D pharmacophore interactions.

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.

Computational Study on Atomic Structures, Electronic Properties, and Chemical Reactions at Surfaces and Interfaces and in Biomaterials

Science.gov (United States)

Takano, Yu; Kobayashi, Nobuhiko; Morikawa, Yoshitada

2018-06-01

Through computer simulations using atomistic models, it is becoming possible to calculate the atomic structures of localized defects or dopants in semiconductors, chemically active sites in heterogeneous catalysts, nanoscale structures, and active sites in biological systems precisely. Furthermore, it is also possible to clarify physical and chemical properties possessed by these nanoscale structures such as electronic states, electronic and atomic transport properties, optical properties, and chemical reactivity. It is sometimes quite difficult to clarify these nanoscale structure-function relations experimentally and, therefore, accurate computational studies are indispensable in materials science. In this paper, we review recent studies on the relation between local structures and functions for inorganic, organic, and biological systems by using atomistic computer simulations.

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...

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:

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...

Structural biology at York Structural Biology Laboratory; laboratory information management systems for structural genomics

Czech Academy of Sciences Publication Activity Database

Dohnálek, Jan

2005-01-01

Roč. 12, č. 1 (2005), s. 3 ISSN 1211-5894. [Meeting of Structural Biologists /4./. 10.03.2005-12.03.2005, Nové Hrady] R&D Projects: GA MŠk(CZ) 1K05008 Keywords : structural biology * LIMS * structural genomics Subject RIV: CD - Macromolecular Chemistry

Computational structural mechanics for engine structures

Science.gov (United States)

Chamis, C. C.

1989-01-01

The computational structural mechanics (CSM) program at Lewis encompasses: (1) fundamental aspects for formulating and solving structural mechanics problems, and (2) development of integrated software systems to computationally simulate the performance/durability/life of engine structures. It is structured to mainly supplement, complement, and whenever possible replace, costly experimental efforts which are unavoidable during engineering research and development programs. Specific objectives include: investigate unique advantages of parallel and multiprocesses for: reformulating/solving structural mechanics and formulating/solving multidisciplinary mechanics and develop integrated structural system computational simulators for: predicting structural performances, evaluating newly developed methods, and for identifying and prioritizing improved/missing methods needed. Herein the CSM program is summarized with emphasis on the Engine Structures Computational Simulator (ESCS). Typical results obtained using ESCS are described to illustrate its versatility.

Structural Biology in the context of EGEE

CERN Document Server

García, D; Carazo, J M; Valverde, J R; Moscicki, J; Muraru, A

2007-01-01

Electron microscopy (EM) is a crucial technique, which allows Structural Biology researchers to characterize macromolecular assemblies in distinct functional states. Image processing in three dimensional EM (3D-EM) is used by a flourishing community (exemplarized by the EU funded 3D-EM NoE) and is characterized by voluminous data and large computing requirements, making this a problem well suited for Grid computing and the EGEE infrastructure. There are various steps in the 3D-EM refinement process that may benefit from Grid computing. To start with, large numbers of experimental images need to be averaged. Nowadays, typically tens of thousands of images are used, while future studies may routinely employ millions of images. Our group has been developing Xmipp, a package for single-particle 3D-EM image processing. Using Xmipp, the classification of 91,000 ribosome projections into 4 classes took more than 2500 CPU hours using the resources of the MareNostrum supercomputer at the Barcelona Supercomputing Centr...

Data acquisition and analysis at the Structural Biology Center

International Nuclear Information System (INIS)

Westbrook, M.L.; Coleman, T.A.; Daly, R.T.; Pflugrath, J.W.

1996-01-01

The Structural Biology Center (SBC), a national user facility for macromolecular crystallography located at Argonne National Laboratory's Advanced Photon Source, is currently being built and commissioned. SBC facilities include a bending-magnet beamline, an insertion-device beamline, laboratory and office space adjacent to the beamlines, and associated instrumentation, experimental apparatus, and facilities. SBC technical facilities will support anomalous dispersion phasing experiments, data collection from microcrystals, data collection from crystals with large molecular structures and rapid data collection from multiple related crystal structures for protein engineering and drug design. The SBC Computing Systems and Software Engineering Group is tasked with developing the SBC Control System, which includes computing systems, network, and software. The emphasis of SBC Control System development has been to provide efficient and convenient beamline control, data acquisition, and data analysis for maximal facility and experimenter productivity. This paper describes the SBC Control System development, specifically data acquisition and analysis at the SBC, and the development methods used to meet this goal

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...

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...

A Self-Assisting Protein Folding Model for Teaching Structural Molecular Biology.

Science.gov (United States)

Davenport, Jodi; Pique, Michael; Getzoff, Elizabeth; Huntoon, Jon; Gardner, Adam; Olson, Arthur

2017-04-04

Structural molecular biology is now becoming part of high school science curriculum thus posing a challenge for teachers who need to convey three-dimensional (3D) structures with conventional text and pictures. In many cases even interactive computer graphics does not go far enough to address these challenges. We have developed a flexible model of the polypeptide backbone using 3D printing technology. With this model we have produced a polypeptide assembly kit to create an idealized model of the Triosephosphate isomerase mutase enzyme (TIM), which forms a structure known as TIM barrel. This kit has been used in a laboratory practical where students perform a step-by-step investigation into the nature of protein folding, starting with the handedness of amino acids to the formation of secondary and tertiary structure. Based on the classroom evidence we collected, we conclude that these models are valuable and inexpensive resource for teaching structural molecular biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Advances in Structural Biology and the Application to Biological Filament Systems.

Science.gov (United States)

Popp, David; Koh, Fujiet; Scipion, Clement P M; Ghoshdastider, Umesh; Narita, Akihiro; Holmes, Kenneth C; Robinson, Robert C

2018-04-01

Structural biology has experienced several transformative technological advances in recent years. These include: development of extremely bright X-ray sources (microfocus synchrotron beamlines and free electron lasers) and the use of electrons to extend protein crystallography to ever decreasing crystal sizes; and an increase in the resolution attainable by cryo-electron microscopy. Here we discuss the use of these techniques in general terms and highlight their application for biological filament systems, an area that is severely underrepresented in atomic resolution structures. We assemble a model of a capped tropomyosin-actin minifilament to demonstrate the utility of combining structures determined by different techniques. Finally, we survey the methods that attempt to transform high resolution structural biology into more physiological environments, such as the cell. Together these techniques promise a compelling decade for structural biology and, more importantly, they will provide exciting discoveries in understanding the designs and purposes of biological machines. © 2018 The Authors. BioEssays Published by WILEY Periodicals, Inc.

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 ...

Structural Identifiability of Dynamic Systems Biology Models.

Science.gov (United States)

Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis

2016-10-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.

Computer-Aided Design of RNA Origami Structures.

Science.gov (United States)

Sparvath, Steffen L; Geary, Cody W; Andersen, Ebbe S

2017-01-01

RNA nanostructures can be used as scaffolds to organize, combine, and control molecular functionalities, with great potential for applications in nanomedicine and synthetic biology. The single-stranded RNA origami method allows RNA nanostructures to be folded as they are transcribed by the RNA polymerase. RNA origami structures provide a stable framework that can be decorated with functional RNA elements such as riboswitches, ribozymes, interaction sites, and aptamers for binding small molecules or protein targets. The rich library of RNA structural and functional elements combined with the possibility to attach proteins through aptamer-based binding creates virtually limitless possibilities for constructing advanced RNA-based nanodevices.In this chapter we provide a detailed protocol for the single-stranded RNA origami design method using a simple 2-helix tall structure as an example. The first step involves 3D modeling of a double-crossover between two RNA double helices, followed by decoration with tertiary motifs. The second step deals with the construction of a 2D blueprint describing the secondary structure and sequence constraints that serves as the input for computer programs. In the third step, computer programs are used to design RNA sequences that are compatible with the structure, and the resulting outputs are evaluated and converted into DNA sequences to order.

Advances in computational dynamics of particles, materials and structures a unified approach

CERN Document Server

Har, Jason

2012-01-01

Computational methods for the modeling and simulation of the dynamic response and behavior of particles, materials and structural systems have had a profound influence on science, engineering and technology. Complex science and engineering applications dealing with complicated structural geometries and materials that would be very difficult to treat using analytical methods have been successfully simulated using computational tools. With the incorporation of quantum, molecular and biological mechanics into new models, these methods are poised to play an even bigger role in the future. Ad

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

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

Science.gov (United States)

Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

2017-12-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

Directory of Open Access Journals (Sweden)

Rebecca F Alford

2017-12-01

Full Text Available Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

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...

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...

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...

cellPACK: a virtual mesoscope to model and visualize structural systems biology.

Science.gov (United States)

Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

2015-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

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 ...

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.  .

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.

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.

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

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

Computational design of proteins with novel structure and functions

International Nuclear Information System (INIS)

Yang Wei; Lai Lu-Hua

2016-01-01

Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence–structure–function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein–protein interactions. Challenges and future prospects of this field are also discussed. (topical review)

Structural biological composites: An overview

Science.gov (United States)

Meyers, Marc A.; Lin, Albert Y. M.; Seki, Yasuaki; Chen, Po-Yu; Kad, Bimal K.; Bodde, Sara

2006-07-01

Biological materials are complex composites that are hierarchically structured and multifunctional. Their mechanical properties are often outstanding, considering the weak constituents from which they are assembled. They are for the most part composed of brittle (often, mineral) and ductile (organic) components. These complex structures, which have risen from millions of years of evolution, are inspiring materials scientists in the design of novel materials. This paper discusses the overall design principles in biological structural composites and illustrates them for five examples; sea spicules, the abalone shell, the conch shell, the toucan and hornbill beaks, and the sheep crab exoskeleton.

Computational methods to study the structure and dynamics of biomolecules and biomolecular processes from bioinformatics to molecular quantum mechanics

CERN Document Server

2014-01-01

Since the second half of the 20th century machine computations have played a critical role in science and engineering. Computer-based techniques have become especially important in molecular biology, since they often represent the only viable way to gain insights into the behavior of a biological system as a whole. The complexity of biological systems, which usually needs to be analyzed on different time- and size-scales and with different levels of accuracy, requires the application of different approaches, ranging from comparative analysis of sequences and structural databases, to the analysis of networks of interdependence between cell components and processes, through coarse-grained modeling to atomically detailed simulations, and finally to molecular quantum mechanics. This book provides a comprehensive overview of modern computer-based techniques for computing the structure, properties and dynamics of biomolecules and biomolecular processes. The twenty-two chapters, written by scientists from all over t...

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.

[Classification of organisms and structuralism in biology].

Science.gov (United States)

Vasil'eva, L I

2001-01-01

Structuralism in biology is the oldest trend oriented to the search for natural "laws of forms" comparable with laws of growth of crystal, was revived at the end of 20th century on the basis of structuralist thought in socio-humanitarian sciences. The development of principal ideas of the linguistic structuralism in some aspects is similar to that of biological systematics, especially concerning the relationships between "system" and "evolution". However, apart from this general similarity, biological structuralism is strongly focused on familiar problems of the origin of diversity in nature. In their striving for the renovation of existing views, biological structuralists oppose the neo-darwinism emphasizing the existence of "law of forms", that are independent on heredity and genetic "determinism". The trend to develop so-called "rational taxonomy" is also characteristic of biological structuralism but this attempt failed being connected neither with Darwin's historicism nor with Plato's typology.

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.

Dynamic neuronal ensembles: Issues in representing structure change in object-oriented, biologically-based brain models

Energy Technology Data Exchange (ETDEWEB)

Vahie, S.; Zeigler, B.P.; Cho, H. [Univ. of Arizona, Tucson, AZ (United States)

1996-12-31

This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a neural circuit from a snail is presented and discussed. This paper provides an insight into the DNE paradigm using models developed and simulated in DEVS.

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...

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...

Neutron structural biology

International Nuclear Information System (INIS)

Niimura, Nobuo

1999-01-01

Neutron structural biology will be one of the most important fields in the life sciences which will interest human beings in the 21st century because neutrons can provide not only the position of hydrogen atoms in biological macromolecules but also the dynamic molecular motion of hydrogen atoms and water molecules. However, there are only a few examples experimentally determined at present because of the lack of neutron source intensity. Next generation neutron source scheduled in JAERI (Performance of which is 100 times better than that of JRR-3M) opens the life science of the 21st century. (author)

Perceptual organization in computer vision - A review and a proposal for a classificatory structure

Science.gov (United States)

Sarkar, Sudeep; Boyer, Kim L.

1993-01-01

The evolution of perceptual organization in biological vision, and its necessity in advanced computer vision systems, arises from the characteristic that perception, the extraction of meaning from sensory input, is an intelligent process. This is particularly so for high order organisms and, analogically, for more sophisticated computational models. The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. First, a brief history of perceptual organization research in both humans and computer vision is offered. Next, a classificatory structure in which to cast perceptual organization research to clarify both the nomenclature and the relationships among the many contributions is proposed. Thirdly, the perceptual organization work in computer vision in the context of this classificatory structure is reviewed. Finally, the array of computational techniques applied to perceptual organization problems in computer vision is surveyed.

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...

PSPP: a protein structure prediction pipeline for computing clusters.

Directory of Open Access Journals (Sweden)

Michael S Lee

2009-07-01

Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

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.

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

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

Science.gov (United States)

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

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.

Data structures, computer graphics, and pattern recognition

CERN Document Server

Klinger, A; Kunii, T L

1977-01-01

Data Structures, Computer Graphics, and Pattern Recognition focuses on the computer graphics and pattern recognition applications of data structures methodology.This book presents design related principles and research aspects of the computer graphics, system design, data management, and pattern recognition tasks. The topics include the data structure design, concise structuring of geometric data for computer aided design, and data structures for pattern recognition algorithms. The survey of data structures for computer graphics systems, application of relational data structures in computer gr

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.

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...

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....

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.

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.

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...

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.

Structural Biology Guides Antibiotic Discovery

Science.gov (United States)

Polyak, Steven

2014-01-01

Modern drug discovery programs require the contribution of researchers in a number of specialist areas. One of these areas is structural biology. Using X-ray crystallography, the molecular basis of how a drug binds to its biological target and exerts its mode of action can be defined. For example, a drug that binds into the active site of an…

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

Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport.

Science.gov (United States)

Howard, Rebecca J; Carnevale, Vincenzo; Delemotte, Lucie; Hellmich, Ute A; Rothberg, Brad S

2018-04-01

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain. Copyright © 2017 Elsevier B.V. All rights reserved.

Discrete computational structures

CERN Document Server

Korfhage, Robert R

1974-01-01

Discrete Computational Structures describes discrete mathematical concepts that are important to computing, covering necessary mathematical fundamentals, computer representation of sets, graph theory, storage minimization, and bandwidth. The book also explains conceptual framework (Gorn trees, searching, subroutines) and directed graphs (flowcharts, critical paths, information network). The text discusses algebra particularly as it applies to concentrates on semigroups, groups, lattices, propositional calculus, including a new tabular method of Boolean function minimization. The text emphasize

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.

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.

Structure problems in the analog computation

International Nuclear Information System (INIS)

Braffort, P.L.

1957-01-01

The recent mathematical development showed the importance of elementary structures (algebraic, topological, etc.) in abeyance under the great domains of classical analysis. Such structures in analog computation are put in evidence and possible development of applied mathematics are discussed. It also studied the topological structures of the standard representation of analog schemes such as additional triangles, integrators, phase inverters and functions generators. The analog method gives only the function of the variable: time, as results of its computations. But the course of computation, for systems including reactive circuits, introduces order structures which are called 'chronological'. Finally, it showed that the approximation methods of ordinary numerical and digital computation present the same structure as these analog computation. The structure analysis permits fruitful comparisons between the several domains of applied mathematics and suggests new important domains of application for analog method. (M.P.)

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...

Infinite possibilities: Computational structures technology

Science.gov (United States)

Beam, Sherilee F.

1994-12-01

Computational Fluid Dynamics (or CFD) methods are very familiar to the research community. Even the general public has had some exposure to CFD images, primarily through the news media. However, very little attention has been paid to CST--Computational Structures Technology. Yet, no important design can be completed without it. During the first half of this century, researchers only dreamed of designing and building structures on a computer. Today their dreams have become practical realities as computational methods are used in all phases of design, fabrication and testing of engineering systems. Increasingly complex structures can now be built in even shorter periods of time. Over the past four decades, computer technology has been developing, and early finite element methods have grown from small in-house programs to numerous commercial software programs. When coupled with advanced computing systems, they help engineers make dramatic leaps in designing and testing concepts. The goals of CST include: predicting how a structure will behave under actual operating conditions; designing and complementing other experiments conducted on a structure; investigating microstructural damage or chaotic, unpredictable behavior; helping material developers in improving material systems; and being a useful tool in design systems optimization and sensitivity techniques. Applying CST to a structure problem requires five steps: (1) observe the specific problem; (2) develop a computational model for numerical simulation; (3) develop and assemble software and hardware for running the codes; (4) post-process and interpret the results; and (5) use the model to analyze and design the actual structure. Researchers in both industry and academia continue to make significant contributions to advance this technology with improvements in software, collaborative computing environments and supercomputing systems. As these environments and systems evolve, computational structures technology will

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…

[Network structures in biological systems].

Science.gov (United States)

Oleskin, A V

2013-01-01

Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

Science.gov (United States)

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and

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. [...

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

Structured population models in biology and epidemiology

CERN Document Server

Ruan, Shigui

2008-01-01

This book consists of six chapters written by leading researchers in mathematical biology. These chapters present recent and important developments in the study of structured population models in biology and epidemiology. Topics include population models structured by age, size, and spatial position; size-structured models for metapopulations, macroparasitc diseases, and prion proliferation; models for transmission of microparasites between host populations living on non-coincident spatial domains; spatiotemporal patterns of disease spread; method of aggregation of variables in population dynamics; and biofilm models. It is suitable as a textbook for a mathematical biology course or a summer school at the advanced undergraduate and graduate level. It can also serve as a reference book for researchers looking for either interesting and specific problems to work on or useful techniques and discussions of some particular problems.

An agent-based computational model for tuberculosis spreading on age-structured populations

Science.gov (United States)

Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

2015-06-01

In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

Neutron structural biology

International Nuclear Information System (INIS)

Schoenborn, B.

1997-01-01

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). We investigated design concepts of neutron scattering capabilities for structural biology at spallation sources. This included the analysis of design parameters for protein crystallography as well as membrane diffraction instruments. These instruments are designed to be general user facilities and will be used by scientists from industry, universities, and other national laboratories

Communication on the structure of biological networks

Indian Academy of Sciences (India)

Introduction. Over the past few years, network science has drawn attention from a large number of ... The qualitative properties of biological networks cannot ... Here, we study the underlying undirected structure of empirical biological networks.

Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase

Directory of Open Access Journals (Sweden)

Katja Venko

Full Text Available The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helix–helix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target. Keywords: Membrane proteins, Bilitranslocase, 3D protein structure, Transmembrane region predictors, Helix–helix interactions

Structural identifiability of systems biology models: a critical comparison of methods.

Directory of Open Access Journals (Sweden)

Oana-Teodora Chis

Full Text Available Analysing the properties of a biological system through in silico experimentation requires a satisfactory mathematical representation of the system including accurate values of the model parameters. Fortunately, modern experimental techniques allow obtaining time-series data of appropriate quality which may then be used to estimate unknown parameters. However, in many cases, a subset of those parameters may not be uniquely estimated, independently of the experimental data available or the numerical techniques used for estimation. This lack of identifiability is related to the structure of the model, i.e. the system dynamics plus the observation function. Despite the interest in knowing a priori whether there is any chance of uniquely estimating all model unknown parameters, the structural identifiability analysis for general non-linear dynamic models is still an open question. There is no method amenable to every model, thus at some point we have to face the selection of one of the possibilities. This work presents a critical comparison of the currently available techniques. To this end, we perform the structural identifiability analysis of a collection of biological models. The results reveal that the generating series approach, in combination with identifiability tableaus, offers the most advantageous compromise among range of applicability, computational complexity and information provided.

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

Science.gov (United States)

Zheng, Haoping

2003-04-01

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

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.

Evidence of pervasive biologically functional secondary structures within the genomes of eukaryotic single-stranded DNA viruses.

Science.gov (United States)

Muhire, Brejnev Muhizi; Golden, Michael; Murrell, Ben; Lefeuvre, Pierre; Lett, Jean-Michel; Gray, Alistair; Poon, Art Y F; Ngandu, Nobubelo Kwanele; Semegni, Yves; Tanov, Emil Pavlov; Monjane, Adérito Luis; Harkins, Gordon William; Varsani, Arvind; Shepherd, Dionne Natalie; Martin, Darren Patrick

2014-02-01

Single-stranded DNA (ssDNA) viruses have genomes that are potentially capable of forming complex secondary structures through Watson-Crick base pairing between their constituent nucleotides. A few of the structural elements formed by such base pairings are, in fact, known to have important functions during the replication of many ssDNA viruses. Unknown, however, are (i) whether numerous additional ssDNA virus genomic structural elements predicted to exist by computational DNA folding methods actually exist and (ii) whether those structures that do exist have any biological relevance. We therefore computationally inferred lists of the most evolutionarily conserved structures within a diverse selection of animal- and plant-infecting ssDNA viruses drawn from the families Circoviridae, Anelloviridae, Parvoviridae, Nanoviridae, and Geminiviridae and analyzed these for evidence of natural selection favoring the maintenance of these structures. While we find evidence that is consistent with purifying selection being stronger at nucleotide sites that are predicted to be base paired than at sites predicted to be unpaired, we also find strong associations between sites that are predicted to pair with one another and site pairs that are apparently coevolving in a complementary fashion. Collectively, these results indicate that natural selection actively preserves much of the pervasive secondary structure that is evident within eukaryote-infecting ssDNA virus genomes and, therefore, that much of this structure is biologically functional. Lastly, we provide examples of various highly conserved but completely uncharacterized structural elements that likely have important functions within some of the ssDNA virus genomes analyzed here.

Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions.

Science.gov (United States)

Hucka, Michael; Bergmann, Frank T; Dräger, Andreas; Hoops, Stefan; Keating, Sarah M; Le Novère, Nicolas; Myers, Chris J; Olivier, Brett G; Sahle, Sven; Schaff, James C; Smith, Lucian P; Waltemath, Dagmar; Wilkinson, Darren J

2015-09-04

Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org.

Systems Biology Markup Language (SBML Level 2 Version 5: Structures and Facilities for Model Definitions

Directory of Open Access Journals (Sweden)

Hucka Michael

2015-06-01

Full Text Available Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.

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...

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.

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.

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

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

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

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...

[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.

Inference problems in structural biology

DEFF Research Database (Denmark)

Olsson, Simon

The structure and dynamics of biological molecules are essential for their function. Consequently, a wealth of experimental techniques have been developed to study these features. However, while experiments yield detailed information about geometrical features of molecules, this information is of...

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…

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.

Biological knowledge bases using Wikis: combining the flexibility of Wikis with the structure of databases.

Science.gov (United States)

Brohée, Sylvain; Barriot, Roland; Moreau, Yves

2010-09-01

In recent years, the number of knowledge bases developed using Wiki technology has exploded. Unfortunately, next to their numerous advantages, classical Wikis present a critical limitation: the invaluable knowledge they gather is represented as free text, which hinders their computational exploitation. This is in sharp contrast with the current practice for biological databases where the data is made available in a structured way. Here, we present WikiOpener an extension for the classical MediaWiki engine that augments Wiki pages by allowing on-the-fly querying and formatting resources external to the Wiki. Those resources may provide data extracted from databases or DAS tracks, or even results returned by local or remote bioinformatics analysis tools. This also implies that structured data can be edited via dedicated forms. Hence, this generic resource combines the structure of biological databases with the flexibility of collaborative Wikis. The source code and its documentation are freely available on the MediaWiki website: http://www.mediawiki.org/wiki/Extension:WikiOpener.

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.

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...

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.

Structural Biology for A-Level Students

Science.gov (United States)

Philip, Judith

2013-01-01

The relationship between the structure and function of proteins is an important area in biochemistry. Pupils studying A-level Biology are introduced to the four levels of protein structure (primary, secondary, tertiary and quaternary) and how these can be used to describe the progressive folding of a chain of amino acid residues to a final,…

Vestigial Biological Structures: A Classroom-Applicable Test of Creationist Hypotheses

Science.gov (United States)

Senter, Phil; Ambrocio, Zenis; Andrade, Julia B.; Foust, Katanya K.; Gaston, Jasmine E.; Lewis, Ryshonda P.; Liniewski, Rachel M.; Ragin, Bobby A.; Robinson, Khanna L.; Stanley, Shane G.

2015-01-01

Lists of vestigial biological structures in biology textbooks are so short that some young-Earth creationist authors claim that scientists have lost confidence in the existence of vestigial structures and can no longer identify any verifiable ones. We tested these hypotheses with a method that is easily adapted to biology classes. We used online…

Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes

Science.gov (United States)

Cleves, Ann E.; Jain, Ajay N.

2015-02-01

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.

Strategies for structuring interdisciplinary education in Systems Biology

DEFF Research Database (Denmark)

Cvijovic, Marija; Höfer, Thomas; Aćimović, Jure

2016-01-01

function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material...... and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active...... performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii...

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).

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.

Structure Biology of Membrane Bound Enzymes

Energy Technology Data Exchange (ETDEWEB)

Fu, Dax [Johns Hopkins Univ., Baltimore, MD (United States). School of Medicine. Dept. of Physiology

2016-11-30

The overall goal of the proposed research is to understand the membrane-associated active processes catalyzed by an alkane $\\square$-hydroxylase (AlkB) from eubacterium Pseudomonase oleovorans. AlkB performs oxygenation of unactivated hydrocarbons found in crude oils. The enzymatic reaction involves energy-demanding steps in the membrane with the uses of structurally unknown metal active sites featuring a diiron [FeFe] center. At present, a critical barrier to understanding the membrane-associated reaction mechanism is the lack of structural information. The structural biology efforts have been challenged by technical difficulties commonly encountered in crystallization and structural determination of membrane proteins. The specific aims of the current budget cycle are to crystalize AlkB and initiate X-ray analysis to set the stage for structural determination. The long-term goals of our structural biology efforts are to provide an atomic description of AlkB structure, and to uncover the mechanisms of selective modification of hydrocarbons. The structural information will help elucidating how the unactivated C-H bonds of saturated hydrocarbons are oxidized to initiate biodegradation and biotransformation processes. The knowledge gained will be fundamental to biotechnological applications to biofuel transformation of non-edible oil feedstock. Renewable biodiesel is a promising energy carry that can be used to reduce fossil fuel dependency. The proposed research capitalizes on prior BES-supported efforts on over-expression and purification of AlkB to explore the inner workings of a bioenergy-relevant membrane-bound enzyme.

Computational methods for three-dimensional microscopy reconstruction

CERN Document Server

Frank, Joachim

2014-01-01

Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different challenges. The editors of this volume, Gabor T. Herman and Joachim Frank, are experts in the respective methodologies and present research at the forefront of biological imaging and structural biology.   Computational Methods for Three-Dimensional Microscopy Reconstruction will serve as a useful resource for scholars interested in the development of computational methods for structural biology and cell biology, particularly in the area of 3D imaging and modeling.

West-Life, Tools for Integrative Structural Biology

CERN Multimedia

CERN. Geneva

2018-01-01

Structural biology is part of molecular biology focusing on determining structure of macromolecules inside living cells and cell membranes. As macromolecules determines most of the functions of cells the structural knowledge is very useful for further research in metabolism, physiology to application in pharmacology etc. As macromolecules are too small to be observed directly by light microscope, there are other methods used to determine the structure including nuclear magnetic resonance (NMR), X-Ray crystalography, cryo electron microscopy and others. Each method has it's advantages and disadvantages in the terms of availability, sample preparation, resolution. West-Life project has ambition to facilitate integrative approach using multiple techniques mentioned above. As there are already lot of software tools to process data produced by the techniques above, the challenge is to integrate them together in a way they can be used by experts in one technique but not experts in other techniques. One product ...

An Error Analysis of Structured Light Scanning of Biological Tissue

DEFF Research Database (Denmark)

Jensen, Sebastian Hoppe Nesgaard; Wilm, Jakob; Aanæs, Henrik

2017-01-01

This paper presents an error analysis and correction model for four structured light methods applied to three common types of biological tissue; skin, fat and muscle. Despite its many advantages, structured light is based on the assumption of direct reflection at the object surface only......, statistical linear model based on the scan geometry. As such, scans can be corrected without introducing any specially designed pattern strategy or hardware. We can effectively reduce the error in a structured light scanner applied to biological tissue by as much as factor of two or three........ This assumption is violated by most biological material e.g. human skin, which exhibits subsurface scattering. In this study, we find that in general, structured light scans of biological tissue deviate significantly from the ground truth. We show that a large portion of this error can be predicted with a simple...

From crystallography to structural biology, a century of discoveries

Directory of Open Access Journals (Sweden)

Montoya, Guillermo

2015-04-01

Full Text Available From crystallography, the technique mostly used to study the structure of matter, the field mutated into structural biology, has mutated in life sciences into structural biology, which has been developed as an essential and rather successful area of research to fully understand the workings of cellular pathways. The application of physical approaches to biological systems has been crucial to comprehend the structure and function of the biological components of living organisms. In this assay the author walks the reader through the last century, which has witnessed how this life sciences research area was born and moved towards larger assemblies in the core of crucial biological problems. The influence of research in physics, biochemistry and molecular biology has been key in the successes and large body of seminal results obtained by structural biologists. The author proposes that the future of this area implies the integration of its results at the cellular level apart of using more quantitative approaches to describe biological processes.La cristalografía, la técnica más ampliamente usada para estudiar la estructura de la materia, ha evolucionado en las ciencias de la vida hacia la biología estructural, una exitosa área de investigación encaminada a comprender el funcionamiento de los procesos celulares. La aplicación de aproximaciones físicas a sistemas biológicos es clave para entender la estructura y funcionamiento de los componentes de los organismos. En este artículo el autor ofrece al lector un paseo por la evolución de esta área de conocimiento durante el siglo XX, desde su nacimiento hasta el análisis de grandes complejos macromoleculares, protagonistas importantes en diversos procesos biológicos. La influencia de investigaciones en física, bioquímica y biología molecular ha sido clave para los numerosos éxitos alcanzados por biólogos estructurales. El autor sostiene que el futuro de esta disciplina pasa por la

New computing systems, future computing environment, and their implications on structural analysis and design

Science.gov (United States)

Noor, Ahmed K.; Housner, Jerrold M.

1993-01-01

Recent advances in computer technology that are likely to impact structural analysis and design of flight vehicles are reviewed. A brief summary is given of the advances in microelectronics, networking technologies, and in the user-interface hardware and software. The major features of new and projected computing systems, including high performance computers, parallel processing machines, and small systems, are described. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed. The impact of the advances in computer technology on structural analysis and the design of flight vehicles is described. A scenario for future computing paradigms is presented, and the near-term needs in the computational structures area are outlined.

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.

The normative structure of mathematization in systematic biology.

Science.gov (United States)

Sterner, Beckett; Lidgard, Scott

2014-06-01

We argue that the mathematization of science should be understood as a normative activity of advocating for a particular methodology with its own criteria for evaluating good research. As a case study, we examine the mathematization of taxonomic classification in systematic biology. We show how mathematization is a normative activity by contrasting its distinctive features in numerical taxonomy in the 1960s with an earlier reform advocated by Ernst Mayr starting in the 1940s. Both Mayr and the numerical taxonomists sought to formalize the work of classification, but Mayr introduced a qualitative formalism based on human judgment for determining the taxonomic rank of populations, while the numerical taxonomists introduced a quantitative formalism based on automated procedures for computing classifications. The key contrast between Mayr and the numerical taxonomists is how they conceptualized the temporal structure of the workflow of classification, specifically where they allowed meta-level discourse about difficulties in producing the classification. Copyright © 2014. Published by Elsevier Ltd.

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

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.

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.

Mathematics, structuralism and biology.

Science.gov (United States)

Saunders, P T

1988-01-01

A new approach is gaining ground in biology, one that has much in common with the structuralist tradition in other fields. It is very much in the spirit of an earlier view of biology and indeed of science in general. It is also, though this is not generally recognized, in the spirit of twentieth century physics. As in modern physics, however, it is not a question of ignoring all the progress that has been made within the former paradigm. On the contrary, the aim is to use it as a basis for setting out in a somewhat different direction. Complex phenomena do not generally lend themselves to reductionist analyses which seek explanation only in terms of detailed mechanisms, but a proper scientific discussion of structure must make full use of what we have already learned - by whatever means - about the processes that underly the phenomena we are trying to understand.

The JCSG high-throughput structural biology pipeline

International Nuclear Information System (INIS)

Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wooley, John; Wüthrich, Kurt; Wilson, Ian A.

2010-01-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years and has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe. The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications

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.)

Structure problems in the analog computation; Problemes de structure dans le calcul analogique

Energy Technology Data Exchange (ETDEWEB)

Braffort, P.L. [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1957-07-01

The recent mathematical development showed the importance of elementary structures (algebraic, topological, etc.) in abeyance under the great domains of classical analysis. Such structures in analog computation are put in evidence and possible development of applied mathematics are discussed. It also studied the topological structures of the standard representation of analog schemes such as additional triangles, integrators, phase inverters and functions generators. The analog method gives only the function of the variable: time, as results of its computations. But the course of computation, for systems including reactive circuits, introduces order structures which are called 'chronological'. Finally, it showed that the approximation methods of ordinary numerical and digital computation present the same structure as these analog computation. The structure analysis permits fruitful comparisons between the several domains of applied mathematics and suggests new important domains of application for analog method. (M.P.)

Structure problems in the analog computation; Problemes de structure dans le calcul analogique

Energy Technology Data Exchange (ETDEWEB)

Braffort, P L [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1957-07-01

The recent mathematical development showed the importance of elementary structures (algebraic, topological, etc.) in abeyance under the great domains of classical analysis. Such structures in analog computation are put in evidence and possible development of applied mathematics are discussed. It also studied the topological structures of the standard representation of analog schemes such as additional triangles, integrators, phase inverters and functions generators. The analog method gives only the function of the variable: time, as results of its computations. But the course of computation, for systems including reactive circuits, introduces order structures which are called 'chronological'. Finally, it showed that the approximation methods of ordinary numerical and digital computation present the same structure as these analog computation. The structure analysis permits fruitful comparisons between the several domains of applied mathematics and suggests new important domains of application for analog method. (M.P.)

Deciphering complement mechanisms: The contributions of structural biology.

NARCIS (Netherlands)

Arlaud, G.J.; Barlow, P.N.; Gaboriaud, C.; Gros, P.; Narayana, S.V.L.

2007-01-01

Since the resolution of the first three-dimensional structure of a complement component in 1980, considerable efforts have been put into the investigation of this system through structural biology techniques, resulting in about a hundred structures deposited in the Protein Data Bank by the beginning

The Protein Data Bank and Its Uses in Structural Biology Education

Directory of Open Access Journals (Sweden)

Judith Voet

2004-05-01

Full Text Available The Protein Data Bank (PDB is a repository for the structures of proteins and nucleic acids. Itcontains les of their 3-dimensional coordinates, information on how these structures were determinedand references to the journal articles describing them. The PDB was established in 1971 by HelenBerman (it s present director and has grown exponentially so that it now contains 25,000 data lesrepresenting X-ray crystallographic, NMR and other structure determinations. Database queryingand data miningtools and resources at the PDB make it possible to search, compare and infer orpredict the function of newly identied proteins. Computer graphics capabilities make it possible foranyone to easily visualize and study the structural data. The capability to present beautiful graphicrepresentations of the 3-dimesnional structures of proteins and nucleic acids has been a boon to theeducation community. Communicating an understanding of these structures and the chemical forcesdetermining them and their interactions is one of the major aims of biochemistry and molecular biologyeducation. The ability to teach these principles visually has made a great dierence in our abilityto excite our students and provide them with physical interpretations for some abstract concepts inbiochemistry and molecular biology. In this talk we will explore some of the ways that the education community uses the PDB.

Multiresolution Computation of Conformal Structures of Surfaces

Directory of Open Access Journals (Sweden)

Xianfeng Gu

2003-10-01

Full Text Available An efficient multiresolution method to compute global conformal structures of nonzero genus triangle meshes is introduced. The homology, cohomology groups of meshes are computed explicitly, then a basis of harmonic one forms and a basis of holomorphic one forms are constructed. A progressive mesh is generated to represent the original surface at different resolutions. The conformal structure is computed for the coarse level first, then used as the estimation for that of the finer level, by using conjugate gradient method it can be refined to the conformal structure of the finer level.

Computing optimal interfacial structure of modulated phases

OpenAIRE

Xu, Jie; Wang, Chu; Shi, An-Chang; Zhang, Pingwen

2016-01-01

We propose a general framework of computing interfacial structures between two modulated phases. Specifically we propose to use a computational box consisting of two half spaces, each occupied by a modulated phase with given position and orientation. The boundary conditions and basis functions are chosen to be commensurate with the bulk structures. It is observed that the ordered nature of modulated structures stabilizes the interface, which enables us to obtain optimal interfacial structures...

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.

Structural biology data archiving: where we are and what lies ahead.

Science.gov (United States)

Kleywegt, Gerard J; Velankar, Sameer; Patwardhan, Ardan

2018-05-10

For almost 50 years, structural biology has endeavoured to conserve and share its experimental data and their interpretations (usually, atomistic models) through global public archives such as the Protein Data Bank (PDB), Electron Microscopy Data Bank (EMDB) and Biologic Magnetic Resonance Bank (BMRB). These archives are treasure troves of freely accessible data that document our quest for molecular or atomic understanding of biological function and processes in health and disease. They have prepared the field to tackle new archiving challenges as more and more (combinations of) techniques are being utilised to elucidate structure at ever increasing length scales. Furthermore, the field has made substantial efforts to develop validation methods that help users to assess the reliability of structures and to identify the most appropriate data for their needs. In this Review, we present an overview of public data archives in structural biology and discuss the importance of validation for users and producers of structural data. Finally, we sketch our efforts to integrate structural data with bioimaging data and with other sources of biological data. This will make relevant structural information available and more easily discoverable for a wide range of scientists. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Biology Student Teachers' Cognitive Structure about "Living Thing"

Science.gov (United States)

Kurt, Hakan

2013-01-01

The current study aims to determine biology student teachers' cognitive structure on the concept of "living thing" through revealing their conceptual framework. Qualitative research method was applied in this study. The data were collected from 44 biology student teachers. A free word association test was used as a data collection…

Structural Biology: Practical NMR Applications

CERN Document Server

Teng, Quincy

2005-01-01

This textbook begins with an overview of NMR development and applications in biological systems. It describes recent developments in instrument hardware and methodology. Chapters highlight the scope and limitation of NMR methods. While detailed math and quantum mechanics dealing with NMR theory have been addressed in several well-known NMR volumes, chapter two of this volume illustrates the fundamental principles and concepts of NMR spectroscopy in a more descriptive manner. Topics such as instrument setup, data acquisition, and data processing using a variety of offline software are discussed. Chapters further discuss several routine stategies for preparing samples, especially for macromolecules and complexes. The target market for such a volume includes researchers in the field of biochemistry, chemistry, structural biology and biophysics.

Dissipative structures and biological rhythms

Science.gov (United States)

Goldbeter, Albert

2017-10-01

Sustained oscillations abound in biological systems. They occur at all levels of biological organization over a wide range of periods, from a fraction of a second to years, and with a variety of underlying mechanisms. They control major physiological functions, and their dysfunction is associated with a variety of physiological disorders. The goal of this review is (i) to give an overview of the main rhythms observed at the cellular and supracellular levels, (ii) to briefly describe how the study of biological rhythms unfolded in the course of time, in parallel with studies on chemical oscillations, (iii) to present the major roles of biological rhythms in the control of physiological functions, and (iv) the pathologies associated with the alteration, disappearance, or spurious occurrence of biological rhythms. Two tables present the main examples of cellular and supracellular rhythms ordered according to their period, and their role in physiology and pathophysiology. Among the rhythms discussed are neural and cardiac rhythms, metabolic oscillations such as those occurring in glycolysis in yeast, intracellular Ca++ oscillations, cyclic AMP oscillations in Dictyostelium amoebae, the segmentation clock that controls somitogenesis, pulsatile hormone secretion, circadian rhythms which occur in all eukaryotes and some bacteria with a period close to 24 h, the oscillatory dynamics of the enzymatic network driving the cell cycle, and oscillations in transcription factors such as NF-ΚB and tumor suppressors such as p53. Ilya Prigogine's concept of dissipative structures applies to temporal oscillations and allows us to unify within a common framework the various rhythms observed at different levels of biological organization, regardless of their period and underlying mechanism.

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.

Hierarchical structure of biological systems: a bioengineering approach.

Science.gov (United States)

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

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.

Structural biology facilities at Brookhaven National Laboratory`s high flux beam reactor

Energy Technology Data Exchange (ETDEWEB)

Korszun, Z.R.; Saxena, A.M.; Schneider, D.K. [Brookhaven National Laboratory, Upton, NY (United States)

1994-12-31

The techniques for determining the structure of biological molecules and larger biological assemblies depend on the extent of order in the particular system. At the High Flux Beam Reactor at the Brookhaven National Laboratory, the Biology Department operates three beam lines dedicated to biological structure studies. These beam lines span the resolution range from approximately 700{Angstrom} to approximately 1.5{Angstrom} and are designed to perform structural studies on a wide range of biological systems. Beam line H3A is dedicated to single crystal diffraction studies of macromolecules, while beam line H3B is designed to study diffraction from partially ordered systems such as biological membranes. Beam line H9B is located on the cold source and is designed for small angle scattering experiments on oligomeric biological systems.

Algorithms and file structures for computational geometry

International Nuclear Information System (INIS)

Hinrichs, K.; Nievergelt, J.

1983-01-01

Algorithms for solving geometric problems and file structures for storing large amounts of geometric data are of increasing importance in computer graphics and computer-aided design. As examples of recent progress in computational geometry, we explain plane-sweep algorithms, which solve various topological and geometric problems efficiently; and we present the grid file, an adaptable, symmetric multi-key file structure that provides efficient access to multi-dimensional data along any space dimension. (orig.)

Structure and function in biology

International Nuclear Information System (INIS)

Hirs, C.H.W.

1976-01-01

A summary is given of the history of the developments of structural chemistry in biology beginning with the work of the bacteriologist Ehrlich leading to a comprehensive examination of the influence of size and configuration on the interaction between specific antibodies and side-chain determinants. Recent developments include the recognition of a higher order of specificity in the interaction of proteins with one another

Mathematical structures for computer graphics

CERN Document Server

Janke, Steven J

2014-01-01

A comprehensive exploration of the mathematics behind the modeling and rendering of computer graphics scenes Mathematical Structures for Computer Graphics presents an accessible and intuitive approach to the mathematical ideas and techniques necessary for two- and three-dimensional computer graphics. Focusing on the significant mathematical results, the book establishes key algorithms used to build complex graphics scenes. Written for readers with various levels of mathematical background, the book develops a solid foundation for graphics techniques and fills in relevant grap

Structural biology by NMR: structure, dynamics, and interactions.

Directory of Open Access Journals (Sweden)

Phineus R L Markwick

2008-09-01

Full Text Available The function of bio-macromolecules is determined by both their 3D structure and conformational dynamics. These molecules are inherently flexible systems displaying a broad range of dynamics on time-scales from picoseconds to seconds. Nuclear Magnetic Resonance (NMR spectroscopy has emerged as the method of choice for studying both protein structure and dynamics in solution. Typically, NMR experiments are sensitive both to structural features and to dynamics, and hence the measured data contain information on both. Despite major progress in both experimental approaches and computational methods, obtaining a consistent view of structure and dynamics from experimental NMR data remains a challenge. Molecular dynamics simulations have emerged as an indispensable tool in the analysis of NMR data.

Data publication with the structural biology data grid supports live analysis

NARCIS (Netherlands)

Meyer, Peter A.; Socias, Stephanie; Key, Jason; Ransey, Elizabeth; Tjon, Emily C.; Buschiazzo, Alejandro; Lei, Ming; Botka, Chris; Withrow, James; Neau, David; Rajashankar, Kanagalaghatta; Anderson, Karen S.; Baxter, Richard H.; Blacklow, Stephen C.; Boggon, Titus J.; Bonvin, Alexandre M J J|info:eu-repo/dai/nl/113691238; Borek, Dominika; Brett, Tom J.; Caflisch, Amedeo; Chang, Chung I.; Chazin, Walter J.; Corbett, Kevin D.; Cosgrove, Michael S.; Crosson, Sean; Dhe-Paganon, Sirano; Di Cera, Enrico; Drennan, Catherine L.; Eck, Michael J.; Eichman, Brandt F.; Fan, Qing R.; Ferré-D'Amaré, Adrian R.; Fromme, J. Christopher; Garcia, K. Christopher; Gaudet, Rachelle; Gong, Peng; Harrison, Stephen C.; Heldwein, Ekaterina E.; Jia, Zongchao; Keenan, Robert J.; Kruse, Andrew C.; Kvansakul, Marc; McLellan, Jason S.; Modis, Yorgo; Nam, Yunsun; Otwinowski, Zbyszek; Pai, Emil F.; Pereira, Pedro José Barbosa; Petosa, Carlo; Raman, C. S.; Rapoport, Tom A.; Roll-Mecak, Antonina; Rosen, Michael K.; Rudenko, Gabby; Schlessinger, Joseph; Schwartz, Thomas U.; Shamoo, Yousif; Sondermann, Holger; Tao, Yizhi J.; Tolia, Niraj H.; Tsodikov, Oleg V.; Westover, Kenneth D.; Wu, Hao; Foster, Ian; Fraser, James S.; Maia, Filipe R N C; Gonen, Tamir; Kirchhausen, Tom; Diederichs, Kay; Crosas, Mercé; Sliz, Piotr

2016-01-01

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology

Aspartate and glutamate mimetic structures in biologically active compounds.

Science.gov (United States)

Stefanic, Peter; Dolenc, Marija Sollner

2004-04-01

Glutamate and aspartate are frequently recognized as key structural elements for the biological activity of natural peptides and synthetic compounds. The acidic side-chain functionality of both the amino acids provides the basis for the ionic interaction and subsequent molecular recognition by specific receptor sites that results in the regulation of physiological or pathophysiological processes in the organism. In the development of new biologically active compounds that possess the ability to modulate these processes, compounds offering the same type of interactions are being designed. Thus, using a peptidomimetic design approach, glutamate and aspartate mimetics are incorporated into the structure of final biologically active compounds. This review covers different bioisosteric replacements of carboxylic acid alone, as well as mimetics of the whole amino acid structure. Amino acid analogs presented include those with different distances between anionic moieties, and analogs with additional functional groups that result in conformational restriction or alternative interaction sites. The article also provides an overview of different cyclic structures, including various cycloalkane, bicyclic and heterocyclic analogs, that lead to conformational restriction. Higher di- and tripeptide mimetics in which carboxylic acid functionality is incorporated into larger molecules are also reviewed. In addition to the mimetic structures presented, emphasis in this article is placed on their steric and electronic properties. These mimetics constitute a useful pool of fragments in the design of new biologically active compounds, particularly in the field of RGD mimetics and excitatory amino acid agonists and antagonists.

Biological Membrane Ion Channels Dynamics, Structure, and Applications

CERN Document Server

Chung, Shin-Ho; Krishnamurthy, Vikram

2007-01-01

Ion channels are biological nanotubes that are formed by membrane proteins. Because ion channels regulate all electrical activities in living cells, understanding their mechanisms at a molecular level is a fundamental problem in biology. This book deals with recent breakthroughs in ion-channel research that have been brought about by the combined effort of experimental biophysicists and computational physicists, who together are beginning to unravel the story of these exquisitely designed biomolecules. With chapters by leading experts, the book is aimed at researchers in nanodevices and biosensors, as well as advanced undergraduate and graduate students in biology and the physical sciences. Key Features Presents the latest information on the molecular mechanisms of ion permeation through membrane ion channels Uses schematic diagrams to illustrate important concepts in biophysics Written by leading researchers in the area of ion channel investigations

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.

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...

Databases, Repositories, and Other Data Resources in Structural Biology.

Science.gov (United States)

Zheng, Heping; Porebski, Przemyslaw J; Grabowski, Marek; Cooper, David R; Minor, Wladek

2017-01-01

Structural biology, like many other areas of modern science, produces an enormous amount of primary, derived, and "meta" data with a high demand on data storage and manipulations. Primary data come from various steps of sample preparation, diffraction experiments, and functional studies. These data are not only used to obtain tangible results, like macromolecular structural models, but also to enrich and guide our analysis and interpretation of various biomedical problems. Herein we define several categories of data resources, (a) Archives, (b) Repositories, (c) Databases, and (d) Advanced Information Systems, that can accommodate primary, derived, or reference data. Data resources may be used either as web portals or internally by structural biology software. To be useful, each resource must be maintained, curated, as well as integrated with other resources. Ideally, the system of interconnected resources should evolve toward comprehensive "hubs", or Advanced Information Systems. Such systems, encompassing the PDB and UniProt, are indispensable not only for structural biology, but for many related fields of science. The categories of data resources described herein are applicable well beyond our usual scientific endeavors.

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.

Recent progress in structural biology: lessons from our research history.

Science.gov (United States)

Nitta, Ryo; Imasaki, Tsuyoshi; Nitta, Eriko

2018-05-16

The recent 'resolution revolution' in structural analyses of cryo-electron microscopy (cryo-EM) has drastically changed the research strategy for structural biology. In addition to X-ray crystallography and nuclear magnetic resonance spectroscopy, cryo-EM has achieved the structural analysis of biological molecules at near-atomic resolution, resulting in the Nobel Prize in Chemistry 2017. The effect of this revolution has spread within the biology and medical science fields affecting everything from basic research to pharmaceutical development by visualizing atomic structure. As we have used cryo-EM as well as X-ray crystallography since 2000 to elucidate the molecular mechanisms of the fundamental phenomena in the cell, here we review our research history and summarize our findings. In the first half of the review, we describe the structural mechanisms of microtubule-based motility of molecular motor kinesin by using a joint cryo-EM and X-ray crystallography method. In the latter half, we summarize our structural studies on transcriptional regulation by X-ray crystallography of in vitro reconstitution of a multi-protein complex.

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.

Computational predictions of zinc oxide hollow structures

Science.gov (United States)

Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

2018-03-01

Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

Development of a Prototype System for Archiving Integrative/Hybrid Structure Models of Biological Macromolecules.

Science.gov (United States)

Vallat, Brinda; Webb, Benjamin; Westbrook, John D; Sali, Andrej; Berman, Helen M

2018-04-09

Essential processes in biology are carried out by large macromolecular assemblies, whose structures are often difficult to determine by traditional methods. Increasingly, researchers combine measured data and computed information from several complementary methods to obtain "hybrid" or "integrative" structural models of macromolecules and their assemblies. These integrative/hybrid (I/H) models are not archived in the PDB because of the absence of standard data representations and processing mechanisms. Here we present the development of data standards and a prototype system for archiving I/H models. The data standards provide the definitions required for representing I/H models that span multiple spatiotemporal scales and conformational states, as well as spatial restraints derived from different experimental techniques. Based on these data definitions, we have built a prototype system called PDB-Dev, which provides the infrastructure necessary to archive I/H structural models. PDB-Dev is now accepting structures and is open to the community for new submissions. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Parallel algorithms and archtectures for computational structural mechanics

Science.gov (United States)

Patrick, Merrell; Ma, Shing; Mahajan, Umesh

1989-01-01

The determination of the fundamental (lowest) natural vibration frequencies and associated mode shapes is a key step used to uncover and correct potential failures or problem areas in most complex structures. However, the computation time taken by finite element codes to evaluate these natural frequencies is significant, often the most computationally intensive part of structural analysis calculations. There is continuing need to reduce this computation time. This study addresses this need by developing methods for parallel computation.

Quantification of the impact of PSI:Biology according to the annotations of the determined structures.

Science.gov (United States)

DePietro, Paul J; Julfayev, Elchin S; McLaughlin, William A

2013-10-21

Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure. One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure. We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i

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…

Basic design of parallel computational program for probabilistic structural analysis

International Nuclear Information System (INIS)

Kaji, Yoshiyuki; Arai, Taketoshi; Gu, Wenwei; Nakamura, Hitoshi

1999-06-01

In our laboratory, for 'development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory' (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)

Basic design of parallel computational program for probabilistic structural analysis

Energy Technology Data Exchange (ETDEWEB)

Kaji, Yoshiyuki; Arai, Taketoshi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Gu, Wenwei; Nakamura, Hitoshi

1999-06-01

In our laboratory, for `development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory` (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)

Proceedings of the 182nd basic science seminar (The workshop on neutron structural biology ) 'New frontiers of structural biology advanced by solution scattering'

International Nuclear Information System (INIS)

Fujiwara, Satoru

2001-03-01

182nd advanced science seminar (the workshop on neutron structural biology) was held in February 9-10, 2000 at Tokai. Thirty-six participants from universities, research institutes, and private companies took part in the workshop, and total of 24 lectures were given. This proceedings collects abstracts, the figures and tables, which the speakers used in their lectures. The proceedings contains two reviews from the point of view of x-ray and neutron scatterings, and six subjects (21 papers) including neutron and x-ray scattering in the era of structure genomics, structural changes detected with solution scattering, a new way in structural biology opened by neutron crystallography and neutron scattering, x-ray sources and detectors, simulation and solution scattering, and neutron sources and detectors. (Kazumata, Y.)

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,…

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

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…

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.

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.

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

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.

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...

Computational methods for structural load and resistance modeling

Science.gov (United States)

Thacker, B. H.; Millwater, H. R.; Harren, S. V.

1991-01-01

An automated capability for computing structural reliability considering uncertainties in both load and resistance variables is presented. The computations are carried out using an automated Advanced Mean Value iteration algorithm (AMV +) with performance functions involving load and resistance variables obtained by both explicit and implicit methods. A complete description of the procedures used is given as well as several illustrative examples, verified by Monte Carlo Analysis. In particular, the computational methods described in the paper are shown to be quite accurate and efficient for a material nonlinear structure considering material damage as a function of several primitive random variables. The results show clearly the effectiveness of the algorithms for computing the reliability of large-scale structural systems with a maximum number of resolutions.

RNA secondary structure prediction using soft computing.

Science.gov (United States)

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

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

On the Concept "Microscope": Biology Student Teachers' Cognitive Structure

Science.gov (United States)

Kurt, Hakan; Ekici, Gulay; Aktas, Murat; Aksu, Ozlem

2013-01-01

The purpose of the current study is to determine biology student teachers' cognitive structures on the concept of microscope. Qualitative research methodology has been applied in the study. The data were collected from biology student teachers. Free word association test and drawing-writing test were used to collect data. The data collected were…

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.

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.

The Effect of Knowledge Linking Levels in Biology Lessons upon Students' Knowledge Structure

Science.gov (United States)

Wadouh, Julia; Liu, Ning; Sandmann, Angela; Neuhaus, Birgit J.

2014-01-01

Knowledge structure is an important aspect for defining students' competency in biology learning, but how knowledge structure is influenced by the teaching process in naturalistic biology classroom settings has scarcely been empirically investigated. In this study, 49 biology lessons in the teaching unit "blood and circulatory system" in…

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.)

Student Computer Use: Its Organizational Structure and Institutional Support.

Science.gov (United States)

Juska, Arunas; Paris, Arthur E.

1993-01-01

Examines the structure of undergraduate computing at a large private university, including patterns of use, impact of computer ownership and gender, and the bureaucratic structure in which usage is embedded. The profile of computer use uncovered in a survey is compared with reports offered by the institution and the trade press. (10 references)…

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.

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.

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...

Cyclobutane-Containing Alkaloids: Origin, Synthesis, and Biological Activities

OpenAIRE

Sergeiko, Anastasia; Poroikov, Vladimir V; Hanuš, Lumir O; Dembitsky, Valery M

2008-01-01

Present review describes research on novel natural cyclobutane-containing alkaloids isolated from terrestrial and marine species. More than 60 biological active compounds have been confirmed to have antimicrobial, antibacterial, antitumor, and other activities. The structures, synthesis, origins, and biological activities of a selection of cyclobutane-containing alkaloids are reviewed. With the computer program PASS some additional biological activities are also predicted, which point toward ...

Computational tools for experimental determination and theoretical prediction of protein structure

Energy Technology Data Exchange (ETDEWEB)

O`Donoghue, S.; Rost, B.

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. The authors intend to review the state of the art in the experimental determination of protein 3D structure (focus on nuclear magnetic resonance), and in the theoretical prediction of protein function and of protein structure in 1D, 2D and 3D from sequence. All the atomic resolution structures determined so far have been derived from either X-ray crystallography (the majority so far) or Nuclear Magnetic Resonance (NMR) Spectroscopy (becoming increasingly more important). The authors briefly describe the physical methods behind both of these techniques; the major computational methods involved will be covered in some detail. They highlight parallels and differences between the methods, and also the current limitations. Special emphasis will be given to techniques which have application to ab initio structure prediction. Large scale sequencing techniques increase the gap between the number of known proteins sequences and that of known protein structures. They describe the scope and principles of methods that contribute successfully to closing that gap. Emphasis will be given on the specification of adequate testing procedures to validate such methods.

Structured brain computing and its learning

International Nuclear Information System (INIS)

Ae, Tadashi; Araki, Hiroyuki; Sakai, Keiichi

1999-01-01

We have proposed a two-level architecture for brain computing, where two levels are introduced for processing of meta-symbol. At level 1 a conventional pattern recognition is performed, where neural computation is included, and its output gives the meta-symbol which is a symbol enlarged from a symbol to a kind of pattern. At Level 2 an algorithm acquisition is made by using a machine for abstract states. We are also developing the VLSI chips at each level for SBC (Structured Brain Computer) Ver.1.0

Composite Structural Motifs of Binding Sites for Delineating Biological Functions of Proteins

Science.gov (United States)

Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures. PMID:22347478

Proceedings of the 182nd basic science seminar (The workshop on neutron structural biology ) 'New frontiers of structural biology advanced by solution scattering'

Energy Technology Data Exchange (ETDEWEB)

Fujiwara, Satoru (ed.) [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

2001-03-01

182nd advanced science seminar (the workshop on neutron structural biology) was held in February 9-10, 2000 at Tokai. Thirty-six participants from universities, research institutes, and private companies took part in the workshop, and total of 24 lectures were given. This proceedings collects abstracts, the figures and tables, which the speakers used in their lectures. The proceedings contains two reviews from the point of view of x-ray and neutron scatterings, and six subjects (21 papers) including neutron and x-ray scattering in the era of structure genomics, structural changes detected with solution scattering, a new way in structural biology opened by neutron crystallography and neutron scattering, x-ray sources and detectors, simulation and solution scattering, and neutron sources and detectors. (Kazumata, Y.)

Node fingerprinting: an efficient heuristic for aligning biological networks.

Science.gov (United States)

Radu, Alex; Charleston, Michael

2014-10-01

With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

Digital computer structure and design

CERN Document Server

Townsend, R

2014-01-01

Digital Computer Structure and Design, Second Edition discusses switching theory, counters, sequential circuits, number representation, and arithmetic functions The book also describes computer memories, the processor, data flow system of the processor, the processor control system, and the input-output system. Switching theory, which is purely a mathematical concept, centers on the properties of interconnected networks of ""gates."" The theory deals with binary functions of 1 and 0 which can change instantaneously from one to the other without intermediate values. The binary number system is

Hydrological structure and biological productivity of the tropical Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Muraleedharan, U.D.; Muraleedharan, P.M.

Hydrological structure analyses of regions in the tropical Atlantic Ocean have consistently revealed the existence of a typical tropical structure characterized by a nitrate-depleted mixed layer above the thermocline. The important biological...

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.

Biological activity of antitumoural MGBG: the structural variable.

Science.gov (United States)

Marques, M P M; Gil, F P S C; Calheiros, R; Battaglia, V; Brunati, A M; Agostinelli, E; Toninello, A

2008-05-01

The present study aims at determining the structure-activity relationships (SAR's) ruling the biological function of MGBG (methylglyoxal bis(guanylhydrazone)), a competitive inhibitor of S-adenosyl-L-methionine decarboxylase displaying anticancer activity, involved in the biosynthesis of the naturally occurring polyamines spermidine and spermine. In order to properly understand its biochemical activity, MGBG's structural preferences at physiological conditions were ascertained, by quantum mechanical (DFT) calculations.

STRUCTURES AND BIOLOGICAL ACTIVITY OF CUPROPHYLLINS

Directory of Open Access Journals (Sweden)

Martynov A.V.

2017-06-01

Full Text Available Chlorophylls (a, b are the porphyrin compounds and most common chemical in the plant’s world. In fact, these compounds are an obligatory intermediate product both in energy metabolism and in plant catabolism. At the same time, currently there are few pharmaceutical preparations on the pharmaceutical market based on chlorophylls. Dyes based on hydrolyzed chlorophyll are successfully used in the food industry. Commercial chlorophylline is a copper complex of hydrolyzed chlorophylls. As shown earlier in TLC, the chlorophyllin mixture contains a large number of different compounds. It is like water-soluble saponified derivatives in the form of sodium-magnesium complexes, and similar structures in the form of a complex with copper. The latter are more brightly colored, soluble in water and widely used as coloring agents in cooking. In this case, if the initial chlorophyll was not found to have a pronounced biological activity, the substituted derivatives in the form of copper complexes possessed a number of new unique biological properties. Non-hydrolyzed hydrophobic cuprophylline obtained from eucalyptus leaves possessed high antimicrobial activity to most strains of staphylococci, inclusion resistant to antimicrobials and multiresistant strains. This drug is called Chlorophyllipt, it is allowed to be used as a medicinal product and is one of the oldest antibacterial drugs from plants on the market. It is marketed as ethanoic and oily solutions for topical use, and as an alcohol solution for intravenous injections. Its main purpose is the fight against staphylococcal infections. Recently, found that the oral administration of chlorophyllipt activates cellular immunity and indirectly exhibits antiviral activity. Another compound of cuprophyllin is water-soluble chlorophyllin. Some authors show the variability of the structure and biological activity of cuprophyllins. Different derivatives of chlorophyll have different biological activity

Structural Interfaces and Attachments in Biology

CERN Document Server

Birman, Victor; Genin, Guy

2013-01-01

Attachment of dissimilar materials in engineering and surgical practice is a perennial challenge. Bimaterial attachment sites are common locations for injury, repeated injury, and mechanical failure. Nature presents several highly effective solutions to the challenge of bimaterial attachment that differ from those found in engineering practice. Structural Interfaces and Attachments in Biology describes the attachment of dissimilar materials from multiple perspectives. The text will simultaneously elucidate natural bimaterial attachments and outline engineering principles underlying successful attachments to the communities of tissue engineers and surgeons. Included an in-depth analysis of the biology of attachments in the body and mechanisms by which robust attachments are formed, a review of current concepts of attaching dissimilar materials in surgical practice and a discussion of bioengineering approaches that are currently being developed. This book also: Provides the first comprehensive treatment of phys...

Using the Cambridge structure database of organic and organometalic compounds in structure biology

Czech Academy of Sciences Publication Activity Database

Hašek, Jindřich

2010-01-01

Roč. 17, 1a (2010), b24-b26 ISSN 1211-5894. [Discussions in Structural Molecular Biology /8./. Nové Hrady, 18.03.2010-20.03.2010] R&D Projects: GA AV ČR IAA500500701; GA ČR GA305/07/1073 Institutional research plan: CEZ:AV0Z40500505 Keywords : organic chemistry * Cambridge Structure Data base * molecular structure Subject RIV: CD - Macromolecular Chemistry http://xray.cz/ms/bul2010-1a/friday2.pdf

Neutron scattering for the analysis of biological structures. Brookhaven symposia in biology. Number 27

Energy Technology Data Exchange (ETDEWEB)

Schoenborn, B P [ed.

1976-01-01

Sessions were included on neutron scattering and biological structure analysis, protein crystallography, neutron scattering from oriented systems, solution scattering, preparation of deuterated specimens, inelastic scattering, data analysis, experimental techniques, and instrumentation. Separate entries were made for the individual papers.

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

High-performance computing in accelerating structure design and analysis

International Nuclear Information System (INIS)

Li Zenghai; Folwell, Nathan; Ge Lixin; Guetz, Adam; Ivanov, Valentin; Kowalski, Marc; Lee, Lie-Quan; Ng, Cho-Kuen; Schussman, Greg; Stingelin, Lukas; Uplenchwar, Ravindra; Wolf, Michael; Xiao, Liling; Ko, Kwok

2006-01-01

Future high-energy accelerators such as the Next Linear Collider (NLC) will accelerate multi-bunch beams of high current and low emittance to obtain high luminosity, which put stringent requirements on the accelerating structures for efficiency and beam stability. While numerical modeling has been quite standard in accelerator R and D, designing the NLC accelerating structure required a new simulation capability because of the geometric complexity and level of accuracy involved. Under the US DOE Advanced Computing initiatives (first the Grand Challenge and now SciDAC), SLAC has developed a suite of electromagnetic codes based on unstructured grids and utilizing high-performance computing to provide an advanced tool for modeling structures at accuracies and scales previously not possible. This paper will discuss the code development and computational science research (e.g. domain decomposition, scalable eigensolvers, adaptive mesh refinement) that have enabled the large-scale simulations needed for meeting the computational challenges posed by the NLC as well as projects such as the PEP-II and RIA. Numerical results will be presented to show how high-performance computing has made a qualitative improvement in accelerator structure modeling for these accelerators, either at the component level (single cell optimization), or on the scale of an entire structure (beam heating and long-range wakefields)

Building bridges between cellular and molecular structural biology.

Science.gov (United States)

Patwardhan, Ardan; Brandt, Robert; Butcher, Sarah J; Collinson, Lucy; Gault, David; Grünewald, Kay; Hecksel, Corey; Huiskonen, Juha T; Iudin, Andrii; Jones, Martin L; Korir, Paul K; Koster, Abraham J; Lagerstedt, Ingvar; Lawson, Catherine L; Mastronarde, David; McCormick, Matthew; Parkinson, Helen; Rosenthal, Peter B; Saalfeld, Stephan; Saibil, Helen R; Sarntivijai, Sirarat; Solanes Valero, Irene; Subramaniam, Sriram; Swedlow, Jason R; Tudose, Ilinca; Winn, Martyn; Kleywegt, Gerard J

2017-07-06

The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.

Capacitive Structures for Gas and Biological Sensing

KAUST Repository

Sapsanis, Christos

2015-04-01

The semiconductor industry was benefited by the advances in technology in the last decades. This fact has an impact on the sensors field, where the simple transducer was evolved into smart miniaturized multi-functional microsystems. However, commercially available gas and biological sensors are mostly bulky, expensive, and power-hungry, which act as obstacles to mass use. The aim of this work is gas and biological sensing using capacitive structures. Capacitive sensors were selected due to its design simplicity, low fabrication cost, and no DC power consumption. In the first part, the dominant structure among interdigitated electrodes (IDEs), fractal curves (Peano and Hilbert) and Archimedean spiral was investigated from capacitance density perspective. The investigation consists of geometrical formula calculations, COMSOL Multiphysics simulations and cleanroom fabrication of the capacitors on a silicon substrate. Moreover, low-cost fabrication on flexible plastic PET substrate was conducted outside cleanroom with rapid prototyping using a maskless laser etching. The second part contains the humidity, Volatile Organic compounds (VOCs) and Ammonia sensing of polymers, Polyimide and Nafion, and metal-organic framework (MOF), Cu(bdc)2.xH2O using IDEs and tested in an automated gas setup for experiment control and data extraction. The last part includes the biological sensing of C - reactive protein (CRP) quantification, which is considered as a biomarker of being prone to cardiac diseases and Bovine serum albumin (BSA) protein quantification, which is used as a reference for quantifying unknown proteins.

Tensegrity I. Cell structure and hierarchical systems biology

Science.gov (United States)

Ingber, Donald E.

2003-01-01

In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

Computing the Reverse Eccentric Connectivity Index for Certain Family of Nanocone and Fullerene Structures

Directory of Open Access Journals (Sweden)

Wei Gao

2016-01-01

Full Text Available A large number of previous works reveal that there exist strong connections between the chemical characteristics of chemical compounds and drugs (e.g., melting point and boiling point and their topological structures. Chemical indices introduced on these molecular topological structures can help chemists and material and medical scientists to grasp its chemical reactivity, biological activity, and physical features better. Hence, the study of the topological indices on the material structure can make up the defect of experiments and provide the theoretical evidence in material engineering. In this paper, we determine the reverse eccentric connectivity index of one family of pentagonal carbon nanocones PCN5[n] and three infinite families of fullerenes C12n+2,  C12n+4, and C18n+10 based on graph analysis and computation derivation, and these results can offer the theoretical basis for material properties.

Generation of structurally novel short carotenoids and study of their biological activity.

Science.gov (United States)

Kim, Se H; Kim, Moon S; Lee, Bun Y; Lee, Pyung C

2016-02-23

Recent research interest in phytochemicals has consistently driven the efforts in the metabolic engineering field toward microbial production of various carotenoids. In spite of systematic studies, the possibility of using C30 carotenoids as biologically functional compounds has not been explored thus far. Here, we generated 13 novel structures of C30 carotenoids and one C35 carotenoid, including acyclic, monocyclic, and bicyclic structures, through directed evolution and combinatorial biosynthesis, in Escherichia coli. Measurement of radical scavenging activity of various C30 carotenoid structures revealed that acyclic C30 carotenoids showed higher radical scavenging activity than did DL-α-tocopherol. We could assume high potential biological activity of the novel structures of C30 carotenoids as well, based on the neuronal differentiation activity observed for the monocyclic C30 carotenoid 4,4'-diapotorulene on rat bone marrow mesenchymal stem cells. Our results demonstrate that a series of structurally novel carotenoids possessing biologically beneficial properties can be synthesized in E. coli.

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...

Track structure in biological models.

Science.gov (United States)

Curtis, S B

1986-01-01

High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.

Structural Systems Biology Evaluation of Metabolic Thermotolerance in Escherichia coli

DEFF Research Database (Denmark)

Chang, Roger L.; Andrews, Kathleen; Kim, Donghyuk

2013-01-01

Improve the System A "systems biology" approach may clarify, for example, how particular proteins determine sensitivity of bacteria to extremes of temperature. Chang et al. (p. 1220) integrated information on protein structure with a model of metabolism, thus associating the protein structure of ...

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

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

Foundations of computer vision computational geometry, visual image structures and object shape detection

CERN Document Server

Peters, James F

2017-01-01

This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classification of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of C...

Data Structures in Classical and Quantum Computing

NARCIS (Netherlands)

M.J. Fillinger (Max)

2013-01-01

textabstractThis survey summarizes several results about quantum computing related to (mostly static) data structures. First, we describe classical data structures for the set membership and the predecessor search problems: Perfect Hash tables for set membership by Fredman, Koml\\'{o}s and

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

The chemical structures, plant origins, ethnobotany and biological activities of homoisoflavanones.

Science.gov (United States)

du Toit, Karen; Drewes, Siegfried E; Bodenstein, Johannes

2010-03-01

This work reviews the four basic structural types of homoisoflavanones. The relationships between the various structures of homoisoflavanones and their plant origins, ethnobotany and biological activities are put into perspective.

Biologically inspired autonomous structural materials with controlled toughening and healing

Science.gov (United States)

Garcia, Michael E.; Sodano, Henry A.

2010-04-01

The field of structural health monitoring (SHM) has made significant contributions in the field of prognosis and damage detection in the past decade. The advantageous use of this technology has not been integrated into operational structures to prevent damage from propagating or to heal injured regions under real time loading conditions. Rather, current systems relay this information to a central processor or human operator, who then determines a course of action such as altering the mission or scheduling repair maintenance. Biological systems exhibit advanced sensory and healing traits that can be applied to the design of material systems. For instance, bone is the major structural component in vertebrates; however, unlike modern structural materials, bone has many properties that make it effective for arresting the propagation of cracks and subsequent healing of the fractured area. The foremost goal for the development of future adaptive structures is to mimic biological systems, similar to bone, such that the material system can detect damage and deploy defensive traits to impede damage from propagating, thus preventing catastrophic failure while in operation. After sensing and stalling the propagation of damage, the structure must then be repaired autonomously using self healing mechanisms motivated by biological systems. Here a novel autonomous system is developed using shape memory polymers (SMPs), that employs an optical fiber network as both a damage detection sensor and a network to deliver stimulus to the damage site initiating adaptation and healing. In the presence of damage the fiber optic fractures allowing a high power laser diode to deposit a controlled level of thermal energy at the fractured sight locally reducing the modulus and blunting the crack tip, which significantly slows the crack growth rate. By applying a pre-induced strain field and utilizing the shape memory recovery effect, thermal energy can be deployed to close the crack and return

Acoustic fine structure may encode biologically relevant information for zebra finches.

Science.gov (United States)

Prior, Nora H; Smith, Edward; Lawson, Shelby; Ball, Gregory F; Dooling, Robert J

2018-04-18

The ability to discriminate changes in the fine structure of complex sounds is well developed in birds. However, the precise limit of this discrimination ability and how it is used in the context of natural communication remains unclear. Here we describe natural variability in acoustic fine structure of male and female zebra finch calls. Results from psychoacoustic experiments demonstrate that zebra finches are able to discriminate extremely small differences in fine structure, which are on the order of the variation in acoustic fine structure that is present in their vocal signals. Results from signal analysis methods also suggest that acoustic fine structure may carry information that distinguishes between biologically relevant categories including sex, call type and individual identity. Combined, our results are consistent with the hypothesis that zebra finches can encode biologically relevant information within the fine structure of their calls. This study provides a foundation for our understanding of how acoustic fine structure may be involved in animal communication.

Neutron scattering applications in structural biology: now and the future

Energy Technology Data Exchange (ETDEWEB)

Trewhella, J [Los Alamos National Lab., NM (United States)

1996-05-01

Neutrons have an important role to play in structural biology. Neutron crystallography, small-angle neutron scattering and inelastic neutron scattering techniques all contribute unique information on biomolecular structures. In particular, solution scattering techniques give critical information on the conformations and dispositions of the components of complex assemblies under a wide variety of relevant conditions. The power of these methods is demonstrated here by studies of protein/DNA complexes, and Ca{sup 2+}-binding proteins complexed with their regulatory targets. In addition, we demonstrate the utility of a new structural approach using neutron resonance scattering. The impact of biological neutron scattering to date has been constrained principally by the available fluxes at neutron sources and the true potential of these approaches will only be realized with the development of new more powerful neutron sources. (author)

Teachers' Organization of Participation Structures for Teaching Science with Computer Technology

Science.gov (United States)

Subramaniam, Karthigeyan

2016-08-01

This paper describes a qualitative study that investigated the nature of the participation structures and how the participation structures were organized by four science teachers when they constructed and communicated science content in their classrooms with computer technology. Participation structures focus on the activity structures and processes in social settings like classrooms thereby providing glimpses into the complex dynamics of teacher-students interactions, configurations, and conventions during collective meaning making and knowledge creation. Data included observations, interviews, and focus group interviews. Analysis revealed that the dominant participation structure evident within participants' instruction with computer technology was ( Teacher) initiation-( Student and Teacher) response sequences-( Teacher) evaluate participation structure. Three key events characterized the how participants organized this participation structure in their classrooms: setting the stage for interactive instruction, the joint activity, and maintaining accountability. Implications include the following: (1) teacher educators need to tap into the knowledge base that underscores science teachers' learning to teach philosophies when computer technology is used in instruction. (2) Teacher educators need to emphasize the essential idea that learning and cognition is not situated within the computer technology but within the pedagogical practices, specifically the participation structures. (3) The pedagogical practices developed with the integration or with the use of computer technology underscored by the teachers' own knowledge of classroom contexts and curriculum needs to be the focus for how students learn science content with computer technology instead of just focusing on how computer technology solely supports students learning of science content.

Sea Cucumber Glycosides: Chemical Structures, Producing Species and Important Biological Properties.

Science.gov (United States)

Mondol, Muhammad Abdul Mojid; Shin, Hee Jae; Rahman, M Aminur; Islam, Mohamad Tofazzal

2017-10-17

Sea cucumbers belonging to echinoderm are traditionally used as tonic food in China and other Asian countries. They produce abundant biologically active triterpene glycosides. More than 300 triterpene glycosides have been isolated and characterized from various species of sea cucumbers, which are classified as holostane and nonholostane depending on the presence or absence of a specific structural unit γ(18,20)-lactone in the aglycone. Triterpene glycosides contain a carbohydrate chain up to six monosaccharide units mainly consisting of d-xylose, 3-O-methy-d-xylose, d-glucose, 3-O-methyl-d-glucose, and d-quinovose. Cytotoxicity is the common biological property of triterpene glycosides isolated from sea cucumbers. Besides cytotoxicity, triterpene glycosides also exhibit antifungal, antiviral and hemolytic activities. This review updates and summarizes our understanding on diverse chemical structures of triterpene glycosides from various species of sea cucumbers and their important biological activities. Mechanisms of action and structural-activity relationships (SARs) of sea cucumber glycosides are also discussed briefly.

XFELs open a new era in structural chemical biology

OpenAIRE

Fromme, Petra

2015-01-01

X-ray crystallography, the workhorse of structural biology, has been revolutionized by the advent of serial femtosecond crystallography using X-ray free electron lasers. Here, the fast pace and history of discoveries are discussed together with current challenges and the method’s great potential to make new structural discoveries, such as the ability to generate molecular movies of biomolecules at work.

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.

Micro-buckling in the nanocomposite structure of biological materials

Science.gov (United States)

Su, Yewang; Ji, Baohua; Hwang, Keh-Chih; Huang, Yonggang

2012-10-01

Nanocomposite structure, consisting of hard mineral and soft protein, is the elementary building block of biological materials, where the mineral crystals are arranged in a staggered manner in protein matrix. This special alignment of mineral is supposed to be crucial to the structural stability of the biological materials under compressive load, but the underlying mechanism is not yet clear. In this study, we performed analytical analysis on the buckling strength of the nanocomposite structure by explicitly considering the staggered alignment of the mineral crystals, as well as the coordination among the minerals during the buckling deformation. Two local buckling modes of the nanostructure were identified, i.e., the symmetric mode and anti-symmetric mode. We showed that the symmetric mode often happens at large aspect ratio and large volume fraction of mineral, while the anti-symmetric happens at small aspect ratio and small volume fraction. In addition, we showed that because of the coordination of minerals with the help of their staggered alignment, the buckling strength of these two modes approached to that of the ideally continuous fiber reinforced composites at large aspect ratio given by Rosen's model, insensitive to the existing "gap"-like flaws between mineral tips. Furthermore, we identified a mechanism of buckling mode transition from local to global buckling with increase of aspect ratio, which was attributed to the biphasic dependence of the buckling strength on the aspect ratio. That is, for small aspect ratio, the local buckling strength is smaller than that of global buckling so that it dominates the buckling behavior of the nanocomposite; for comparatively larger aspect ratio, the local buckling strength is higher than that of global buckling so that the global buckling dominates the buckling behavior. We also found that the hierarchical structure can effectively enhance the buckling strength, particularly, this structural design enables

Transmission electron microscopy in molecular structural biology: A historical survey.

Science.gov (United States)

Harris, J Robin

2015-09-01

In this personal, historic account of macromolecular transmission electron microscopy (TEM), published data from the 1940s through to recent times is surveyed, within the context of the remarkable progress that has been achieved during this time period. The evolution of present day molecular structural biology is described in relation to the associated biological disciplines. The contribution of numerous electron microscope pioneers to the development of the subject is discussed. The principal techniques for TEM specimen preparation, thin sectioning, metal shadowing, negative staining and plunge-freezing (vitrification) of thin aqueous samples are described, with a selection of published images to emphasise the virtues of each method. The development of digital image analysis and 3D reconstruction is described in detail as applied to electron crystallography and reconstructions from helical structures, 2D membrane crystals as well as single particle 3D reconstruction of icosahedral viruses and macromolecules. The on-going development of new software, algorithms and approaches is highlighted before specific examples of the historical progress of the structural biology of proteins and viruses are presented. Copyright © 2014 Elsevier Inc. All rights reserved.

Synthesis of Efficient Structures for Concurrent Computation.

Science.gov (United States)

1983-10-01

formal presentation of these techniques, called virtualisation and aggregation, can be found n [King-83$. 113.2 Census Functions Trees perform broadcast... Functions .. .. .. .. ... .... ... ... .... ... ... ....... 6 4 User-Assisted Aggregation .. .. .. .. ... ... ... .... ... .. .......... 6 5 Parallel...6. Simple Parallel Structure for Broadcasting .. .. .. .. .. . ... .. . .. . .... 4 Figure 7. Internal Structure of a Prefix Computation Network

J D Bernal and the genesis of structural biology

Science.gov (United States)

Caffrey, Martin

2007-02-01

I was invited to participate in this Symposium a month or so before the event. At that time however, I knew little about J D Bernal. I vaguely remembered a brief conversation on the topic over a decade ago with Professor Vittorio Luzzati as we ambled around the gardens at the Palace of Varsailles. Vittorio likely knew Bernal through his friend Rosalind Franklin who worked with Bernal at Birbeck College. But beyond that I knew nothing about the man or his science. And so it was most fortunate that Andrew Brown's book J D Bernal: The Sage of Science appeared in 2005 and I was able to call on it. Indeed, much of the material included in this chapter is based on that source and on Dorothy Hodgkin's biographic memoir of J D Bernal, her postgraduate supervisor. Given that this chapter is to be published in a Physics journal I thought it appropriate to provide some background to the theme of my presentation, structural biology. Accordingly, I will begin with an introduction to proteins, one of structural biology's central characters, and to which Bernal devoted much energy and attention. How the molecular structure of a protein determines its activity and function will then be described. Bernal's major contribution in this area was to X-ray crystallography, the primary method by which a protein's structure is determined. The method, and aspects of its development, will be described. I will also make reference to some of Bernal's additional contributions in related fields. Finally, Vincent Casey, the symposium organizer, asked that I comment on how structural biology might impact on society. I will attempt to address that at the close of my presentation.

J D Bernal and the genesis of structural biology

International Nuclear Information System (INIS)

Caffrey, Martin

2007-01-01

I was invited to participate in this Symposium a month or so before the event. At that time however, I knew little about J D Bernal. I vaguely remembered a brief conversation on the topic over a decade ago with Professor Vittorio Luzzati as we ambled around the gardens at the Palace of Varsailles. Vittorio likely knew Bernal through his friend Rosalind Franklin who worked with Bernal at Birbeck College. But beyond that I knew nothing about the man or his science. And so it was most fortunate that Andrew Brown's book J D Bernal: The Sage of Science appeared in 2005 and I was able to call on it. Indeed, much of the material included in this chapter is based on that source and on Dorothy Hodgkin's biographic memoir of J D Bernal, her postgraduate supervisor. Given that this chapter is to be published in a Physics journal I thought it appropriate to provide some background to the theme of my presentation, structural biology. Accordingly, I will begin with an introduction to proteins, one of structural biology's central characters, and to which Bernal devoted much energy and attention. How the molecular structure of a protein determines its activity and function will then be described. Bernal's major contribution in this area was to X-ray crystallography, the primary method by which a protein's structure is determined. The method, and aspects of its development, will be described. I will also make reference to some of Bernal's additional contributions in related fields. Finally, Vincent Casey, the symposium organizer, asked that I comment on how structural biology might impact on society. I will attempt to address that at the close of my presentation

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.

Sharing Structure and Function in Biological Design with SBOL 2.0.

Science.gov (United States)

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

2016-06-17

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

Study of nanoscale structural biology using advanced particle beam microscopy

Science.gov (United States)

Boseman, Adam J.

This work investigates developmental and structural biology at the nanoscale using current advancements in particle beam microscopy. Typically the examination of micro- and nanoscale features is performed using scanning electron microscopy (SEM), but in order to decrease surface charging, and increase resolution, an obscuring conductive layer is applied to the sample surface. As magnification increases, this layer begins to limit the ability to identify nanoscale surface structures. A new technology, Helium Ion Microscopy (HIM), is used to examine uncoated surface structures on the cuticle of wild type and mutant fruit flies. Corneal nanostructures observed with HIM are further investigated by FIB/SEM to provide detailed three dimensional information about internal events occurring during early structural development. These techniques are also used to reconstruct a mosquito germarium in order to characterize unknown events in early oogenesis. Findings from these studies, and many more like them, will soon unravel many of the mysteries surrounding the world of developmental biology.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

Science.gov (United States)

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Three-dimensional protein structure prediction: Methods and computational strategies.

Science.gov (United States)

Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

2014-10-12

A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Mathematical modellings and computational methods for structural analysis of LMFBR's

International Nuclear Information System (INIS)

Liu, W.K.; Lam, D.

1983-01-01

In this paper, two aspects of nuclear reactor problems are discussed, modelling techniques and computational methods for large scale linear and nonlinear analyses of LMFBRs. For nonlinear fluid-structure interaction problem with large deformation, arbitrary Lagrangian-Eulerian description is applicable. For certain linear fluid-structure interaction problem, the structural response spectrum can be found via 'added mass' approach. In a sense, the fluid inertia is accounted by a mass matrix added to the structural mass. The fluid/structural modes of certain fluid-structure problem can be uncoupled to get the reduced added mass. The advantage of this approach is that it can account for the many repeated structures of nuclear reactor. In regard to nonlinear dynamic problem, the coupled nonlinear fluid-structure equations usually have to be solved by direct time integration. The computation can be very expensive and time consuming for nonlinear problems. Thus, it is desirable to optimize the accuracy and computation effort by using implicit-explicit mixed time integration method. (orig.)

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.

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.

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.

An introduction to biological NMR spectroscopy

International Nuclear Information System (INIS)

Marion, Dominique

2013-01-01

NMR spectroscopy is a powerful tool for biologists interested in the structure, dynamics, and interactions of biological macromolecules. This review aims at presenting in an accessible manner the requirements and limitations of this technique. As an introduction, the history of NMR will highlight how the method evolved from physics to chemistry and finally to biology over several decades. We then introduce the NMR spectral parameters used in structural biology, namely the chemical shift, the J-coupling, nuclear Overhauser effects, and residual dipolar couplings. Resonance assignment, the required step for any further NMR study, bears a resemblance to jigsaw puzzle strategy. The NMR spectral parameters are then converted into angle and distances and used as input using restrained molecular dynamics to compute a bundle of structures. When interpreting a NMR-derived structure, the biologist has to judge its quality on the basis of the statistics provided. When the 3D structure is a priori known by other means, the molecular interaction with a partner can be mapped by NMR: information on the binding interface as well as on kinetic and thermodynamic constants can be gathered. NMR is suitable to monitor, over a wide range of frequencies, protein fluctuations that play a crucial role in their biological function. In the last section of this review, intrinsically disordered proteins, which have escaped the attention of classical structural biology, are discussed in the perspective of NMR, one of the rare available techniques able to describe structural ensembles. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 16 MCP). (authors)

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...

Effective Elastic Modulus of Structured Adhesives: From Biology to Biomimetics

Directory of Open Access Journals (Sweden)

Xin Wang

2017-06-01

Full Text Available Micro- and nano-hierarchical structures (lamellae, setae, branches, and spatulae on the toe pads of many animals play key roles for generating strong but reversible adhesion for locomotion. The hierarchical structure possesses significantly reduced, effective elastic modulus (Eeff, as compared to the inherent elastic modulus (Einh of the corresponding biological material (and therefore contributes to a better compliance with the counterpart surface. Learning from nature, three types of hierarchical structures (namely self-similar pillar structure, lamella–pillar hybrid structure, and porous structure have been developed and investigated.

Collective network for computer structures

Science.gov (United States)

Blumrich, Matthias A [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Chen, Dong [Croton On Hudson, NY; Gara, Alan [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Takken, Todd E [Brewster, NY; Steinmacher-Burow, Burkhard D [Wernau, DE; Vranas, Pavlos M [Bedford Hills, NY

2011-08-16

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

An integrative computational modelling of music structure apprehension

DEFF Research Database (Denmark)

Lartillot, Olivier

2014-01-01

, the computational model, by virtue of its generality, extensiveness and operationality, is suggested as a blueprint for the establishment of cognitively validated model of music structure apprehension. Available as a Matlab module, it can be used for practical musicological uses.......An objectivization of music analysis requires a detailed formalization of the underlying principles and methods. The formalization of the most elementary structural processes is hindered by the complexity of music, both in terms of profusions of entities (such as notes) and of tight interactions...... between a large number of dimensions. Computational modeling would enable systematic and exhaustive tests on sizeable pieces of music, yet current researches cover particular musical dimensions with limited success. The aim of this research is to conceive a computational modeling of music analysis...

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.

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.

Computational modeling of neural plasticity for self-organization of neural networks.

Science.gov (United States)

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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…

Fluid/Structure Interaction Studies of Aircraft Using High Fidelity Equations on Parallel Computers

Science.gov (United States)

Guruswamy, Guru; VanDalsem, William (Technical Monitor)

1994-01-01

Abstract Aeroelasticity which involves strong coupling of fluids, structures and controls is an important element in designing an aircraft. Computational aeroelasticity using low fidelity methods such as the linear aerodynamic flow equations coupled with the modal structural equations are well advanced. Though these low fidelity approaches are computationally less intensive, they are not adequate for the analysis of modern aircraft such as High Speed Civil Transport (HSCT) and Advanced Subsonic Transport (AST) which can experience complex flow/structure interactions. HSCT can experience vortex induced aeroelastic oscillations whereas AST can experience transonic buffet associated structural oscillations. Both aircraft may experience a dip in the flutter speed at the transonic regime. For accurate aeroelastic computations at these complex fluid/structure interaction situations, high fidelity equations such as the Navier-Stokes for fluids and the finite-elements for structures are needed. Computations using these high fidelity equations require large computational resources both in memory and speed. Current conventional super computers have reached their limitations both in memory and speed. As a result, parallel computers have evolved to overcome the limitations of conventional computers. This paper will address the transition that is taking place in computational aeroelasticity from conventional computers to parallel computers. The paper will address special techniques needed to take advantage of the architecture of new parallel computers. Results will be illustrated from computations made on iPSC/860 and IBM SP2 computer by using ENSAERO code that directly couples the Euler/Navier-Stokes flow equations with high resolution finite-element structural equations.

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.

The diverse and expanding role of mass spectrometry in structural and molecular biology.

Science.gov (United States)

Lössl, Philip; van de Waterbeemd, Michiel; Heck, Albert Jr

2016-12-15

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

Unified data model for biological data

International Nuclear Information System (INIS)

Idrees, M.

2014-01-01

A data model empowers us to store, retrieve and manipulate data in a unified way. We consider the biological data consists of DNA (De-Oxyribonucleic Acid), RNA (Ribonucleic Acid) and protein structures. In our Bioinformatics Lab (Bioinformatics Lab, Alkhawarizmi Institute of Computer Science, University of Engineering and Technology, Lahore, Pakistan), we have already proposed two data models for DNA and protein structures individually. In this paper, we propose a unified data model by using the data models of TOS (Temporal Object Oriented System) after making some necessary modifications to this data model and our already proposed the two data models. This proposed unified data model can be used for the modeling and maintaining the biological data (i.e. DNA, RNA and protein structures), in a single unified way. (author)

Computer-aided visualization of database structural relationships

International Nuclear Information System (INIS)

Cahn, D.F.

1980-04-01

Interactive computer graphic displays can be extremely useful in augmenting understandability of data structures. In complexly interrelated domains such as bibliographic thesauri and energy information systems, node and link displays represent one such tool. This paper presents examples of data structure representations found useful in these domains and discusses some of their generalizable components. 2 figures

Soil structure characterized using computed tomographic images

Science.gov (United States)

Zhanqi Cheng; Stephen H. Anderson; Clark J. Gantzer; J. W. Van Sambeek

2003-01-01

Fractal analysis of soil structure is a relatively new method for quantifying the effects of management systems on soil properties and quality. The objective of this work was to explore several methods of studying images to describe and quantify structure of soils under forest management. This research uses computed tomography and a topological method called Multiple...

Giga-voxel computational morphogenesis for structural design

Science.gov (United States)

Aage, Niels; Andreassen, Erik; Lazarov, Boyan S.; Sigmund, Ole

2017-10-01

In the design of industrial products ranging from hearing aids to automobiles and aeroplanes, material is distributed so as to maximize the performance and minimize the cost. Historically, human intuition and insight have driven the evolution of mechanical design, recently assisted by computer-aided design approaches. The computer-aided approach known as topology optimization enables unrestricted design freedom and shows great promise with regard to weight savings, but its applicability has so far been limited to the design of single components or simple structures, owing to the resolution limits of current optimization methods. Here we report a computational morphogenesis tool, implemented on a supercomputer, that produces designs with giga-voxel resolution—more than two orders of magnitude higher than previously reported. Such resolution provides insights into the optimal distribution of material within a structure that were hitherto unachievable owing to the challenges of scaling up existing modelling and optimization frameworks. As an example, we apply the tool to the design of the internal structure of a full-scale aeroplane wing. The optimized full-wing design has unprecedented structural detail at length scales ranging from tens of metres to millimetres and, intriguingly, shows remarkable similarity to naturally occurring bone structures in, for example, bird beaks. We estimate that our optimized design corresponds to a reduction in mass of 2-5 per cent compared to currently used aeroplane wing designs, which translates into a reduction in fuel consumption of about 40-200 tonnes per year per aeroplane. Our morphogenesis process is generally applicable, not only to mechanical design, but also to flow systems, antennas, nano-optics and micro-systems.

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.

Development of a Computer Application to Simulate Porous Structures

Directory of Open Access Journals (Sweden)

S.C. Reis

2002-09-01

Full Text Available Geometric modeling is an important tool to evaluate structural parameters as well as to follow the application of stereological relationships. The obtention, visualization and analysis of volumetric images of the structure of materials, using computational geometric modeling, facilitates the determination of structural parameters of difficult experimental access, such as topological and morphological parameters. In this work, we developed a geometrical model implemented by computer software that simulates random pore structures. The number of nodes, number of branches (connections between nodes and the number of isolated parts, are obtained. Also, the connectivity (C is obtained from this application. Using a list of elements, nodes and branches, generated by the software, in AutoCAD® command line format, the obtained structure can be viewed and analyzed.

Computer methods for transient fluid-structure analysis of nuclear reactors

International Nuclear Information System (INIS)

Belytschko, T.; Liu, W.K.

1985-01-01

Fluid-structure interaction problems in nuclear engineering are categorized according to the dominant physical phenomena and the appropriate computational methods. Linear fluid models that are considered include acoustic fluids, incompressible fluids undergoing small disturbances, and small amplitude sloshing. Methods available in general-purpose codes for these linear fluid problems are described. For nonlinear fluid problems, the major features of alternative computational treatments are reviewed; some special-purpose and multipurpose computer codes applicable to these problems are then described. For illustration, some examples of nuclear reactor problems that entail coupled fluid-structure analysis are described along with computational results

Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

KAUST Repository

Gao, Xin

2013-01-01

research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing

Large, dynamic, multi-protein complexes: a challenge for structural biology

Czech Academy of Sciences Publication Activity Database

Rozycki, B.; Bouřa, Evžen

2014-01-01

Roč. 26, č. 46 (2014), 463103/1-463103/11 ISSN 0953-8984 R&D Projects: GA MŠk LO1302 EU Projects: European Commission(XE) 333916 - STARPI4K Institutional support: RVO:61388963 Keywords : protein structure * multi-protein complexes * hybrid methods of structural biology Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.346, year: 2014

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.

The RCSB Protein Data Bank: views of structural biology for basic and applied research and education.

Science.gov (United States)

Rose, Peter W; Prlić, Andreas; Bi, Chunxiao; Bluhm, Wolfgang F; Christie, Cole H; Dutta, Shuchismita; Green, Rachel Kramer; Goodsell, David S; Westbrook, John D; Woo, Jesse; Young, Jasmine; Zardecki, Christine; Berman, Helen M; Bourne, Philip E; Burley, Stephen K

2015-01-01

The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Synthesis of computational structures for analog signal processing

CERN Document Server

Popa, Cosmin Radu

2011-01-01

Presents the most important classes of computational structures for analog signal processing, including differential or multiplier structures, squaring or square-rooting circuits, exponential or Euclidean distance structures and active resistor circuitsIntroduces the original concept of the multifunctional circuit, an active structure that is able to implement, starting from the same circuit core, a multitude of continuous mathematical functionsCovers mathematical analysis, design and implementation of a multitude of function generator structures

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

Defining and detecting structural sensitivity in biological models: developing a new framework.

Science.gov (United States)

Adamson, M W; Morozov, A Yu

2014-12-01

When we construct mathematical models to represent biological systems, there is always uncertainty with regards to the model specification--whether with respect to the parameters or to the formulation of model functions. Sometimes choosing two different functions with close shapes in a model can result in substantially different model predictions: a phenomenon known in the literature as structural sensitivity, which is a significant obstacle to improving the predictive power of biological models. In this paper, we revisit the general definition of structural sensitivity, compare several more specific definitions and discuss their usefulness for the construction and analysis of biological models. Then we propose a general approach to reveal structural sensitivity with regards to certain system properties, which considers infinite-dimensional neighbourhoods of the model functions: a far more powerful technique than the conventional approach of varying parameters for a fixed functional form. In particular, we suggest a rigorous method to unearth sensitivity with respect to the local stability of systems' equilibrium points. We present a method for specifying the neighbourhood of a general unknown function with [Formula: see text] inflection points in terms of a finite number of local function properties, and provide a rigorous proof of its completeness. Using this powerful result, we implement our method to explore sensitivity in several well-known multicomponent ecological models and demonstrate the existence of structural sensitivity in these models. Finally, we argue that structural sensitivity is an important intrinsic property of biological models, and a direct consequence of the complexity of the underlying real systems.

2010 Diffraction Methods in Structural Biology

Energy Technology Data Exchange (ETDEWEB)

Dr. Ana Gonzalez

2011-03-10

Advances in basic methodologies have played a major role in the dramatic progress in macromolecular crystallography over the past decade, both in terms of overall productivity and in the increasing complexity of the systems being successfully tackled. The 2010 Gordon Research Conference on Diffraction Methods in Structural Biology will, as in the past, focus on the most recent developments in methodology, covering all aspects of the process from crystallization to model building and refinement, complemented by examples of structural highlights and complementary methods. Extensive discussion will be encouraged and it is hoped that all attendees will participate by giving oral or poster presentations, the latter using the excellent poster display area available at Bates College. The relatively small size and informal atmosphere of the meeting provides an excellent opportunity for all participants, especially younger scientists, to meet and exchange ideas with leading methods developers.

Computer - based modeling in extract sciences research -III ...

African Journals Online (AJOL)

Molecular modeling techniques have been of great applicability in the study of the biological sciences and other exact science fields like agriculture, mathematics, computer science and the like. In this write up, a list of computer programs for predicting, for instance, the structure of proteins has been provided. Discussions on ...

The structural robustness of multiprocessor computing system

Directory of Open Access Journals (Sweden)

N. Andronaty

1996-03-01

Full Text Available The model of the multiprocessor computing system on the base of transputers which permits to resolve the question of valuation of a structural robustness (viability, survivability is described.

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)

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.

75 FR 33312 - Indexing Structured Product Labeling for Human Prescription Drug and Biological Products; Request...

Science.gov (United States)

2010-06-11

...] Indexing Structured Product Labeling for Human Prescription Drug and Biological Products; Request for... Biologics Evaluation and Research (CBER) are indexing certain categories of information in product labeling for use as terms to search repositories of approved prescription medical product structured product...

A Glimpse of Membrane Transport through Structures-Advances in the Structural Biology of the GLUT Glucose Transporters.

Science.gov (United States)

Yan, Nieng

2017-08-18

The cellular uptake of glucose is an essential physiological process, and movement of glucose across biological membranes requires specialized transporters. The major facilitator superfamily glucose transporters GLUTs, encoded by the SLC2A genes, have been a paradigm for functional, mechanistic, and structural understanding of solute transport in the past century. This review starts with a glimpse into the structural biology of membrane proteins and particularly membrane transport proteins, enumerating the landmark structures in the past 25years. The recent breakthrough in the structural elucidation of GLUTs is then elaborated following a brief overview of the research history of these archetypal transporters, their functional specificity, and physiological and pathophysiological significances. Structures of GLUT1, GLUT3, and GLUT5 in distinct transport and/or ligand-binding states reveal detailed mechanisms of the alternating access transport cycle and substrate recognition, and thus illuminate a path by which structure-based drug design may be applied to help discover novel therapeutics against several debilitating human diseases associated with GLUT malfunction and/or misregulation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational applications of DNA structural scales

DEFF Research Database (Denmark)

Baldi, P.; Chauvin, Y.; Brunak, Søren

1998-01-01

that these scales provide an alternative or complementary compact representation of DNA sequences. As an example, we construct a strand-invariant representation of DNA sequences. The scales can also be used to analyze and discover new DNA structural patterns, especially in combination with hidden Markov models......Studies several different physical scales associated with the structural features of DNA sequences from a computational standpoint, including dinucleotide scales, such as base stacking energy and propeller twist, and trinucleotide scales, such as bendability and nucleosome positioning. We show...

High-performance computing for structural mechanics and earthquake/tsunami engineering

CERN Document Server

Hori, Muneo; Ohsaki, Makoto

2016-01-01

Huge earthquakes and tsunamis have caused serious damage to important structures such as civil infrastructure elements, buildings and power plants around the globe.  To quantitatively evaluate such damage processes and to design effective prevention and mitigation measures, the latest high-performance computational mechanics technologies, which include telascale to petascale computers, can offer powerful tools. The phenomena covered in this book include seismic wave propagation in the crust and soil, seismic response of infrastructure elements such as tunnels considering soil-structure interactions, seismic response of high-rise buildings, seismic response of nuclear power plants, tsunami run-up over coastal towns and tsunami inundation considering fluid-structure interactions. The book provides all necessary information for addressing these phenomena, ranging from the fundamentals of high-performance computing for finite element methods, key algorithms of accurate dynamic structural analysis, fluid flows ...

Generation of structurally novel short carotenoids and study of their biological activity

DEFF Research Database (Denmark)

Kim, Se Hyeuk; Kim, Moon S.; Lee, Bun Y.

2016-01-01

Recent research interest in phytochemicals has consistently driven the efforts in the metabolic engineering field toward microbial production of various carotenoids. In spite of systematic studies, the possibility of using C30 carotenoids as biologically functional compounds has not been explored...... thus far. Here, we generated 13 novel structures of C30 carotenoids and one C35 carotenoid, including acyclic, monocyclic, and bicyclic structures, through directed evolution and combinatorial biosynthesis, in Escherichia coli. Measurement of radical scavenging activity of various C30 carotenoid...... structures revealed that acyclic C30 carotenoids showed higher radical scavenging activity than did DL-atocopherol. We could assume high potential biological activity of the novel structures of C30 carotenoids as well, based on the neuronal differentiation activity observed for the monocyclic C30 carotenoid...

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

Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

KAUST Repository

Gao, Xin

2013-01-11

Although three-dimensional protein structure determination using nuclear magnetic resonance (NMR) spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from specialists in bioinformatics and computational biology. In this paper, we review recent advances in computational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing methods and outline some open problems in the field. We also discuss current trends in NMR technology development and suggest directions for research on future computational methods for NMR.

Structural Basis of Biological Nitrile Reduction*

Science.gov (United States)

Chikwana, Vimbai M.; Stec, Boguslaw; Lee, Bobby W. K.; de Crécy-Lagard, Valérie; Iwata-Reuyl, Dirk; Swairjo, Manal A.

2012-01-01

The enzyme QueF catalyzes the reduction of the nitrile group of 7-cyano-7-deazaguanine (preQ0) to 7-aminomethyl-7-deazaguanine (preQ1), the only nitrile reduction reaction known in biology. We describe here two crystal structures of Bacillus subtilis QueF, one of the wild-type enzyme in complex with the substrate preQ0, trapped as a covalent thioimide, a putative intermediate in the reaction, and the second of the C55A mutant in complex with the substrate preQ0 bound noncovalently. The QueF enzyme forms an asymmetric tunnel-fold homodecamer of two head-to-head facing pentameric subunits, harboring 10 active sites at the intersubunit interfaces. In both structures, a preQ0 molecule is bound at eight sites, and in the wild-type enzyme, it forms a thioimide covalent linkage to the catalytic residue Cys-55. Both structural and transient kinetic data show that preQ0 binding, not thioimide formation, induces a large conformational change in and closure of the active site. Based on these data, we propose a mechanism for the activation of the Cys-55 nucleophile and subsequent hydride transfer. PMID:22787148

Computational methods for constructing protein structure models from 3D electron microscopy maps.

Science.gov (United States)

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2013-10-01

Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3Å. Computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided. Copyright © 2013 Elsevier Inc. All rights reserved.

Structural biology studies of CagA from Helicobacter pylori and histone chaperone CIA/ASF1

International Nuclear Information System (INIS)

Senda, Toshiya

2015-01-01

Crystal structures of proteins and their complexes have become critical information for molecular-based life science. Biochemical and biological analysis based on tertiary structural information is a powerful tool to unveil complex molecular processes in the cell. Here, we present two examples of the structure-based life science study, structural biology studies of CagA, an effector protein from Helicobacter pylori, and histone chaperone CIA/ASF1, which is involved in transcription initiation. (author)

Connecting Structure-Property and Structure-Function Relationships across the Disciplines of Chemistry and Biology: Exploring Student Perceptions

Science.gov (United States)

Kohn, Kathryn P.; Underwood, Sonia M.; Cooper, Melanie M.

2018-01-01

While many university students take science courses in multiple disciplines, little is known about how they perceive common concepts from different disciplinary perspectives. Structure-property and structure-function relationships have long been considered important explanatory concepts in the disciplines of chemistry and biology, respectively.…

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.

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.

Exploring biological network structure with clustered random networks

Directory of Open Access Journals (Sweden)

Bansal Shweta

2009-12-01

Full Text Available Abstract Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions and the extent of clustering (the tendency for a set of three nodes to be interconnected are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics. Results Here we develop and implement a new Markov chain simulation algorithm to generate simple, connected random graphs that have a specified degree sequence and level of clustering, but are random in all other respects. The implementation of the algorithm (ClustRNet: Clustered Random Networks provides the generation of random graphs optimized according to a local or global, and relative or absolute measure of clustering. We compare our algorithm to other similar methods and show that ours more successfully produces desired network characteristics. Finding appropriate null models is crucial in bioinformatics research, and is often difficult, particularly for biological networks. As we demonstrate, the networks generated by ClustRNet can serve as random controls when investigating the impacts of complex network features beyond the byproduct of degree and clustering in empirical networks. Conclusion ClustRNet generates ensembles of graphs of specified edge structure and clustering. These graphs allow for systematic study of the impacts of connectivity and redundancies on network function and dynamics. This process is a key step in

Recent developments of the NESSUS probabilistic structural analysis computer program

Science.gov (United States)

Millwater, H.; Wu, Y.-T.; Torng, T.; Thacker, B.; Riha, D.; Leung, C. P.

1992-01-01

The NESSUS probabilistic structural analysis computer program combines state-of-the-art probabilistic algorithms with general purpose structural analysis methods to compute the probabilistic response and the reliability of engineering structures. Uncertainty in loading, material properties, geometry, boundary conditions and initial conditions can be simulated. The structural analysis methods include nonlinear finite element and boundary element methods. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. The scope of the code has recently been expanded to include probabilistic life and fatigue prediction of structures in terms of component and system reliability and risk analysis of structures considering cost of failure. The code is currently being extended to structural reliability considering progressive crack propagation. Several examples are presented to demonstrate the new capabilities.

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 ...

2013 Gordon Research Conference on metals in biology and seminar on bioinorganic chemistry

Energy Technology Data Exchange (ETDEWEB)

Rosenzweig, Amy C. [Northwestern Univ., Evanston, IL (United States)

2013-01-25

Typical topics for lectures and posters include: biochemical and biophysical characterization of new metal containing proteins, enzymes, nucleic acids, factors, and chelators from all forms of life; synthesis, detailed characterization, and reaction chemistry of biomimetic compounds; novel crystal and solution structures of biological molecules and synthetic metal-chelates; discussions of the roles that metals play in medicine, maintenance of the environment, and biogeochemical processes; metal homeostasis; application of theory and computations to the structure and mechanism of metal-containing biological systems; and novel applications of spectroscopy to metals in biological systems.

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.

Wing-Body Aeroelasticity Using Finite-Difference Fluid/Finite-Element Structural Equations on Parallel Computers

Science.gov (United States)

Byun, Chansup; Guruswamy, Guru P.; Kutler, Paul (Technical Monitor)

1994-01-01

In recent years significant advances have been made for parallel computers in both hardware and software. Now parallel computers have become viable tools in computational mechanics. Many application codes developed on conventional computers have been modified to benefit from parallel computers. Significant speedups in some areas have been achieved by parallel computations. For single-discipline use of both fluid dynamics and structural dynamics, computations have been made on wing-body configurations using parallel computers. However, only a limited amount of work has been completed in combining these two disciplines for multidisciplinary applications. The prime reason is the increased level of complication associated with a multidisciplinary approach. In this work, procedures to compute aeroelasticity on parallel computers using direct coupling of fluid and structural equations will be investigated for wing-body configurations. The parallel computer selected for computations is an Intel iPSC/860 computer which is a distributed-memory, multiple-instruction, multiple data (MIMD) computer with 128 processors. In this study, the computational efficiency issues of parallel integration of both fluid and structural equations will be investigated in detail. The fluid and structural domains will be modeled using finite-difference and finite-element approaches, respectively. Results from the parallel computer will be compared with those from the conventional computers using a single processor. This study will provide an efficient computational tool for the aeroelastic analysis of wing-body structures on MIMD type parallel computers.

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.

Form and function: Perspectives on structural biology and resources for the future

International Nuclear Information System (INIS)

Vaughan, D.

1990-12-01

The purpose of this study is largely to explore and expand on the thesis that biological structures and their functions are suited to. Form indeed follows function and if we are to understand the workings of a living system, with all that such an understanding promises, we must first seek to describe the structure of its parts. Descriptions of a few achievements of structural biology lay the groundwork, but the substance of this booklet is a discussion of important questions yet unanswered and opportunities just beyond our grasp. The concluding pages then outline a course of action in which the Department of Energy would exercise its responsibility to develop the major resources needed to extend our reach and to answer some of those unanswered questions. 22 figs

Form and function: Perspectives on structural biology and resources for the future

Energy Technology Data Exchange (ETDEWEB)

Vaughan, D. (ed.)

1990-12-01

The purpose of this study is largely to explore and expand on the thesis that biological structures and their functions are suited to. Form indeed follows function and if we are to understand the workings of a living system, with all that such an understanding promises, we must first seek to describe the structure of its parts. Descriptions of a few achievements of structural biology lay the groundwork, but the substance of this booklet is a discussion of important questions yet unanswered and opportunities just beyond our grasp. The concluding pages then outline a course of action in which the Department of Energy would exercise its responsibility to develop the major resources needed to extend our reach and to answer some of those unanswered questions. 22 figs.

Structural Studies of Biological Solids Using NMR

Science.gov (United States)

Ramamoorthy, Ayyalusamy

2011-03-01

High-resolution structure and dynamics of biological molecules are important in understanding their function. While studies have been successful in solving the structures of water-soluble biomolecules, it has been proven difficult to determine the structures of membrane proteins and fibril systems. Recent studies have shown that solid-state NMR is a promising technique and could be highly valuable in studying such non-crystalline and non-soluble biosystems. I will present strategies to study the structures of such challenging systems and also about the applications of solid-state NMR to study the modes of membrane-peptide interactions for a better assessment of the prospects of antimicrobial peptides as substitutes to antibiotics in the control of human disease. Our studies on the mechanism of membrane disruption by LL-37 (a human antimicrobial peptide), analogs of the naturally occurring antimicrobial peptide magainin2 extracted from the skin of the African frog Xenopus Laevis, and pardaxin will be presented. Solid-state NMR experiments were used to determine the secondary structure, dynamics and topology of these peptides in lipid bilayers. Similarities and difference in the cell-lysing mechanism, and their dependence on the membrane composition, of these peptides will be discussed. Atomic-level resolution NMR structures of amyloidogenic proteins revealing the misfolding pathway and early intermediates that play key roles in amyloid toxicity will also be presented.

Procedure for developing biological input for the design, location, or modification of water-intake structures

Energy Technology Data Exchange (ETDEWEB)

Neitzel, D.A.; McKenzie, D.H.

1981-12-01

To minimize adverse impact on aquatic ecosystems resulting from the operation of water intake structures, design engineers must have relevant information on the behavior, physiology and ecology of local fish and shellfish. Identification of stimulus/response relationships and the environmental factors that influence them is the first step in incorporating biological information in the design, location or modification of water intake structures. A procedure is presented in this document for providing biological input to engineers who are designing, locating or modifying a water intake structure. The authors discuss sources of stimuli at water intakes, historical approaches in assessing potential/actual impact and review biological information needed for intake design.

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.

Shifting to structures in physics and biology: a prophylactic for promiscuous realism.

Science.gov (United States)

French, Steven

2011-06-01

Within the philosophy of science, the realism debate has been revitalised by the development of forms of structural realism. These urge a shift in focus from the object oriented ontologies that come and go through the history of science to the structures that remain through theory change. Such views have typically been elaborated in the context of theories of physics and are motivated by, first of all, the presence within such theories of mathematical equations that allow straightforward representation of the relevant structures; and secondly, the implications of such theories for the individuality and identity of putative objects. My aim in this paper is to explore the possibility of extending such views to biological theories. An obvious concern is that within the context of the latter it is typically insisted that we cannot find the kinds of highly mathematised structures that structural realism can point to in physics. I shall indicate how the model-theoretic approach to theories might help allay such concerns. Furthermore, issues of identity and individuality also arise within biology. Thus Dupré has recently noted that there exists a 'General Problem of Biological Individuality' which relates to the issue of how one divides 'massively integrated and interconnected' systems into discrete components. In response Dupré advocates a form of 'Promiscuous Realism' that holds, for example, that there is no unique way of dividing the phylogenetic tree into kinds. Instead I shall urge serious consideration of those aspects of the work of Dupré and others that lean towards a structuralist interpretation. By doing so I hope to suggest possible ways in which a structuralist stance might be extended to biology. Copyright © 2010 Elsevier Ltd. All rights reserved.

Computational mesh generation for vascular structures with deformable surfaces

International Nuclear Information System (INIS)

Putter, S. de; Laffargue, F.; Breeuwer, M.; Vosse, F.N. van de; Gerritsen, F.A.; Philips Medical Systems, Best

2006-01-01

Computational blood flow and vessel wall mechanics simulations for vascular structures are becoming an important research tool for patient-specific surgical planning and intervention. An important step in the modelling process for patient-specific simulations is the creation of the computational mesh based on the segmented geometry. Most known solutions either require a large amount of manual processing or lead to a substantial difference between the segmented object and the actual computational domain. We have developed a chain of algorithms that lead to a closely related implementation of image segmentation with deformable models and 3D mesh generation. The resulting processing chain is very robust and leads both to an accurate geometrical representation of the vascular structure as well as high quality computational meshes. The chain of algorithms has been tested on a wide variety of shapes. A benchmark comparison of our mesh generation application with five other available meshing applications clearly indicates that the new approach outperforms the existing methods in the majority of cases. (orig.)

Worldwide Protein Data Bank biocuration supporting open access to high-quality 3D structural biology data

Science.gov (United States)

Westbrook, John D; Feng, Zukang; Persikova, Irina; Sala, Raul; Sen, Sanchayita; Berrisford, John M; Swaminathan, G Jawahar; Oldfield, Thomas J; Gutmanas, Aleksandras; Igarashi, Reiko; Armstrong, David R; Baskaran, Kumaran; Chen, Li; Chen, Minyu; Clark, Alice R; Di Costanzo, Luigi; Dimitropoulos, Dimitris; Gao, Guanghua; Ghosh, Sutapa; Gore, Swanand; Guranovic, Vladimir; Hendrickx, Pieter M S; Hudson, Brian P; Ikegawa, Yasuyo; Kengaku, Yumiko; Lawson, Catherine L; Liang, Yuhe; Mak, Lora; Mukhopadhyay, Abhik; Narayanan, Buvaneswari; Nishiyama, Kayoko; Patwardhan, Ardan; Sahni, Gaurav; Sanz-García, Eduardo; Sato, Junko; Sekharan, Monica R; Shao, Chenghua; Smart, Oliver S; Tan, Lihua; van Ginkel, Glen; Yang, Huanwang; Zhuravleva, Marina A; Markley, John L; Nakamura, Haruki; Kurisu, Genji; Kleywegt, Gerard J; Velankar, Sameer; Berman, Helen M; Burley, Stephen K

2018-01-01

Abstract The Protein Data Bank (PDB) is the single global repository for experimentally determined 3D structures of biological macromolecules and their complexes with ligands. The worldwide PDB (wwPDB) is the international collaboration that manages the PDB archive according to the FAIR principles: Findability, Accessibility, Interoperability and Reusability. The wwPDB recently developed OneDep, a unified tool for deposition, validation and biocuration of structures of biological macromolecules. All data deposited to the PDB undergo critical review by wwPDB Biocurators. This article outlines the importance of biocuration for structural biology data deposited to the PDB and describes wwPDB biocuration processes and the role of expert Biocurators in sustaining a high-quality archive. Structural data submitted to the PDB are examined for self-consistency, standardized using controlled vocabularies, cross-referenced with other biological data resources and validated for scientific/technical accuracy. We illustrate how biocuration is integral to PDB data archiving, as it facilitates accurate, consistent and comprehensive representation of biological structure data, allowing efficient and effective usage by research scientists, educators, students and the curious public worldwide. Database URL: https://www.wwpdb.org/ PMID:29688351

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...

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.

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

International Nuclear Information System (INIS)

McMahon, S.

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

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

Energy Technology Data Exchange (ETDEWEB)

McMahon, S. [Massachusetts General Hospital and Harvard Medical School (United States)

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

Computational methods in drug discovery

Directory of Open Access Journals (Sweden)

Sumudu P. Leelananda

2016-12-01

Full Text Available The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

Computer analysis of the thermomechanical structure behavior. The CEASEMT system. The TEDEL code

International Nuclear Information System (INIS)

Hoffmann, A.; Jeanpierre, Francoise.

1976-01-01

TEDEL is intended for the elastoplastic computation of pipes and three-dimensional mechanical structures. Structures are described by means of jointed girder elements or more complex elements as for pipings: bended pipes, right angle elbows, tees, or any elements whose strength parameters are given to TEDEL. TEDEL is also for the dynamic computation of structures, damping included. A TEDEL option is for computing buckling critical load [fr

Biological, Histological and Ultra-Structural Studies of Female Mullet ...

African Journals Online (AJOL)

Biological, Histological and Ultra-Structural Studies of Female Mullet, Mugil cephalus , Ovaries Collected from Different Habitats during Annual Reproductive Cycle. ... 35 and 52 cm, respectively; whereas, the total number of ripe ova in brackish water fish ranged from 0.57±0.14 to 3.81±0.59 x106 for the same length groups.

Networks as a Privileged Way to Develop Mesoscopic Level Approaches in Systems Biology

OpenAIRE

Alessandro Giuliani

2014-01-01

The methodologies advocated in computational biology are in many cases proper system-level approaches. These methodologies are variously connected to the notion of “mesosystem” and thus on the focus on relational structures that are at the basis of biological regulation. Here, I describe how the formalization of biological systems by means of graph theory constitutes an extremely fruitful approach to biology. I suggest the epistemological relevance of the notion of graph resides in its multil...

Adapting federated cyberinfrastructure for shared data collection facilities in structural biology.

Science.gov (United States)

Stokes-Rees, Ian; Levesque, Ian; Murphy, Frank V; Yang, Wei; Deacon, Ashley; Sliz, Piotr

2012-05-01

Early stage experimental data in structural biology is generally unmaintained and inaccessible to the public. It is increasingly believed that this data, which forms the basis for each macromolecular structure discovered by this field, must be archived and, in due course, published. Furthermore, the widespread use of shared scientific facilities such as synchrotron beamlines complicates the issue of data storage, access and movement, as does the increase of remote users. This work describes a prototype system that adapts existing federated cyberinfrastructure technology and techniques to significantly improve the operational environment for users and administrators of synchrotron data collection facilities used in structural biology. This is achieved through software from the Virtual Data Toolkit and Globus, bringing together federated users and facilities from the Stanford Synchrotron Radiation Lightsource, the Advanced Photon Source, the Open Science Grid, the SBGrid Consortium and Harvard Medical School. The performance and experience with the prototype provide a model for data management at shared scientific facilities.

Mass spectrometry in structural biology and biophysics architecture, dynamics, and interaction of biomolecules

CERN Document Server

Kaltashov, Igor A; Desiderio, Dominic M; Nibbering, Nico M

2012-01-01

The definitive guide to mass spectrometry techniques in biology and biophysics The use of mass spectrometry (MS) to study the architecture and dynamics of proteins is increasingly common within the biophysical community, and Mass Spectrometry in Structural Biology and Biophysics: Architecture, Dynamics, and Interaction of Biomolecules, Second Edition provides readers with detailed, systematic coverage of the current state of the art. Offering an unrivalled overview of modern MS-based armamentarium that can be used to solve the most challenging problems in biophysics, structural biol

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.

Spatial Structures and Regulation in Biological Systems

DEFF Research Database (Denmark)

Yde, Pernille

, and the other is the spatial regulation of biological systems, here related to different aspects of the inflammatory response. All systems are studied using computational modelling and mathematical analysis. The first part of the thesis explores different protein aggregation scenarios. In Chapter 1, we consider...... a previously studied and very general aggregation model describing frangible linear filaments. This model is especially relevant for the growth of amyloid fibres, that have been related to a number of serious human diseases, and which are known to grow in an accelerated self-enhanced manner.We derive...... model of the tissue and show how coupled cells are able to function as an excitable medium and propagate waves of high cytokine concentration through the tissue. If the internal regulation in the cells is over-productive, the model predicts a continuous amplification of cytokines, which spans the entire...

Design, modeling and control of a pneumatically actuated manipulator inspired by biological continuum structures

International Nuclear Information System (INIS)

Kang, Rongjie; Zheng Tianjiang; Guglielmino, Emanuele; Caldwell, Darwin G; Branson, David T

2013-01-01

Biological tentacles, such as octopus arms, have entirely flexible structures and virtually infinite degrees of freedom (DOF) that allow for elongation, shortening and bending at any point along the arm length. The amazing dexterity of biological tentacles has driven the growing implementation of continuum manipulators in robotic systems. This paper presents a pneumatic manipulator inspired by biological continuum structures in some of their key features and functions, such as continuum morphology, intrinsic compliance and stereotyped motions with hyper redundant DOF. The kinematics and dynamics of the manipulator are formulated and identified, and a hierarchical controller taking inspiration from the structure of an octopus nervous system is used to relate desired stereotyped motions to individual actuator inputs. Simulations and experiments are carried out to validate the model and prototype where good agreement was found between the two. (paper)

Blind trials of computer-assisted structure elucidation software

Directory of Open Access Journals (Sweden)

Moser Arvin

2012-02-01

Full Text Available Abstract Background One of the largest challenges in chemistry today remains that of efficiently mining through vast amounts of data in order to elucidate the chemical structure for an unknown compound. The elucidated candidate compound must be fully consistent with the data and any other competing candidates efficiently eliminated without doubt by using additional data if necessary. It has become increasingly necessary to incorporate an in silico structure generation and verification tool to facilitate this elucidation process. An effective structure elucidation software technology aims to mimic the skills of a human in interpreting the complex nature of spectral data while producing a solution within a reasonable amount of time. This type of software is known as computer-assisted structure elucidation or CASE software. A systematic trial of the ACD/Structure Elucidator CASE software was conducted over an extended period of time by analysing a set of single and double-blind trials submitted by a global audience of scientists. The purpose of the blind trials was to reduce subjective bias. Double-blind trials comprised of data where the candidate compound was unknown to both the submitting scientist and the analyst. The level of expertise of the submitting scientist ranged from novice to expert structure elucidation specialists with experience in pharmaceutical, industrial, government and academic environments. Results Beginning in 2003, and for the following nine years, the algorithms and software technology contained within ACD/Structure Elucidator have been tested against 112 data sets; many of these were unique challenges. Of these challenges 9% were double-blind trials. The results of eighteen of the single-blind trials were investigated in detail and included problems of a diverse nature with many of the specific challenges associated with algorithmic structure elucidation such as deficiency in protons, structure symmetry, a large number of

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.

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.

Diffusion-advection within dynamic biological gaps driven by structural motion

Science.gov (United States)

Asaro, Robert J.; Zhu, Qiang; Lin, Kuanpo

2018-04-01

To study the significance of advection in the transport of solutes, or particles, within thin biological gaps (channels), we examine theoretically the process driven by stochastic fluid flow caused by random thermal structural motion, and we compare it with transport via diffusion. The model geometry chosen resembles the synaptic cleft; this choice is motivated by the cleft's readily modeled structure, which allows for well-defined mechanical and physical features that control the advection process. Our analysis defines a Péclet-like number, AD, that quantifies the ratio of time scales of advection versus diffusion. Another parameter, AM, is also defined by the analysis that quantifies the full potential extent of advection in the absence of diffusion. These parameters provide a clear and compact description of the interplay among the well-defined structural, geometric, and physical properties vis-a ̀-vis the advection versus diffusion process. For example, it is found that AD˜1 /R2 , where R is the cleft diameter and hence diffusion distance. This curious, and perhaps unexpected, result follows from the dependence of structural motion that drives fluid flow on R . AM, on the other hand, is directly related (essentially proportional to) the energetic input into structural motion, and thereby to fluid flow, as well as to the mechanical stiffness of the cleftlike structure. Our model analysis thus provides unambiguous insight into the prospect of competition of advection versus diffusion within biological gaplike structures. The importance of the random, versus a regular, nature of structural motion and of the resulting transient nature of advection under random motion is made clear in our analysis. Further, by quantifying the effects of geometric and physical properties on the competition between advection and diffusion, our results clearly demonstrate the important role that metabolic energy (ATP) plays in this competitive process.

Structured Parallel Programming Patterns for Efficient Computation

CERN Document Server

McCool, Michael; Robison, Arch

2012-01-01

Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of th

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.

Computing the Partition Function for Kinetically Trapped RNA Secondary Structures

Science.gov (United States)

Lorenz, William A.; Clote, Peter

2011-01-01

An RNA secondary structure is locally optimal if there is no lower energy structure that can be obtained by the addition or removal of a single base pair, where energy is defined according to the widely accepted Turner nearest neighbor model. Locally optimal structures form kinetic traps, since any evolution away from a locally optimal structure must involve energetically unfavorable folding steps. Here, we present a novel, efficient algorithm to compute the partition function over all locally optimal secondary structures of a given RNA sequence. Our software, RNAlocopt runs in time and space. Additionally, RNAlocopt samples a user-specified number of structures from the Boltzmann subensemble of all locally optimal structures. We apply RNAlocopt to show that (1) the number of locally optimal structures is far fewer than the total number of structures – indeed, the number of locally optimal structures approximately equal to the square root of the number of all structures, (2) the structural diversity of this subensemble may be either similar to or quite different from the structural diversity of the entire Boltzmann ensemble, a situation that depends on the type of input RNA, (3) the (modified) maximum expected accuracy structure, computed by taking into account base pairing frequencies of locally optimal structures, is a more accurate prediction of the native structure than other current thermodynamics-based methods. The software RNAlocopt constitutes a technical breakthrough in our study of the folding landscape for RNA secondary structures. For the first time, locally optimal structures (kinetic traps in the Turner energy model) can be rapidly generated for long RNA sequences, previously impossible with methods that involved exhaustive enumeration. Use of locally optimal structure leads to state-of-the-art secondary structure prediction, as benchmarked against methods involving the computation of minimum free energy and of maximum expected accuracy. Web server

Computing the partition function for kinetically trapped RNA secondary structures.

Directory of Open Access Journals (Sweden)

William A Lorenz

Full Text Available An RNA secondary structure is locally optimal if there is no lower energy structure that can be obtained by the addition or removal of a single base pair, where energy is defined according to the widely accepted Turner nearest neighbor model. Locally optimal structures form kinetic traps, since any evolution away from a locally optimal structure must involve energetically unfavorable folding steps. Here, we present a novel, efficient algorithm to compute the partition function over all locally optimal secondary structures of a given RNA sequence. Our software, RNAlocopt runs in O(n3 time and O(n2 space. Additionally, RNAlocopt samples a user-specified number of structures from the Boltzmann subensemble of all locally optimal structures. We apply RNAlocopt to show that (1 the number of locally optimal structures is far fewer than the total number of structures--indeed, the number of locally optimal structures approximately equal to the square root of the number of all structures, (2 the structural diversity of this subensemble may be either similar to or quite different from the structural diversity of the entire Boltzmann ensemble, a situation that depends on the type of input RNA, (3 the (modified maximum expected accuracy structure, computed by taking into account base pairing frequencies of locally optimal structures, is a more accurate prediction of the native structure than other current thermodynamics-based methods. The software RNAlocopt constitutes a technical breakthrough in our study of the folding landscape for RNA secondary structures. For the first time, locally optimal structures (kinetic traps in the Turner energy model can be rapidly generated for long RNA sequences, previously impossible with methods that involved exhaustive enumeration. Use of locally optimal structure leads to state-of-the-art secondary structure prediction, as benchmarked against methods involving the computation of minimum free energy and of maximum expected

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

Assessment of uranium and selenium speciation in human and bacterial biological models to probe changes in their structural environment

International Nuclear Information System (INIS)

Avoscan, L.; Milgram, S.; Untereiner, G.; Collins, R.; Khodja, H.; Carriere, M.; Gouget, B.; Coves, J.; Hazemann, J.L.

2009-01-01

This study illustrates the potential of physicochemical techniques to speciate uranium (U) and selenium (Se) in biological samples. Speciation, defined he0re as the study of structural environment, of both toxic elements, was characterized at several levels in biological media and directly in human cells or bacteria once the metal(loid)s were internalized. External speciation that is extracellular speciation in culture media was predicted by thermodynamic equilibrium computer modelling using the JChess software and validated by spectroscopic measurements (XANES and EXAFS). Internal speciation that is intracellular speciation in eukaryotic and prokaryotic cells was studied in vitro with a soil bacterium Cupriavidus metallidurans CH34 and ROS 17/2.8 osteoblasts, human cells responsible for bone formation. XANES, EXAFS, HPLC-ICP-MS and SDS-PAGE coupled to particle induced X-ray emission (PIXE) permitted the identification and quantification of complexes formed with organic or inorganic molecules and/or larger proteins. (orig.)

Assessment of uranium and selenium speciation in human and bacterial biological models to probe changes in their structural environment

Energy Technology Data Exchange (ETDEWEB)

Avoscan, L.; Milgram, S.; Untereiner, G.; Collins, R.; Khodja, H.; Carriere, M.; Gouget, B. [Lab. Pierre Sue, CEA-CNRS UMR 9956, CEA/Saclay, Gif-sur-Yvette (France); Coves, J. [Inst. de Biologie Structurale - J.-P. Ebel, Lab. des Proteines Membranaires, Grenoble (France); Hazemann, J.L. [Lab. de Geophysique Interne et Tectonopbysique, UMR CNRS/Univ. Joseph Fourier, Saint-Martin-D' Heres (France)

2009-07-01

This study illustrates the potential of physicochemical techniques to speciate uranium (U) and selenium (Se) in biological samples. Speciation, defined he0re as the study of structural environment, of both toxic elements, was characterized at several levels in biological media and directly in human cells or bacteria once the metal(loid)s were internalized. External speciation that is extracellular speciation in culture media was predicted by thermodynamic equilibrium computer modelling using the JChess software and validated by spectroscopic measurements (XANES and EXAFS). Internal speciation that is intracellular speciation in eukaryotic and prokaryotic cells was studied in vitro with a soil bacterium Cupriavidus metallidurans CH34 and ROS 17/2.8 osteoblasts, human cells responsible for bone formation. XANES, EXAFS, HPLC-ICP-MS and SDS-PAGE coupled to particle induced X-ray emission (PIXE) permitted the identification and quantification of complexes formed with organic or inorganic molecules and/or larger proteins. (orig.)

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

Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis

Directory of Open Access Journals (Sweden)

Data Iranata

2010-05-01

Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.

The Diamond Light Source and the challenges ahead for structural biology: some informal remarks.

Science.gov (United States)

Ramakrishnan, V

2015-03-06

The remarkable advances in structural biology in the past three decades have led to the determination of increasingly complex structures that lie at the heart of many important biological processes. Many of these advances have been made possible by the use of X-ray crystallography using synchrotron radiation. In this short article, some of the challenges and prospects that lie ahead will be summarized. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

X-ray structure analyses of biological molecules and particles in Japan. A brief history and future prospect

International Nuclear Information System (INIS)

Nakasako, Masayoshi; Yamamoto, Masaki

2015-01-01

In Japan, X-ray structure analyses of molecules and particles from biology started in the 1970s. The structure analysis methods have been developed through the innovation of various techniques in advance, and have contributed for understanding the elementary and microscopic processes in life. Here we summarize briefly the history of X-ray structure analyses for structural biology in Japan and think about the prospect. (author)

ssbio: a Python framework for structural systems biology.

Science.gov (United States)

Mih, Nathan; Brunk, Elizabeth; Chen, Ke; Catoiu, Edward; Sastry, Anand; Kavvas, Erol; Monk, Jonathan M; Zhang, Zhen; Palsson, Bernhard O

2018-06-15

Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genome-scale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows. ssbio is implemented in Python and available to download under the MIT license at http://github.com/SBRG/ssbio. Documentation and Jupyter notebook tutorials are available at http://ssbio.readthedocs.io/en/latest/. Interactive notebooks can be launched using Binder at https://mybinder.org/v2/gh/SBRG/ssbio/master?filepath=Binder.ipynb. Supplementary data are available at Bioinformatics online.

Integrative structure modeling with the Integrative Modeling Platform.

Science.gov (United States)

Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

2018-01-01

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

The Widespread Prevalence and Functional Significance of Silk-Like Structural Proteins in Metazoan Biological Materials.

Directory of Open Access Journals (Sweden)

Carmel McDougall

Full Text Available In nature, numerous mechanisms have evolved by which organisms fabricate biological structures with an impressive array of physical characteristics. Some examples of metazoan biological materials include the highly elastic byssal threads by which bivalves attach themselves to rocks, biomineralized structures that form the skeletons of various animals, and spider silks that are renowned for their exceptional strength and elasticity. The remarkable properties of silks, which are perhaps the best studied biological materials, are the result of the highly repetitive, modular, and biased amino acid composition of the proteins that compose them. Interestingly, similar levels of modularity/repetitiveness and similar bias in amino acid compositions have been reported in proteins that are components of structural materials in other organisms, however the exact nature and extent of this similarity, and its functional and evolutionary relevance, is unknown. Here, we investigate this similarity and use sequence features common to silks and other known structural proteins to develop a bioinformatics-based method to identify similar proteins from large-scale transcriptome and whole-genome datasets. We show that a large number of proteins identified using this method have roles in biological material formation throughout the animal kingdom. Despite the similarity in sequence characteristics, most of the silk-like structural proteins (SLSPs identified in this study appear to have evolved independently and are restricted to a particular animal lineage. Although the exact function of many of these SLSPs is unknown, the apparent independent evolution of proteins with similar sequence characteristics in divergent lineages suggests that these features are important for the assembly of biological materials. The identification of these characteristics enable the generation of testable hypotheses regarding the mechanisms by which these proteins assemble and direct the

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

Science.gov (United States)

Kaski, K.; Salomaa, M.

1990-01-01

), physics (fluid-dynamical and quantum-mechanical calculations; extensive numerical simulations of various condensed-matter systems; the development of stellar constellations, even the early Universe), chemistry (quantum-chemical calculations on the structures of new chemical compounds; chemical reactions and reaction dynamics), and biology (various models, for example, in population dynamics). We succeeded in our effort to assemble several internationally recognized researchers of Computational Science to deliver invited talks on a couple of exceptionally beautiful late-summer days in the modern premises of the Adult Education Center at Lahti. Among the plenary speakers, Per Bak described his highly original work on self-organized criticality. David Ceperley discussed pioneering numerical simulations of superfluid helium in which, for the first time, Feynman's path-integral formulation of quantum mechanics has been implemented on a computer. Jim Gunton presented his comprehensive studies of the Cahn-Hilliard equation for the dynamics of ordering in a condensed-matter system far from equilibrium, while Alex Hansen explained those on nonlinear breakdown in disordered materials. Representing the important field of computational chemistry, Bo Jönsson dealt with attractive forces between polyelectrolytes. Kurt Kremer gave an interesting account on computer-simulation studies of complex polymer systems, while Ole Mouritsen reviewed studies of interfacial fluctuations in lipid membranes. Pekka Pyykkö introduced his pioneering work which has led to predictions of completely novel chemical species. Annette Zippelius gave an expert introduction to the highly active field of neural networks. It is evident from each of these intriguing plenary contributions that, indeed, the computational approach is a frontier field of science, possibly providing the most versatile research method available today. We also arranged a competition for the best Posters presented at the Symposium; the

Partitioned Fluid-Structure Interaction for Full Rotor Computations Using CFD

DEFF Research Database (Denmark)

Heinz, Joachim Christian

) based aerodynamic model which is computationally cheap but includes several limitations and corrections in order to account for three-dimensional and unsteady eects. The present work discusses the development of an aero-elastic simulation tool where high-fidelity computational fluid dynamics (CFD......) is used to model the aerodynamics of the flexible wind turbine rotor. Respective CFD computations are computationally expensive but do not show the limitations of the BEM-based models. It is one of the first times that high-fidelity fluid-structure interaction (FSI) simulations are used to model the aero......-elastic response of an entire wind turbine rotor. The work employs a partitioned FSI coupling between the multi-body-based structural model of the aero-elastic solver HAWC2 and the finite volume CFD solver EllipSys3D. In order to establish an FSI coupling of sufficient time accuracy and sufficient numerical...

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.

Nonpher: computational method for design of hard-to-synthesize structures

Czech Academy of Sciences Publication Activity Database

Voršilák, M.; Svozil, Daniel

2017-01-01

Roč. 9, březen (2017), č. článku 20. ISSN 1758-2946 R&D Projects: GA MŠk LO1220; GA MŠk LM2015063 Institutional support: RVO:68378050 Keywords : synthetic feasibility * molecular complexity * molecular morphing Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 4.220, year: 2016

Structure and biophysics

CERN Document Server

Puglisi, Joseph D

2007-01-01

This volume is a collection of articles from the proceedings of the ISSBMR 7th Course: Structure and Biophysics - New Technologies for Current Challenges in Biology and Beyond. This NATO Advanced Institute (ASI) was held in Erice at the Ettore Majorana Foundation and Centre for Scientific Culture on 22 June through 3 July 2005. The ASI brought together a diverse group of experts in the fields of Structural Biology, Biophysics and Physics. Prominent lecturers, from seven different countries, and students from around the world participated in the NATO ASI organized by Professors Joseph Puglisi (Stanford University, USA) and Alexander Arseniev (Moscow, RU). Advances in nuclear magnetic resonance spectroscopy (NMR) and x-ray crystallography have allowed the three-dimensional structures of many biological macromolecules and their complexes, including the ribosome and RNA polymerase to be solved. Fundamental principles of NMR spectroscopy and dynamics, x-ray crystallography, computation and experimental dynamics we...

Synthesis, crystal structure and biological activity of novel diester cyclophanes

International Nuclear Information System (INIS)

Zhang, Pengfei; Yang, Bingqin; Fang, Xianwen; Cheng, Zhao; Yang, Meipan

2012-01-01

A series of novel diester cyclophanes was synthesized by esterification of 1,2-benzenedicarbonyl chloride with eight different diols under high dilution conditions. The structures of the compounds were verified by elemental analysis, 1 H nuclear magnetic resonance (NMR), IR spectroscopy and high resolution mass spectrometry (HRMS). The crystal structures of two compounds were characterized by single crystal X-ray diffractometry (XRD). All the new cyclophanes were evaluated for biological activities and the results showed that some of these compounds have low antibacterial or antifungal activities (author)

2D neural hardware versus 3D biological ones

Energy Technology Data Exchange (ETDEWEB)

Beiu, V.

1998-12-31

This paper will present important limitations of hardware neural nets as opposed to biological neural nets (i.e. the real ones). The author starts by discussing neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural nets. Going further, the focus will be on hardware constraints. The author will present recent results for three different alternatives of implementing neural networks: digital, threshold gate, and analog, while the area and the delay will be related to neurons' fan-in and weights' precision. Based on all of these, it will be shown why hardware implementations cannot cope with their biological inspiration with respect to their power of computation: the mapping onto silicon lacking the third dimension of biological nets. This translates into reduced fan-in, and leads to reduced precision. The main conclusion is that one is faced with the following alternatives: (1) try to cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow one to use the third dimension, e.g. using optical interconnections.

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.

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.

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.

A combinatorial enumeration problem of RNA secondary structures

African Journals Online (AJOL)

use

2011-12-21

Dec 21, 2011 ... connection between Discrete Mathematics and Compu- tational Molecular Biology (Chen et al, 2005; Hofacker et ... in Computational Molecular Biology. An RNA molecule is described by its sequences of bases ... Here, a mathematical definition of secondary structure is given (Stein and Waterman 1978).

Neutron scattering and diffraction instrument for structural study on biology in Japan

Energy Technology Data Exchange (ETDEWEB)

Niimura, Nobuo [Japan Atomic Energy Research Inst., Ibaraki-ken (Japan)

1994-12-31

Neutron scattering and diffraction instruments in Japan which can be used for structural studies in biology are briefly introduced. Main specifications and general layouts of the instruments are shown.

Computational RNA secondary structure design: empirical complexity and improved methods

Directory of Open Access Journals (Sweden)

Condon Anne

2007-01-01

Full Text Available Abstract Background We investigate the empirical complexity of the RNA secondary structure design problem, that is, the scaling of the typical difficulty of the design task for various classes of RNA structures as the size of the target structure is increased. The purpose of this work is to understand better the factors that make RNA structures hard to design for existing, high-performance algorithms. Such understanding provides the basis for improving the performance of one of the best algorithms for this problem, RNA-SSD, and for characterising its limitations. Results To gain insights into the practical complexity of the problem, we present a scaling analysis on random and biologically motivated structures using an improved version of the RNA-SSD algorithm, and also the RNAinverse algorithm from the Vienna package. Since primary structure constraints are relevant for designing RNA structures, we also investigate the correlation between the number and the location of the primary structure constraints when designing structures and the performance of the RNA-SSD algorithm. The scaling analysis on random and biologically motivated structures supports the hypothesis that the running time of both algorithms scales polynomially with the size of the structure. We also found that the algorithms are in general faster when constraints are placed only on paired bases in the structure. Furthermore, we prove that, according to the standard thermodynamic model, for some structures that the RNA-SSD algorithm was unable to design, there exists no sequence whose minimum free energy structure is the target structure. Conclusion Our analysis helps to better understand the strengths and limitations of both the RNA-SSD and RNAinverse algorithms, and suggests ways in which the performance of these algorithms can be further improved.

A compilation of structural property data for computer impact calculation (1/5)

International Nuclear Information System (INIS)

Ikushima, Takeshi; Nagata, Norio.

1988-10-01

The paper describes structural property data for computer impact calculations of nuclear fuel shipping casks. Four kinds of material data, mild steel, stainless steel, lead and wood are compiled. These materials are main structural elements of shipping casks. Structural data such as, the coefficient of thermal expansion, the modulus of longitudinal elasticity, the modulus of transverse elasticity, the Poisson's ratio and stress and strain relationships, have been tabulated against temperature or strain rate. This volume 1 involve structural property data and data processing computer program. (author)

Biomolecular electrostatics and solvation: a computational perspective.

Science.gov (United States)

Ren, Pengyu; Chun, Jaehun; Thomas, Dennis G; Schnieders, Michael J; Marucho, Marcelo; Zhang, Jiajing; Baker, Nathan A

2012-11-01

An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

Advances in Computational Fluid-Structure Interaction and Flow Simulation Conference

CERN Document Server

Takizawa, Kenji

2016-01-01

This contributed volume celebrates the work of Tayfun E. Tezduyar on the occasion of his 60th birthday. The articles it contains were born out of the Advances in Computational Fluid-Structure Interaction and Flow Simulation (AFSI 2014) conference, also dedicated to Prof. Tezduyar and held at Waseda University in Tokyo, Japan on March 19-21, 2014. The contributing authors represent a group of international experts in the field who discuss recent trends and new directions in computational fluid dynamics (CFD) and fluid-structure interaction (FSI). Organized into seven distinct parts arranged by thematic topics, the papers included cover basic methods and applications of CFD, flows with moving boundaries and interfaces, phase-field modeling, computer science and high-performance computing (HPC) aspects of flow simulation, mathematical methods, biomedical applications, and FSI. Researchers, practitioners, and advanced graduate students working on CFD, FSI, and related topics will find this collection to be a defi...

Practice in multi-disciplinary computing. Transonic aero-structural dynamics of semi-monocoque wing

International Nuclear Information System (INIS)

Onishi, Ryoichi; Guo, Zhihong; Kimura, Toshiya; Iwamiya, Toshiyuki

2000-01-01

Japan Atomic Energy Research Institute is currently involved in expanding the application areas of its distributed parallel computing facility. One of the most anticipated areas of applications is multi-disciplinary interaction problem. This paper introduces the status quo of the system for fluid-structural interaction analysis on the institute's parallel computers by exploring multi-disciplinary engineering methodology. Current application is focused on a transonic aero-elastic analysis of a three dimensional wing. The distinctive features of the system are: (1) Simultaneous executions of fluid and structural codes by exploiting distributed-and-parallel processing technologies. (2) Construction of a computational fluid (aero)-structural dynamics model which combines flow-field grid with a wing structure composed of the external surface and the internal reinforcements. The purpose of this paper is to summarize the basic concepts, analytical methods, and their implementations along with the computed aero-structural properties of a swept-back wing at March, 7 flow condition. (author)

CyBy(2): a structure-based data management tool for chemical and biological data.

Science.gov (United States)

Höck, Stefan; Riedl, Rainer

2012-01-01

We report the development of a powerful data management tool for chemical and biological data: CyBy(2). CyBy(2) is a structure-based information management tool used to store and visualize structural data alongside additional information such as project assignment, physical information, spectroscopic data, biological activity, functional data and synthetic procedures. The application consists of a database, an application server, used to query and update the database, and a client application with a rich graphical user interface (GUI) used to interact with the server.

Parallel structures in human and computer memory

Science.gov (United States)

Kanerva, Pentti

1986-08-01

If we think of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library: We recognize a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. This paper is about how to construct a computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do. Such a memory is remarkably similar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. The paper concludes that the frame problem of artificial intelligence could be solved by the use of such a memory if we were able to encode information about the world properly.

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.

The potential for biological structure determination with pulsed neutrons

International Nuclear Information System (INIS)

Wilson, C.C.

1994-01-01

The potential of pulsed neutron diffraction in structural determination of biological materials is discussed. The problems and potential solutions in this area are outlined, with reference to both current and future sources and instrumentation. The importance of developing instrumentation on pulsed sources in emphasized, with reference to the likelihood of future expansion in this area. The possibilities and limitations of single crystal, fiber and powder diffraction in this area are assessed

The potential for biological structure determination with pulsed neutrons

Energy Technology Data Exchange (ETDEWEB)

Wilson, C.C. [CLRC Rutherford Appleton Laboratory, Chilton Didcot Oxon (United Kingdom)

1994-12-31

The potential of pulsed neutron diffraction in structural determination of biological materials is discussed. The problems and potential solutions in this area are outlined, with reference to both current and future sources and instrumentation. The importance of developing instrumentation on pulsed sources in emphasized, with reference to the likelihood of future expansion in this area. The possibilities and limitations of single crystal, fiber and powder diffraction in this area are assessed.

DFT computations of the lattice constant, stable atomic structure and ...

African Journals Online (AJOL)

This paper presents the most stable atomic structure and lattice constant of Fullerenes (C60). FHI-aims DFT code was used to predict the stable structure and the computational lattice constant of C60. These were compared with known experimental structures and lattice constants of C60. The results obtained showed that ...

Synthesis, crystal structure and biological activity of novel diester cyclophanes

Energy Technology Data Exchange (ETDEWEB)

Zhang, Pengfei; Yang, Bingqin; Fang, Xianwen; Cheng, Zhao; Yang, Meipan, E-mail: yangbq@nwu.edu.cn [Department of Chemistry, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry, Northwest University, Shaanxi (China)

2012-10-15

A series of novel diester cyclophanes was synthesized by esterification of 1,2-benzenedicarbonyl chloride with eight different diols under high dilution conditions. The structures of the compounds were verified by elemental analysis, {sup 1}H nuclear magnetic resonance (NMR), IR spectroscopy and high resolution mass spectrometry (HRMS). The crystal structures of two compounds were characterized by single crystal X-ray diffractometry (XRD). All the new cyclophanes were evaluated for biological activities and the results showed that some of these compounds have low antibacterial or antifungal activities (author)

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.

Using systems and structure biology tools to dissect cellular phenotypes.

Science.gov (United States)

Floratos, Aris; Honig, Barry; Pe'er, Dana; Califano, Andrea

2012-01-01

The Center for the Multiscale Analysis of Genetic Networks (MAGNet, http://magnet.c2b2.columbia.edu) was established in 2005, with the mission of providing the biomedical research community with Structural and Systems Biology algorithms and software tools for the dissection of molecular interactions and for the interaction-based elucidation of cellular phenotypes. Over the last 7 years, MAGNet investigators have developed many novel analysis methodologies, which have led to important biological discoveries, including understanding the role of the DNA shape in protein-DNA binding specificity and the discovery of genes causally related to the presentation of malignant phenotypes, including lymphoma, glioma, and melanoma. Software tools implementing these methodologies have been broadly adopted by the research community and are made freely available through geWorkbench, the Center's integrated analysis platform. Additionally, MAGNet has been instrumental in organizing and developing key conferences and meetings focused on the emerging field of systems biology and regulatory genomics, with special focus on cancer-related research.

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.

Teachers' Organization of Participation Structures for Teaching Science with Computer Technology

Science.gov (United States)

Subramaniam, Karthigeyan

2016-01-01

This paper describes a qualitative study that investigated the nature of the participation structures and how the participation structures were organized by four science teachers when they constructed and communicated science content in their classrooms with computer technology. Participation structures focus on the activity structures and…

Computational Lipidomics and Lipid Bioinformatics: Filling In the Blanks.

Science.gov (United States)

Pauling, Josch; Klipp, Edda

2016-12-22

Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolomics is a broad field under the omics umbrella that may also relate to lipids, lipidomics is an emerging field which specializes in the identification, quantification and functional interpretation of complex lipidomes. Today, it is possible to identify and distinguish lipids in a high-resolution, high-throughput manner and simultaneously with a lot of structural detail. However, doing so may produce thousands of mass spectra in a single experiment which has created a high demand for specialized computational support to analyze these spectral libraries. The computational biology and bioinformatics community has so far established methodology in genomics, transcriptomics and proteomics but there are many (combinatorial) challenges when it comes to structural diversity of lipids and their identification, quantification and interpretation. This review gives an overview and outlook on lipidomics research and illustrates ongoing computational and bioinformatics efforts. These efforts are important and necessary steps to advance the lipidomics field alongside analytic, biochemistry, biomedical and biology communities and to close the gap in available computational methodology between lipidomics and other omics sub-branches.

Computational simulation of acoustic fatigue for hot composite structures

Science.gov (United States)

Singhal, S. N.; Nagpal, V. K.; Murthy, P. L. N.; Chamis, C. C.