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

PubMed

Smolinski, Tomasz G

2010-01-01

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

India's Computational Biology Growth and Challenges.

PubMed

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Agoramoorthy, Govindasamy

2016-09-01

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

Management and Analysis of Biological and Clinical Data: How Computer Science May Support Biomedical and Clinical Research

NASA Astrophysics Data System (ADS)

Veltri, Pierangelo

The use of computer based solutions for data management in biology and clinical science has contributed to improve life-quality and also to gather research results in shorter time. Indeed, new algorithms and high performance computation have been using in proteomics and genomics studies for curing chronic diseases (e.g., drug designing) as well as supporting clinicians both in diagnosis (e.g., images-based diagnosis) and patient curing (e.g., computer based information analysis on information gathered from patient). In this paper we survey on examples of computer based techniques applied in both biology and clinical contexts. The reported applications are also results of experiences in real case applications at University Medical School of Catanzaro and also part of experiences of the National project Staywell SH 2.0 involving many research centers and companies aiming to study and improve citizen wellness.

Computational systems chemical biology.

PubMed

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

2011-01-01

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

Computational Systems Chemical Biology

PubMed Central

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

2013-01-01

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

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

PubMed

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.

Message from the ISCB: ISCB Ebola award for important future research on the computational biology of Ebola virus.

PubMed

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

2015-02-15

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 and three-dimensional 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$2000, at its July 2016 annual meeting (ISCB Intelligent Systems for Molecular Biology 2016, Orlando, FL). dkovats@iscb.org or rost@in.tum.de. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

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

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

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

Synthetic biology: insights into biological computation.

PubMed

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

2016-04-18

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

Computational biology for ageing

PubMed Central

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

DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wallace, Susan S.

2008-02-21

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

Data integration in biological research: an overview.

PubMed

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

2015-12-01

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

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

PubMed

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

2012-01-01

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

CSBB: synthetic biology research at Newcastle University.

PubMed

Goñi-Moreno, Angel; Wipat, Anil; Krasnogor, Natalio

2017-06-15

The Centre for Synthetic Biology and the Bioeconomy (CSBB) brings together a far-reaching multidisciplinary community across all Newcastle University's faculties - Medical Sciences, Science, Agriculture and Engineering, and Humanities, Arts and Social Sciences. The CSBB focuses on many different areas of Synthetic Biology, including bioprocessing, computational design and in vivo computation, as well as improving understanding of basic molecular machinery. Such breadth is supported by major national and international research funding, a range of industrial partners in the North East of England and beyond, as well as a large number of doctoral and post-doctoral researchers. The CSBB trains the next generation of scientists through a 1-year MSc in Synthetic Biology. © 2017 The Author(s).

Digital and biological computing in organizations.

PubMed

Kampfner, Roberto R

2002-01-01

Michael Conrad unveiled many of the fundamental characteristics of biological computing. Underlying the behavioral variability and the adaptability of biological systems are these characteristics, including the ability of biological information processing to exploit quantum features at the atomic level, the powerful 3-D pattern recognition capabilities of macromolecules, the computational efficiency, and the ability to support biological function. Among many other things, Conrad formalized and explicated the underlying principles of biological adaptability, characterized the differences between biological and digital computing in terms of a fundamental tradeoff between adaptability and programmability of information processing, and discussed the challenges of interfacing digital computers and human society. This paper is about the encounter of biological and digital computing. The focus is on the nature of the biological information processing infrastructure of organizations and how it can be extended effectively with digital computing. In order to achieve this goal effectively, however, we need to embed properly digital computing into the information processing aspects of human and social behavior and intelligence, which are fundamentally biological. Conrad's legacy provides a firm, strong, and inspiring foundation for this endeavor.

Ten quick tips for machine learning in computational biology.

PubMed

Chicco, Davide

2017-01-01

Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects. We believe our ten suggestions can strongly help any machine learning practitioner to carry on a successful project in computational biology and related sciences.

Designing integrated computational biology pipelines visually.

PubMed

Jamil, Hasan M

2013-01-01

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

Applicability of computational systems biology in toxicology.

PubMed

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

2014-07-01

Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search. However, computational systems biology offers more advantages than providing a high-throughput literature search; it may form the basis for establishment of hypotheses on potential links between environmental chemicals and human diseases, which would be very difficult to establish experimentally. This is possible due to the existence of comprehensive databases containing information on networks of human protein-protein interactions and protein-disease associations. Experimentally determined targets of the specific chemical of interest can be fed into these networks to obtain additional information that can be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method in the hypothesis-generating phase of toxicological research. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

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

PubMed Central

Anupama, Jigisha; Shanmugam, Avinash Kumar; Santos, Alberto; Michaut, Magali

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. PMID:29346365

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

PubMed

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.

Where next for the reproducibility agenda in computational biology?

PubMed

Lewis, Joanna; Breeze, Charles E; Charlesworth, Jane; Maclaren, Oliver J; Cooper, Jonathan

2016-07-15

The concept of reproducibility is a foundation of the scientific method. With the arrival of fast and powerful computers over the last few decades, there has been an explosion of results based on complex computational analyses and simulations. The reproducibility of these results has been addressed mainly in terms of exact replicability or numerical equivalence, ignoring the wider issue of the reproducibility of conclusions through equivalent, extended or alternative methods. We use case studies from our own research experience to illustrate how concepts of reproducibility might be applied in computational biology. Several fields have developed 'minimum information' checklists to support the full reporting of computational simulations, analyses and results, and standardised data formats and model description languages can facilitate the use of multiple systems to address the same research question. We note the importance of defining the key features of a result to be reproduced, and the expected agreement between original and subsequent results. Dynamic, updatable tools for publishing methods and results are becoming increasingly common, but sometimes come at the cost of clear communication. In general, the reproducibility of computational research is improving but would benefit from additional resources and incentives. We conclude with a series of linked recommendations for improving reproducibility in computational biology through communication, policy, education and research practice. More reproducible research will lead to higher quality conclusions, deeper understanding and more valuable knowledge.

Calibrated Peer Review for Computer-Assisted Learning of Biological Research Competencies

ERIC Educational Resources Information Center

Clase, Kari L.; Gundlach, Ellen; Pelaez, Nancy J.

2010-01-01

Recently, both science and technology faculty have been recognizing biological research competencies that are valued but rarely assessed. Some of these valued learning outcomes include scientific methods and thinking, critical assessment of primary papers, quantitative reasoning, communication, and putting biological research into a historical and…

Biological Basis For Computer Vision: Some Perspectives

NASA Astrophysics Data System (ADS)

Gupta, Madan M.

1990-03-01

Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

Advances in systems biology: computational algorithms and applications.

PubMed

Huang, Yufei; Zhao, Zhongming; Xu, Hua; Shyr, Yu; Zhang, Bing

2012-01-01

The 2012 International Conference on Intelligent Biology and Medicine (ICIBM 2012) was held on April 22-24, 2012 in Nashville, Tennessee, USA. The conference featured six technical sessions, one tutorial session, one workshop, and 3 keynote presentations that covered state-of-the-art research activities in genomics, systems biology, and intelligent computing. In addition to a major emphasis on the next generation sequencing (NGS)-driven informatics, ICIBM 2012 aligned significant interests in systems biology and its applications in medicine. We highlight in this editorial the selected papers from the meeting that address the developments of novel algorithms and applications in systems biology.

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

PubMed

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

2010-12-01

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

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

PubMed Central

2010-01-01

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

Filling the gap between biology and computer science

PubMed Central

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

2008-01-01

This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biological data. We outline the aims and scope of the journal, introduce the publishing model and describe the open peer review policy, which fosters interaction within the research community. PMID:18822148

Novel opportunities for computational biology and sociology in drug discovery☆

PubMed Central

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

2013-01-01

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

Novel opportunities for computational biology and sociology in drug discovery

PubMed Central

Yao, Lixia

2009-01-01

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

Perspectives on an education in computational biology and medicine.

PubMed

Rubinstein, Jill C

2012-09-01

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

P43-S Computational Biology Applications Suite for High-Performance Computing (BioHPC.net)

PubMed Central

Pillardy, J.

2007-01-01

One of the challenges of high-performance computing (HPC) is user accessibility. At the Cornell University Computational Biology Service Unit, which is also a Microsoft HPC institute, we have developed a computational biology application suite that allows researchers from biological laboratories to submit their jobs to the parallel cluster through an easy-to-use Web interface. Through this system, we are providing users with popular bioinformatics tools including BLAST, HMMER, InterproScan, and MrBayes. The system is flexible and can be easily customized to include other software. It is also scalable; the installation on our servers currently processes approximately 8500 job submissions per year, many of them requiring massively parallel computations. It also has a built-in user management system, which can limit software and/or database access to specified users. TAIR, the major database of the plant model organism Arabidopsis, and SGN, the international tomato genome database, are both using our system for storage and data analysis. The system consists of a Web server running the interface (ASP.NET C#), Microsoft SQL server (ADO.NET), compute cluster running Microsoft Windows, ftp server, and file server. Users can interact with their jobs and data via a Web browser, ftp, or e-mail. The interface is accessible at http://cbsuapps.tc.cornell.edu/.

Excellence in Computational Biology and Informatics — EDRN Public Portal

Cancer.gov

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

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

PubMed Central

Gu, Shuo

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. PMID:28690664

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

PubMed

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.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Computer Science Research Funding: How Much Is Too Little?

DTIC Science & Technology

2009-06-01

Bioinformatics Parallel computing Computational biology Principles of programming Computational neuroscience Real-time and embedded systems Scientific...National Security Agency ( NSA ) • Missile Defense Agency (MDA) and others The various research programs have been coordinated through the DDR&E...DOD funding included only DARPA and OSD programs. FY07 and FY08 PBR funding included DARPA, NSA , some of the Services’ basic and applied research

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

PubMed

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.

Computational Tools for Stem Cell Biology

PubMed Central

Bian, Qin; Cahan, Patrick

2016-01-01

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 last several years, a new sub-discipline 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. PMID:27318512

Computational Tools for Stem Cell Biology.

PubMed

Bian, Qin; Cahan, Patrick

2016-12-01

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

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

PubMed Central

Alford, Rebecca F.; Dolan, Erin L.

2017-01-01

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. PMID:29216185

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

PubMed

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.

Using Computer Technology to Create a Revolutionary New Style of Biology.

ERIC Educational Resources Information Center

Monaghan, Peter

1993-01-01

A $13-million gift of William Gates III to the University of Washington has enabled establishment of the country's first department in molecular biotechnology, a combination of medicine and molecular biology to be practiced by researchers versed in a variety of fields, including computer science, computation, applied physics, and engineering. (MSE)

Integrating interactive computational modeling in biology curricula.

PubMed

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

2015-03-01

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

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

PubMed Central

Moe-Behrens, Gerd HG

2013-01-01

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

Bringing Advanced Computational Techniques to Energy Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitchell, Julie C

2012-11-17

Please find attached our final technical report for the BACTER Institute award. BACTER was created as a graduate and postdoctoral training program for the advancement of computational biology applied to questions of relevance to bioenergy research.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Community-driven computational biology with Debian Linux.

PubMed

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.

Community-driven computational biology with Debian Linux

PubMed Central

2010-01-01

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

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

PubMed Central

2013-01-01

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

Bioconductor: open software development for computational biology and bioinformatics

PubMed Central

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

2004-01-01

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

Computational Skills for Biology Students

ERIC Educational Resources Information Center

Gross, Louis J.

2008-01-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

Textual data compression in computational biology: a synopsis.

PubMed

Giancarlo, Raffaele; Scaturro, Davide; Utro, Filippo

2009-07-01

Textual data compression, and the associated techniques coming from information theory, are often perceived as being of interest for data communication and storage. However, they are also deeply related to classification and data mining and analysis. In recent years, a substantial effort has been made for the application of textual data compression techniques to various computational biology tasks, ranging from storage and indexing of large datasets to comparison and reverse engineering of biological networks. The main focus of this review is on a systematic presentation of the key areas of bioinformatics and computational biology where compression has been used. When possible, a unifying organization of the main ideas and techniques is also provided. It goes without saying that most of the research results reviewed here offer software prototypes to the bioinformatics community. The Supplementary Material provides pointers to software and benchmark datasets for a range of applications of broad interest. In addition to provide reference to software, the Supplementary Material also gives a brief presentation of some fundamental results and techniques related to this paper. It is at: http://www.math.unipa.it/ approximately raffaele/suppMaterial/compReview/

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

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

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

2014-01-01

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

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

EPA Science Inventory

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

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

PubMed Central

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

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

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

PubMed

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

2012-01-01

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

Biomaterial science meets computational biology.

PubMed

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

2015-05-01

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

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

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

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

PubMed

Fong, Stephen S

2014-08-01

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

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

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.

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

PubMed

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.

The "Biologically-Inspired Computing" Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2007-01-01

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

Space biology research development

NASA Technical Reports Server (NTRS)

Bonting, Sjoerd L.

1993-01-01

The purpose of the Search for Extraterrestrial Intelligence (SETI) Institute is to conduct and promote research related activities regarding the search for extraterrestrial life, particularly intelligent life. Such research encompasses the broad discipline of 'Life in the Universe', including all scientific and technological aspects of astronomy and the planetary sciences, chemical evolution, the origin of life, biological evolution, and cultural evolution. The primary purpose was to provide funding for the Principal Investigator to collaborate with the personnel of the SETI Institute and the NASA-Ames Research center in order to plan and develop space biology research on and in connection with Space Station Freedom; to promote cooperation with the international partners in the space station; to conduct a study on the use of biosensors in space biology research and life support system operation; and to promote space biology research through the initiation of an annual publication 'Advances in Space Biology and Medicine'.

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

PubMed

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

2008-05-28

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

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

PubMed Central

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

2008-01-01

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

How to integrate biological research into society and exclude errors in biomedical publications? Progress in theoretical and systems biology releases pressure on experimental research.

PubMed

Volkov, Vadim

2014-01-01

This brief opinion proposes measures to increase efficiency and exclude errors in biomedical research under the existing dynamic situation. Rapid changes in biology began with the description of the three dimensional structure of DNA 60 years ago; today biology has progressed by interacting with computer science and nanoscience together with the introduction of robotic stations for the acquisition of large-scale arrays of data. These changes have had an increasing influence on the entire research and scientific community. Future advance demands short-term measures to ensure error-proof and efficient development. They can include the fast publishing of negative results, publishing detailed methodical papers and excluding a strict connection between career progression and publication activity, especially for younger researchers. Further development of theoretical and systems biology together with the use of multiple experimental methods for biological experiments could also be helpful in the context of years and decades. With regards to the links between science and society, it is reasonable to compare both these systems, to find and describe specific features for biology and to integrate it into the existing stream of social life and financial fluxes. It will increase the level of scientific research and have mutual positive effects for both biology and society. Several examples are given for further discussion.

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

PubMed Central

Navlakha, Saket; Bar-Joseph, Ziv

2011-01-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 previousmore » 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.« less

Computer Analogies: Teaching Molecular Biology and Ecology.

ERIC Educational Resources Information Center

Rice, Stanley; McArthur, John

2002-01-01

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

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

EPA Science Inventory

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

Integer Linear Programming in Computational Biology

NASA Astrophysics Data System (ADS)

Althaus, Ernst; Klau, Gunnar W.; Kohlbacher, Oliver; Lenhof, Hans-Peter; Reinert, Knut

Computational molecular biology (bioinformatics) is a young research field that is rich in NP-hard optimization problems. The problem instances encountered are often huge and comprise thousands of variables. Since their introduction into the field of bioinformatics in 1997, integer linear programming (ILP) techniques have been successfully applied to many optimization problems. These approaches have added much momentum to development and progress in related areas. In particular, ILP-based approaches have become a standard optimization technique in bioinformatics. In this review, we present applications of ILP-based techniques developed by members and former members of Kurt Mehlhorn’s group. These techniques were introduced to bioinformatics in a series of papers and popularized by demonstration of their effectiveness and potential.

Toward Computational Cumulative Biology by Combining Models of Biological Datasets

PubMed Central

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

2014-01-01

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

Toward computational cumulative biology by combining models of biological datasets.

PubMed

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.

Micro-Computers in Biology Inquiry.

ERIC Educational Resources Information Center

Barnato, Carolyn; Barrett, Kathy

1981-01-01

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

Incorporating computational resources in a cancer research program

PubMed Central

Woods, Nicholas T.; Jhuraney, Ankita; Monteiro, Alvaro N.A.

2015-01-01

Recent technological advances have transformed cancer genetics research. These advances have served as the basis for the generation of a number of richly annotated datasets relevant to the cancer geneticist. In addition, many of these technologies are now within reach of smaller laboratories to answer specific biological questions. Thus, one of the most pressing issues facing an experimental cancer biology research program in genetics is incorporating data from multiple sources to annotate, visualize, and analyze the system under study. Fortunately, there are several computational resources to aid in this process. However, a significant effort is required to adapt a molecular biology-based research program to take advantage of these datasets. Here, we discuss the lessons learned in our laboratory and share several recommendations to make this transition effectively. This article is not meant to be a comprehensive evaluation of all the available resources, but rather highlight those that we have incorporated into our laboratory and how to choose the most appropriate ones for your research program. PMID:25324189

International Conference in Computational Cell Biology: From the Past to the Future

DTIC Science & Technology

2016-09-12

24061 -0001 ABSTRACT Number of Papers published in peer -reviewed journals: Number of Papers published in non peer -reviewed journals: Final Report...present their latest research and discussed challenges in computational cell biology research and education. (a) Papers published in peer -reviewed...List the papers, including journal references, in the following categories: (b) Papers published in non- peer -reviewed journals (N/A for none) (c

Analog Computer Laboratory with Biological Examples.

ERIC Educational Resources Information Center

Strebel, Donald E.

1979-01-01

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

Computation of repetitions and regularities of biologically weighted sequences.

PubMed

Christodoulakis, M; Iliopoulos, C; Mouchard, L; Perdikuri, K; Tsakalidis, A; Tsichlas, K

2006-01-01

Biological weighted sequences are used extensively in molecular biology as profiles for protein families, in the representation of binding sites and often for the representation of sequences produced by a shotgun sequencing strategy. In this paper, we address three fundamental problems in the area of biologically weighted sequences: (i) computation of repetitions, (ii) pattern matching, and (iii) computation of regularities. Our algorithms can be used as basic building blocks for more sophisticated algorithms applied on weighted sequences.

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

ERIC Educational Resources Information Center

Callman, Joshua L.; And Others

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

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aderem, Alan; Adkins, Joshua N.; Ansong, Charles

The 20th century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and water borne illnesses are frequent, multi-drug resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the 21st century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondinglymore » deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program we think that the time is at hand to redefine the pathogen-host research paradigm.« less

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

PubMed Central

Aderem, Alan; Adkins, Joshua N.; Ansong, Charles; Galagan, James; Kaiser, Shari; Korth, Marcus J.; Law, G. Lynn; McDermott, Jason G.; Proll, Sean C.; Rosenberger, Carrie; Schoolnik, Gary; Katze, Michael G.

2011-01-01

The twentieth century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and waterborne illnesses are frequent, multidrug-resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the twenty-first century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program, we think that the time is at hand to redefine the pathogen-host research paradigm. PMID:21285433

AN OVERVIEW OF COMPUTATIONAL LIFE SCIENCE DATABASES & EXCHANGE FORMATS OF RELEVANCE TO CHEMICAL BIOLOGY RESEARCH

PubMed Central

Hall, Aaron Smalter; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2016-01-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities. PMID:22934944

An overview of computational life science databases & exchange formats of relevance to chemical biology research.

PubMed

Smalter Hall, Aaron; Shan, Yunfeng; Lushington, Gerald; Visvanathan, Mahesh

2013-03-01

Databases and exchange formats describing biological entities such as chemicals and proteins, along with their relationships, are a critical component of research in life sciences disciplines, including chemical biology wherein small information about small molecule properties converges with cellular and molecular biology. Databases for storing biological entities are growing not only in size, but also in type, with many similarities between them and often subtle differences. The data formats available to describe and exchange these entities are numerous as well. In general, each format is optimized for a particular purpose or database, and hence some understanding of these formats is required when choosing one for research purposes. This paper reviews a selection of different databases and data formats with the goal of summarizing their purposes, features, and limitations. Databases are reviewed under the categories of 1) protein interactions, 2) metabolic pathways, 3) chemical interactions, and 4) drug discovery. Representation formats will be discussed according to those describing chemical structures, and those describing genomic/proteomic entities.

HPC AND GRID COMPUTING FOR INTEGRATIVE BIOMEDICAL RESEARCH

PubMed Central

Kurc, Tahsin; Hastings, Shannon; Kumar, Vijay; Langella, Stephen; Sharma, Ashish; Pan, Tony; Oster, Scott; Ervin, David; Permar, Justin; Narayanan, Sivaramakrishnan; Gil, Yolanda; Deelman, Ewa; Hall, Mary; Saltz, Joel

2010-01-01

Integrative biomedical research projects query, analyze, and integrate many different data types and make use of datasets obtained from measurements or simulations of structure and function at multiple biological scales. With the increasing availability of high-throughput and high-resolution instruments, the integrative biomedical research imposes many challenging requirements on software middleware systems. In this paper, we look at some of these requirements using example research pattern templates. We then discuss how middleware systems, which incorporate Grid and high-performance computing, could be employed to address the requirements. PMID:20107625

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

PubMed

Kasson, Peter M

2013-01-01

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

Parallel computing in genomic research: advances and applications

PubMed Central

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today’s genomic experiments have to process the so-called “biological big data” that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. PMID:26604801

Parallel computing in genomic research: advances and applications.

PubMed

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

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

EPA Science Inventory

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

Computational optimization and biological evolution.

PubMed

Goryanin, Igor

2010-10-01

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

[Comparison study between biological vision and computer vision].

PubMed

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

2001-08-01

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

Biological Dual-Use Research and Synthetic Biology of Yeast.

PubMed

Cirigliano, Angela; Cenciarelli, Orlando; Malizia, Andrea; Bellecci, Carlo; Gaudio, Pasquale; Lioj, Michele; Rinaldi, Teresa

2017-04-01

In recent years, the publication of the studies on the transmissibility in mammals of the H5N1 influenza virus and synthetic genomes has triggered heated and concerned debate within the community of scientists on biological dual-use research; these papers have raised the awareness that, in some cases, fundamental research could be directed to harmful experiments, with the purpose of developing a weapon that could be used by a bioterrorist. Here is presented an overview regarding the dual-use concept and its related international agreements which underlines the work of the Australia Group (AG) Export Control Regime. It is hoped that the principles and activities of the AG, that focuses on export control of chemical and biological dual-use materials, will spread and become well known to academic researchers in different countries, as they exchange biological materials (i.e. plasmids, strains, antibodies, nucleic acids) and scientific papers. To this extent, and with the aim of drawing the attention of the scientific community that works with yeast to the so called Dual-Use Research of Concern, this article reports case studies on biological dual-use research and discusses a synthetic biology applied to the yeast Saccharomyces cerevisiae, namely the construction of the first eukaryotic synthetic chromosome of yeast and the use of yeast cells as a factory to produce opiates. Since this organism is considered harmless and is not included in any list of biological agents, yeast researchers should take simple actions in the future to avoid the sharing of strains and advanced technology with suspicious individuals.

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

PubMed

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

2007-02-01

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

Research | Computational Science | NREL

Science.gov Websites

Research Research NREL's computational science experts use advanced high-performance computing (HPC technologies, thereby accelerating the transformation of our nation's energy system. Enabling High-Impact Research NREL's computational science capabilities enable high-impact research. Some recent examples

Understanding sequence similarity and framework analysis between centromere proteins using computational biology.

PubMed

Doss, C George Priya; Chakrabarty, Chiranjib; Debajyoti, C; Debottam, S

2014-11-01

Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.

Biological data sciences in genome research

PubMed Central

Schatz, Michael C.

2015-01-01

The last 20 years have been a remarkable era for biology and medicine. One of the most significant achievements has been the sequencing of the first human genomes, which has laid the foundation for profound insights into human genetics, the intricacies of regulation and development, and the forces of evolution. Incredibly, as we look into the future over the next 20 years, we see the very real potential for sequencing more than 1 billion genomes, bringing even deeper insight into human genetics as well as the genetics of millions of other species on the planet. Realizing this great potential for medicine and biology, though, will only be achieved through the integration and development of highly scalable computational and quantitative approaches that can keep pace with the rapid improvements to biotechnology. In this perspective, I aim to chart out these future technologies, anticipate the major themes of research, and call out the challenges ahead. One of the largest shifts will be in the training used to prepare the class of 2035 for their highly interdisciplinary world. PMID:26430150

Teacher Perceptions of the Integration of Laptop Computers in Their High School Biology Classrooms

NASA Astrophysics Data System (ADS)

Gundy, Morag S.

2011-12-01

Studies indicate that teachers, and in particular science teachers in the senior high school grades, do not integrate laptop computers into their instruction to the extent anticipated by researchers. This technology has not spread easily to other teachers even with improved access to hardware and software, increased support, and a paradigm shift from teacher-centred to student-centred education. Although a number of studies have focused on the issues and problems related to the integration of laptops in classroom instruction, these studies, largely quantitative in nature, have tended to bypass the role teachers play in integrating laptop computers into their instruction. This thesis documents and describes the role of Ontario high school science teachers in the integration of laptop computers in the classroom. Ten teachers who have successfully integrated laptop computers into their biology courses participated in this descriptive study. Their perceptions of implementing laptops into their biology courses, key factors about the implementation process, and how the implementation was accomplished are examined. The study also identifies the conditions which they feel would allow this innovation to be implemented by other teachers. Key findings of the study indicate that teachers must initiate, implement and sustain an emergent and still evolving innovation; teacher perceptions change and continue to change with increased experience using laptops in the science classroom; changes in teaching approaches are significant as a result of the introduction of laptop technology; and, the teachers considered the acquisition and use of new teaching materials to be an important aspect of integrating laptop computers into instruction. Ongoing challenges for appropriate professional development, sharing of knowledge, skills and teaching materials are identified. The study provides a body of practical knowledge for biology teachers who are considering the integration of laptops into

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

PubMed Central

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

2013-01-01

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

Global Biology Research Program: Program plan

NASA Technical Reports Server (NTRS)

1983-01-01

Biological processes which play a dominant role in these cycles which transform and transfer much of this material throughout the biosphere are examined. A greater understanding of planetary biological processes as revealed by the interaction of the biota and the environment. The rationale, scope, research strategy, and research priorities of the global biology is presented.

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

PubMed

Eisenhaber, Frank; Sherman, Westley Arthur

2014-06-01

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

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP), Basic Science Program, HLA Immunogenetics Section, under the leadership of Dr. Mary Carrington, studies the influence of human leukocyte antigens (HLA) and specific KIR/HLA genotypes on risk of and outcomes to infection, cancer, autoimmune disease, and maternal-fetal disease. Recent studies have focused on the impact of HLA gene expression in disease, the molecular mechanism regulating expression levels, and the functional basis for the effect of differential expression on disease outcome. The lab’s further focus is on the genetic basis for resistance/susceptibility to disease conferred by immunogenetic variation. KEY ROLES/RESPONSIBILITIES The Senior Computational Scientist will provide research support to the CIP-BSP-HLA Immunogenetics Section performing bio-statistical design, analysis and reporting of research projects conducted in the lab. This individual will be involved in the implementation of statistical models and data preparation. Successful candidate should have 5 or more years of competent, innovative biostatistics/bioinformatics research experience, beyond doctoral training Considerable experience with statistical software, such as SAS, R and S-Plus Sound knowledge, and demonstrated experience of theoretical and applied statistics Write program code to analyze data using statistical analysis software Contribute to the interpretation and publication of research results

Common data manipulations with R in biological researches

PubMed Central

Liu, Qin

2017-01-01

R is a computer language and has been widely used in science community due to the powerful capability in data analysis and visualization; and these functions are mainly provided by the developed packages. Because every package has strict format definitions on the inputted data, it is always required to appropriately manipulate the original data in advance. Unfortunately, users, especially for the beginners, are always confused by the extreme flexibility with R in data manipulation. In the present paper, we roughly categorize the common manipulations with R for biological data into four classes, including overview of data, transformation, summarization, and reshaping. Subsequently, these manipulations are exemplified in a sample data of clinical records of diabetic patients. Our main purpose is to provide a better landscape on the data manipulation with R and hence facilitate the practical applications in biological researches. PMID:28840022

Computational Nanotechnology at NASA Ames Research Center, 1996

NASA Technical Reports Server (NTRS)

Globus, Al; Bailey, David; Langhoff, Steve; Pohorille, Andrew; Levit, Creon; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Some forms of nanotechnology appear to have enormous potential to improve aerospace and computer systems; computational nanotechnology, the design and simulation of programmable molecular machines, is crucial to progress. NASA Ames Research Center has begun a computational nanotechnology program including in-house work, external research grants, and grants of supercomputer time. Four goals have been established: (1) Simulate a hypothetical programmable molecular machine replicating itself and building other products. (2) Develop molecular manufacturing CAD (computer aided design) software and use it to design molecular manufacturing systems and products of aerospace interest, including computer components. (3) Characterize nanotechnologically accessible materials of aerospace interest. Such materials may have excellent strength and thermal properties. (4) Collaborate with experimentalists. Current in-house activities include: (1) Development of NanoDesign, software to design and simulate a nanotechnology based on functionalized fullerenes. Early work focuses on gears. (2) A design for high density atomically precise memory. (3) Design of nanotechnology systems based on biology. (4) Characterization of diamonoid mechanosynthetic pathways. (5) Studies of the laplacian of the electronic charge density to understand molecular structure and reactivity. (6) Studies of entropic effects during self-assembly. Characterization of properties of matter for clusters up to sizes exhibiting bulk properties. In addition, the NAS (NASA Advanced Supercomputing) supercomputer division sponsored a workshop on computational molecular nanotechnology on March 4-5, 1996 held at NASA Ames Research Center. Finally, collaborations with Bill Goddard at CalTech, Ralph Merkle at Xerox Parc, Don Brenner at NCSU (North Carolina State University), Tom McKendree at Hughes, and Todd Wipke at UCSC are underway.

Impact of Interdisciplinary Undergraduate Research in mathematics and biology on the development of a new course integrating five STEM disciplines.

PubMed

Caudill, Lester; Hill, April; Hoke, Kathy; Lipan, Ovidiu

2010-01-01

Funded by innovative programs at the National Science Foundation and the Howard Hughes Medical Institute, University of Richmond faculty in biology, chemistry, mathematics, physics, and computer science teamed up to offer first- and second-year students the opportunity to contribute to vibrant, interdisciplinary research projects. The result was not only good science but also good science that motivated and informed course development. Here, we describe four recent undergraduate research projects involving students and faculty in biology, physics, mathematics, and computer science and how each contributed in significant ways to the conception and implementation of our new Integrated Quantitative Science course, a course for first-year students that integrates the material in the first course of the major in each of biology, chemistry, mathematics, computer science, and physics.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

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

PubMed

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.

Encouraging Student Biological Research.

ERIC Educational Resources Information Center

Frame, Kathy, Ed.; Hays, Rachel, Ed.; Mack, Alison, Ed.

This publication encourages student involvement in biological research through student research with the cooperation of teachers and scientists. The contents of the book are divided into two sections. The first section introduces students to research investigations and includes: (1) "How the Investigations Are Set Up and the Rationale Behind…

Initiatives in biological research in Indian psychiatry

PubMed Central

Shrivatava, Amresh

2010-01-01

Biological psychiatry is an exploratory science for mental health. These biological changes provide some explicit insight into the complex area of ‘brain-mind and behavior’. One major achievement of research in biological field is the finding to explain how biological factors cause changes in behavior. In India, we have a clear history of initiatives in research from a biological perspective, which goes back to 1958. In the last 61 years, this field has seen significant evolution, precision and effective utilization of contemporary technological advances. It is a matter of great pride to see that in spite of difficult times in terms of challenges of practice and services, administration, resource, funding and manpower the zest for research was very forthcoming. There was neither dedicated time nor any funding for conducting research. It came from the intellectual insight of our fore fathers in the field of mental health to gradually grow to the state of strategic education in research, training in research, international research collaborations and setting up of internationally accredited centers. During difficult economic conditions in the past, the hypothesis tested and conclusions derived have not been so important. It is more important how it was done, how it was made possible and how robust traditions were established. Almost an entire spectrum of biological research has been touched upon by Indian researchers. Some of these are electroconvulsive therapy, biological markers, neurocognition, neuroimaging, neuroendocrine, neurochemistry, electrophysiology and genetics. A lot has been published given the limited space in the Indian Journal of Psychiatry and other medical journals published in India. A large body of biological research conducted on Indian patients has also been published in International literature (which I prefer to call non-Indian journals). Newer research questions in biological psychiatry, keeping with trend of international standards are

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-02-01

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

Connecting Biology and Organic Chemistry Introductory Laboratory Courses through a Collaborative Research Project

ERIC Educational Resources Information Center

Boltax, Ariana L.; Armanious, Stephanie; Kosinski-Collins, Melissa S.; Pontrello, Jason K.

2015-01-01

Modern research often requires collaboration of experts in fields, such as math, chemistry, biology, physics, and computer science to develop unique solutions to common problems. Traditional introductory undergraduate laboratory curricula in the sciences often do not emphasize connections possible between the various disciplines. We designed an…

Biological data sciences in genome research.

PubMed

Schatz, Michael C

2015-10-01

The last 20 years have been a remarkable era for biology and medicine. One of the most significant achievements has been the sequencing of the first human genomes, which has laid the foundation for profound insights into human genetics, the intricacies of regulation and development, and the forces of evolution. Incredibly, as we look into the future over the next 20 years, we see the very real potential for sequencing more than 1 billion genomes, bringing even deeper insight into human genetics as well as the genetics of millions of other species on the planet. Realizing this great potential for medicine and biology, though, will only be achieved through the integration and development of highly scalable computational and quantitative approaches that can keep pace with the rapid improvements to biotechnology. In this perspective, I aim to chart out these future technologies, anticipate the major themes of research, and call out the challenges ahead. One of the largest shifts will be in the training used to prepare the class of 2035 for their highly interdisciplinary world. © 2015 Schatz; Published by Cold Spring Harbor Laboratory Press.

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases.

PubMed

Oh, Soo Jin; Choi, Young Ki; Shin, Ok Sarah

2018-03-01

Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs. © Copyright: Yonsei University College of Medicine 2018.

Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases

PubMed Central

2018-01-01

Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs. PMID:29436184

Impact of Interdisciplinary Undergraduate Research in Mathematics and Biology on the Development of a New Course Integrating Five STEM Disciplines

PubMed Central

Caudill, Lester; Hill, April; Lipan, Ovidiu

2010-01-01

Funded by innovative programs at the National Science Foundation and the Howard Hughes Medical Institute, University of Richmond faculty in biology, chemistry, mathematics, physics, and computer science teamed up to offer first- and second-year students the opportunity to contribute to vibrant, interdisciplinary research projects. The result was not only good science but also good science that motivated and informed course development. Here, we describe four recent undergraduate research projects involving students and faculty in biology, physics, mathematics, and computer science and how each contributed in significant ways to the conception and implementation of our new Integrated Quantitative Science course, a course for first-year students that integrates the material in the first course of the major in each of biology, chemistry, mathematics, computer science, and physics. PMID:20810953

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

James, Conrad D.; Schiess, Adrian B.; Howell, Jamie

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 willmore » 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.« less

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

PubMed

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

2013-12-01

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

OpenStructure: a flexible software framework for computational structural biology.

PubMed

Biasini, Marco; Mariani, Valerio; Haas, Jürgen; Scheuber, Stefan; Schenk, Andreas D; Schwede, Torsten; Philippsen, Ansgar

2010-10-15

Developers of new methods in computational structural biology are often hampered in their research by incompatible software tools and non-standardized data formats. To address this problem, we have developed OpenStructure as a modular open source platform to provide a powerful, yet flexible general working environment for structural bioinformatics. OpenStructure consists primarily of a set of libraries written in C++ with a cleanly designed application programmer interface. All functionality can be accessed directly in C++ or in a Python layer, meeting both the requirements for high efficiency and ease of use. Powerful selection queries and the notion of entity views to represent these selections greatly facilitate the development and implementation of algorithms on structural data. The modular integration of computational core methods with powerful visualization tools makes OpenStructure an ideal working and development environment. Several applications, such as the latest versions of IPLT and QMean, have been implemented based on OpenStructure-demonstrating its value for the development of next-generation structural biology algorithms. Source code licensed under the GNU lesser general public license and binaries for MacOS X, Linux and Windows are available for download at http://www.openstructure.org. torsten.schwede@unibas.ch Supplementary data are available at Bioinformatics online.

Computational knowledge integration in biopharmaceutical research.

PubMed

Ficenec, David; Osborne, Mark; Pradines, Joel; Richards, Dan; Felciano, Ramon; Cho, Raymond J; Chen, Richard O; Liefeld, Ted; Owen, James; Ruttenberg, Alan; Reich, Christian; Horvath, Joseph; Clark, Tim

2003-09-01

An initiative to increase biopharmaceutical research productivity by capturing, sharing and computationally integrating proprietary scientific discoveries with public knowledge is described. This initiative involves both organisational process change and multiple interoperating software systems. The software components rely on mutually supporting integration techniques. These include a richly structured ontology, statistical analysis of experimental data against stored conclusions, natural language processing of public literature, secure document repositories with lightweight metadata, web services integration, enterprise web portals and relational databases. This approach has already begun to increase scientific productivity in our enterprise by creating an organisational memory (OM) of internal research findings, accessible on the web. Through bringing together these components it has also been possible to construct a very large and expanding repository of biological pathway information linked to this repository of findings which is extremely useful in analysis of DNA microarray data. This repository, in turn, enables our research paradigm to be shifted towards more comprehensive systems-based understandings of drug action.

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

ERIC Educational Resources Information Center

Hasenekoglu, Ismet; Timucin, Melih

2007-01-01

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

NASA's computer science research program

NASA Technical Reports Server (NTRS)

Larsen, R. L.

1983-01-01

Following a major assessment of NASA's computing technology needs, a new program of computer science research has been initiated by the Agency. The program includes work in concurrent processing, management of large scale scientific databases, software engineering, reliable computing, and artificial intelligence. The program is driven by applications requirements in computational fluid dynamics, image processing, sensor data management, real-time mission control and autonomous systems. It consists of university research, in-house NASA research, and NASA's Research Institute for Advanced Computer Science (RIACS) and Institute for Computer Applications in Science and Engineering (ICASE). The overall goal is to provide the technical foundation within NASA to exploit advancing computing technology in aerospace applications.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tavare, S.

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

Distributed and grid computing projects with research focus in human health.

PubMed

Diomidous, Marianna; Zikos, Dimitrios

2012-01-01

Distributed systems and grid computing systems are used to connect several computers to obtain a higher level of performance, in order to solve a problem. During the last decade, projects use the World Wide Web to aggregate individuals' CPU power for research purposes. This paper presents the existing active large scale distributed and grid computing projects with research focus in human health. There have been found and presented 11 active projects with more than 2000 Processing Units (PUs) each. The research focus for most of them is molecular biology and, specifically on understanding or predicting protein structure through simulation, comparing proteins, genomic analysis for disease provoking genes and drug design. Though not in all cases explicitly stated, common target diseases include research to find cure against HIV, dengue, Duchene dystrophy, Parkinson's disease, various types of cancer and influenza. Other diseases include malaria, anthrax, Alzheimer's disease. The need for national initiatives and European Collaboration for larger scale projects is stressed, to raise the awareness of citizens to participate in order to create a culture of internet volunteering altruism.

Center for Computing Research Summer Research Proceedings 2015.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, Andrew Michael; Parks, Michael L.

2015-12-18

The Center for Computing Research (CCR) at Sandia National Laboratories organizes a summer student program each summer, in coordination with the Computer Science Research Institute (CSRI) and Cyber Engineering Research Institute (CERI).

Biological and Environmental Research Network Requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balaji, V.; Boden, Tom; Cowley, Dave

2013-09-01

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet be a highly successful enabler of scientific discovery for over 25 years. In November 2012, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organizedmore » a review to characterize the networking requirements of the programs funded by the BER program office. Several key findings resulted from the review. Among them: 1) The scale of data sets available to science collaborations continues to increase exponentially. This has broad impact, both on the network and on the computational and storage systems connected to the network. 2) Many science collaborations require assistance to cope with the systems and network engineering challenges inherent in managing the rapid growth in data scale. 3) Several science domains operate distributed facilities that rely on high-performance networking for success. Key examples illustrated in this report include the Earth System Grid Federation (ESGF) and the Systems Biology Knowledgebase (KBase). This report expands on these points, and addresses others as well. The report contains a findings section as well as the text of the case studies discussed at the review.« less

Synthetic biology: An emerging research field in China

PubMed Central

Pei, Lei; Schmidt, Markus; Wei, Wei

2011-01-01

Synthetic biology is considered as an emerging research field that will bring new opportunities to biotechnology. There is an expectation that synthetic biology will not only enhance knowledge in basic science, but will also have great potential for practical applications. Synthetic biology is still in an early developmental stage in China. We provide here a review of current Chinese research activities in synthetic biology and its different subfields, such as research on genetic circuits, minimal genomes, chemical synthetic biology, protocells and DNA synthesis, using literature reviews and personal communications with Chinese researchers. To meet the increasing demand for a sustainable development, research on genetic circuits to harness biomass is the most pursed research within Chinese researchers. The environmental concerns are driven force of research on the genetic circuits for bioremediation. The research on minimal genomes is carried on identifying the smallest number of genomes needed for engineering minimal cell factories and research on chemical synthetic biology is focused on artificial proteins and expanded genetic code. The research on protocells is more in combination with the research on molecular-scale motors. The research on DNA synthesis and its commercialisation are also reviewed. As for the perspective on potential future Chinese R&D activities, it will be discussed based on the research capacity and governmental policy. PMID:21729747

Deep learning for computational biology.

PubMed

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

2016-07-29

Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new technology. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

pClone: Synthetic Biology Tool Makes Promoter Research Accessible to Beginning Biology Students

ERIC Educational Resources Information Center

Campbell, A. Malcolm; Eckdahl, Todd; Cronk, Brian; Andresen, Corinne; Frederick, Paul; Huckuntod, Samantha; Shinneman, Claire; Wacker, Annie; Yuan, Jason

2014-01-01

The "Vision and Change" report recommended genuine research experiences for undergraduate biology students. Authentic research improves science education, increases the number of scientifically literate citizens, and encourages students to pursue research. Synthetic biology is well suited for undergraduate research and is a growing area…

Research Techniques Made Simple: Bioinformatics for Genome-Scale Biology.

PubMed

Foulkes, Amy C; Watson, David S; Griffiths, Christopher E M; Warren, Richard B; Huber, Wolfgang; Barnes, Michael R

2017-09-01

High-throughput biology presents unique opportunities and challenges for dermatological research. Drawing on a small handful of exemplary studies, we review some of the major lessons of these new technologies. We caution against several common errors and introduce helpful statistical concepts that may be unfamiliar to researchers without experience in bioinformatics. We recommend specific software tools that can aid dermatologists at varying levels of computational literacy, including platforms with command line and graphical user interfaces. The future of dermatology lies in integrative research, in which clinicians, laboratory scientists, and data analysts come together to plan, execute, and publish their work in open forums that promote critical discussion and reproducibility. In this article, we offer guidelines that we hope will steer researchers toward best practices for this new and dynamic era of data intensive dermatology. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

78 FR 6087 - Biological and Environmental Research Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-29

... Biological and Environmental Research News from the Biological Systems Science and Climate and Environmental... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Office of... the Biological and Environmental Research Advisory Committee (BERAC). The Federal Advisory Committee...

Division of Biological and Medical Research research summary 1984-1985

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barr, S.H.

1985-08-01

The Division of Biological and Medical Research at Argonne National Laboratory conducts multidisciplinary research aimed at defining the biological and medical hazards to man from energy technologies and new energy options. These technically oriented studies have a strong base in fundamental research in a variety of scientific disciplines, including molecular and cellular biology, biophysics, genetics, radiobiology, pharmacology, biochemistry, chemistry, environmental toxicology, and epidemiology. This research summary is organized into six parts. The first five parts reflect the Divisional structure and contain the scientific program chapters, which summarize the activities of the individual groups during the calendar year 1984 and themore » first half of 1985. To provide better continuity and perspective, previous work is sometimes briefly described. Although the summaries are short, efforts have been made to indicate the range of research activities for each group.« less

78 FR 34088 - Biological and Environmental Research Advisory Committee

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2013-06-06

... Report from the Office of Biological and Environmental Research News from the Biological Systems Science... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Office of... the Biological and Environmental Research Advisory Committee (BERAC). The Federal Advisory Committee...

77 FR 4028 - Biological and Environmental Research Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-26

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76 FR 8357 - Biological and Environmental Research Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-14

... Report from the Office of Biological and Environmental Research News from the Biological Systems Science... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Department... announces a meeting of the Biological and Environmental Research Advisory Committee (BERAC). The Federal...

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 tomore » make use of the new data.3« less

Computer-aided design of biological circuits using TinkerCell.

PubMed

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

Computer-aided design of biological circuits using TinkerCell

PubMed Central

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. PMID:21327060

A new online computational biology curriculum.

PubMed

Searls, David B

2014-06-01

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

Tumor Biology and Microenvironment Research

Cancer.gov

Part of NCI's Division of Cancer Biology's research portfolio, research in this area seeks to understand the role of tumor cells and the tumor microenvironment (TME) in driving cancer initiation, progression, maintenance and recurrence.

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

NASA Astrophysics Data System (ADS)

Marco, S.; Gutierrez-Gálvez, A.

2009-05-01

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

Revision history aware repositories of computational models of biological systems.

PubMed

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

Biological Visualization, Imaging and Simulation(Bio-VIS) at NASA Ames Research Center: Developing New Software and Technology for Astronaut Training and Biology Research in Space

NASA Technical Reports Server (NTRS)

Smith, Jeffrey

2003-01-01

The Bio- Visualization, Imaging and Simulation (BioVIS) Technology Center at NASA's Ames Research Center is dedicated to developing and applying advanced visualization, computation and simulation technologies to support NASA Space Life Sciences research and the objectives of the Fundamental Biology Program. Research ranges from high resolution 3D cell imaging and structure analysis, virtual environment simulation of fine sensory-motor tasks, computational neuroscience and biophysics to biomedical/clinical applications. Computer simulation research focuses on the development of advanced computational tools for astronaut training and education. Virtual Reality (VR) and Virtual Environment (VE) simulation systems have become important training tools in many fields from flight simulation to, more recently, surgical simulation. The type and quality of training provided by these computer-based tools ranges widely, but the value of real-time VE computer simulation as a method of preparing individuals for real-world tasks is well established. Astronauts routinely use VE systems for various training tasks, including Space Shuttle landings, robot arm manipulations and extravehicular activities (space walks). Currently, there are no VE systems to train astronauts for basic and applied research experiments which are an important part of many missions. The Virtual Glovebox (VGX) is a prototype VE system for real-time physically-based simulation of the Life Sciences Glovebox where astronauts will perform many complex tasks supporting research experiments aboard the International Space Station. The VGX consists of a physical display system utilizing duel LCD projectors and circular polarization to produce a desktop-sized 3D virtual workspace. Physically-based modeling tools (Arachi Inc.) provide real-time collision detection, rigid body dynamics, physical properties and force-based controls for objects. The human-computer interface consists of two magnetic tracking devices

Accelerating cancer systems biology research through Semantic Web technology.

PubMed

Wang, Zhihui; Sagotsky, Jonathan; Taylor, Thomas; Shironoshita, Patrick; Deisboeck, Thomas S

2013-01-01

Cancer systems biology is an interdisciplinary, rapidly expanding research field in which collaborations are a critical means to advance the field. Yet the prevalent database technologies often isolate data rather than making it easily accessible. The Semantic Web has the potential to help facilitate web-based collaborative cancer research by presenting data in a manner that is self-descriptive, human and machine readable, and easily sharable. We have created a semantically linked online Digital Model Repository (DMR) for storing, managing, executing, annotating, and sharing computational cancer models. Within the DMR, distributed, multidisciplinary, and inter-organizational teams can collaborate on projects, without forfeiting intellectual property. This is achieved by the introduction of a new stakeholder to the collaboration workflow, the institutional licensing officer, part of the Technology Transfer Office. Furthermore, the DMR has achieved silver level compatibility with the National Cancer Institute's caBIG, so users can interact with the DMR not only through a web browser but also through a semantically annotated and secure web service. We also discuss the technology behind the DMR leveraging the Semantic Web, ontologies, and grid computing to provide secure inter-institutional collaboration on cancer modeling projects, online grid-based execution of shared models, and the collaboration workflow protecting researchers' intellectual property. Copyright © 2012 Wiley Periodicals, Inc.

Dispensing Processes Impact Apparent Biological Activity as Determined by Computational and Statistical Analyses

PubMed Central

Ekins, Sean; Olechno, Joe; Williams, Antony J.

2013-01-01

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. PMID:23658723

Connecting biology and organic chemistry introductory laboratory courses through a collaborative research project.

PubMed

Boltax, Ariana L; Armanious, Stephanie; Kosinski-Collins, Melissa S; Pontrello, Jason K

2015-01-01

Modern research often requires collaboration of experts in fields, such as math, chemistry, biology, physics, and computer science to develop unique solutions to common problems. Traditional introductory undergraduate laboratory curricula in the sciences often do not emphasize connections possible between the various disciplines. We designed an interdisciplinary, medically relevant, project intended to help students see connections between chemistry and biology. Second term organic chemistry laboratory students designed and synthesized potential polymer inhibitors or inducers of polyglutamine protein aggregation. The use of novel target compounds added the uncertainty of scientific research to the project. Biology laboratory students then tested the novel potential pharmaceuticals in Huntington's disease model assays, using in vitro polyglutamine peptide aggregation and in vivo lethality studies in Drosophila. Students read articles from the primary literature describing the system from both chemical and biological perspectives. Assessment revealed that students emerged from both courses with a deeper understanding of the interdisciplinary nature of biology and chemistry and a heightened interest in basic research. The design of this collaborative project for introductory biology and organic chemistry labs demonstrated how the local interests and expertise at a university can be drawn from to create an effective way to integrate these introductory courses. Rather than simply presenting a series of experiments to be replicated, we hope that our efforts will inspire other scientists to think about how some aspect of authentic work can be brought into their own courses, and we also welcome additional collaborations to extend the scope of the scientific exploration. © 2015 The International Union of Biochemistry and Molecular Biology.

Has Modern Biology Entered the Mouth? The Clinical Impact of Biological Research.

ERIC Educational Resources Information Center

Baum, Bruce J.

1991-01-01

Three areas of biological research that are beginning to have an impact on clinical medicine are examined, including molecular biology, cell biology, and biotechnology. It is concluded that oral biologists and educators must work cooperatively to bring rapid biological and biomedical advances into dental training in a meaningful way. (MSE)

Computational intelligence approaches for pattern discovery in biological systems.

PubMed

Fogel, Gary B

2008-07-01

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

Plant biology research and training for the 21st century

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, K.

1992-12-31

The committee was assembled in response to a request from the National Science Foundation (NSF), the US Department of Agriculture (USDA), and the US Department of Energy (DoE). The leadership of these agencies asked the National Academy of Sciences through the National Research Council (NRC) to assess the status of plant-science research in the United States in light of the opportunities arising from advances inother areas of biology. NRC was asked to suggest ways of accelerating the application of these new biologic concepts and tools to research in plant science with the aim of enhancing the acquisition of new knowledgemore » about plants. The charge to the committee was to examine the following: Organizations, departments, and institutions conducting plant biology research; human resources involved in plant biology research; graduate training programs in plant biology; federal, state, and private sources of support for plant-biology research; the role of industry in conducting and supporting plant-biology research; the international status of US plant-biology research; and the relationship of plant biology to leading-edge research in biology.« less

Plant biology research and training for the 21st century

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, K.

1992-01-01

The committee was assembled in response to a request from the National Science Foundation (NSF), the US Department of Agriculture (USDA), and the US Department of Energy (DoE). The leadership of these agencies asked the National Academy of Sciences through the National Research Council (NRC) to assess the status of plant-science research in the United States in light of the opportunities arising from advances inother areas of biology. NRC was asked to suggest ways of accelerating the application of these new biologic concepts and tools to research in plant science with the aim of enhancing the acquisition of new knowledgemore » about plants. The charge to the committee was to examine the following: Organizations, departments, and institutions conducting plant biology research; human resources involved in plant biology research; graduate training programs in plant biology; federal, state, and private sources of support for plant-biology research; the role of industry in conducting and supporting plant-biology research; the international status of US plant-biology research; and the relationship of plant biology to leading-edge research in biology.« less

openBIS: a flexible framework for managing and analyzing complex data in biology research

PubMed Central

2011-01-01

Background Modern data generation techniques used in distributed systems biology research projects often create datasets of enormous size and diversity. We argue that in order to overcome the challenge of managing those large quantitative datasets and maximise the biological information extracted from them, a sound information system is required. Ease of integration with data analysis pipelines and other computational tools is a key requirement for it. Results We have developed openBIS, an open source software framework for constructing user-friendly, scalable and powerful information systems for data and metadata acquired in biological experiments. openBIS enables users to collect, integrate, share, publish data and to connect to data processing pipelines. This framework can be extended and has been customized for different data types acquired by a range of technologies. Conclusions openBIS is currently being used by several SystemsX.ch and EU projects applying mass spectrometric measurements of metabolites and proteins, High Content Screening, or Next Generation Sequencing technologies. The attributes that make it interesting to a large research community involved in systems biology projects include versatility, simplicity in deployment, scalability to very large data, flexibility to handle any biological data type and extensibility to the needs of any research domain. PMID:22151573

Structural Biology and Molecular Applications Research

Cancer.gov

Part of NCI's Division of Cancer Biology's research portfolio, research and development in this area focuses on enabling technologies, models, and methodologies to support basic and applied cancer research.

Computational Tools to Assess Turbine Biological Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richmond, Marshall C.; Serkowski, John A.; Rakowski, Cynthia L.

2014-07-24

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

Biologically Inspired Micro-Flight Research

NASA Technical Reports Server (NTRS)

Raney, David L.; Waszak, Martin R.

2003-01-01

Natural fliers demonstrate a diverse array of flight capabilities, many of which are poorly understood. NASA has established a research project to explore and exploit flight technologies inspired by biological systems. One part of this project focuses on dynamic modeling and control of micro aerial vehicles that incorporate flexible wing structures inspired by natural fliers such as insects, hummingbirds and bats. With a vast number of potential civil and military applications, micro aerial vehicles represent an emerging sector of the aerospace market. This paper describes an ongoing research activity in which mechanization and control concepts for biologically inspired micro aerial vehicles are being explored. Research activities focusing on a flexible fixed- wing micro aerial vehicle design and a flapping-based micro aerial vehicle concept are presented.

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

PubMed

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.

Using computer algebra and SMT solvers in algebraic biology

NASA Astrophysics Data System (ADS)

Pineda Osorio, Mateo

2014-05-01

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

76 FR 57028 - Biological and Environmental Research Advisory Committee

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2011-09-15

... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Department... announces a meeting of the Biological and Environmental Research Advisory Committee (BERAC). The Federal... Biological and Environmental Research, SC-23/Germantown Building, 1000 Independence Avenue, SW., Washington...

77 FR 55201 - Biological and Environmental Research Advisory Committee

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2012-09-07

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2013-02-21

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2012-05-14

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2010-09-01

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2010-02-10

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76 FR 31319 - Biological and Environmental Research Advisory Committee

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2011-05-31

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A design automation framework for computational bioenergetics in biological networks.

PubMed

Angione, Claudio; Costanza, Jole; Carapezza, Giovanni; Lió, Pietro; Nicosia, Giuseppe

2013-10-01

The bioenergetic activity of mitochondria can be thoroughly investigated by using computational methods. In particular, in our work we focus on ATP and NADH, namely the metabolites representing the production of energy in the cell. We develop a computational framework to perform an exhaustive investigation at the level of species, reactions, genes and metabolic pathways. The framework integrates several methods implementing the state-of-the-art algorithms for many-objective optimization, sensitivity, and identifiability analysis applied to biological systems. We use this computational framework to analyze three case studies related to the human mitochondria and the algal metabolism of Chlamydomonas reinhardtii, formally described with algebraic differential equations or flux balance analysis. Integrating the results of our framework applied to interacting organelles would provide a general-purpose method for assessing the production of energy in a biological network.

76 FR 78908 - Biological and Environmental Research Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-20

... hereby given that the Biological and Environmental Research Advisory Committee will be renewed for a two... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Office of Science, Department of Energy. ACTION: Notice of renewal of the Biological and Environmental Research...

Computer Science Research at Langley

NASA Technical Reports Server (NTRS)

Voigt, S. J. (Editor)

1982-01-01

A workshop was held at Langley Research Center, November 2-5, 1981, to highlight ongoing computer science research at Langley and to identify additional areas of research based upon the computer user requirements. A panel discussion was held in each of nine application areas, and these are summarized in the proceedings. Slides presented by the invited speakers are also included. A survey of scientific, business, data reduction, and microprocessor computer users helped identify areas of focus for the workshop. Several areas of computer science which are of most concern to the Langley computer users were identified during the workshop discussions. These include graphics, distributed processing, programmer support systems and tools, database management, and numerical methods.

Using a Computer Animation to Teach High School Molecular Biology

ERIC Educational Resources Information Center

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

2008-01-01

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

Systems Biology in Immunology – A Computational Modeling Perspective

PubMed Central

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

2011-01-01

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

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

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

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

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

ERIC Educational Resources Information Center

Anxolabehere, D.; And Others

1980-01-01

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

Space Station Biological Research Project.

PubMed

Johnson, C C; Wade, C E; Givens, J J

1997-06-01

To meet NASA's objective of using the unique aspects of the space environment to expand fundamental knowledge in the biological sciences, the Space Station Biological Research Project at Ames Research Center is developing, or providing oversight, for two major suites of hardware which will be installed on the International Space Station (ISS). The first, the Gravitational Biology Facility, consists of Habitats to support plants, rodents, cells, aquatic specimens, avian and reptilian eggs, and insects and the Habitat Holding Rack in which to house them at microgravity; the second, the Centrifuge Facility, consists of a 2.5 m diameter centrifuge that will provide acceleration levels between 0.01 g and 2.0 g and a Life Sciences Glovebox. These two facilities will support the conduct of experiments to: 1) investigate the effect of microgravity on living systems; 2) what level of gravity is required to maintain normal form and function, and 3) study the use of artificial gravity as a countermeasure to the deleterious effects of microgravity observed in the crew. Upon completion, the ISS will have three complementary laboratory modules provided by NASA, the European Space Agency and the Japanese space agency, NASDA. Use of all facilities in each of the modules will be available to investigators from participating space agencies. With the advent of the ISS, space-based gravitational biology research will transition from 10-16 day short-duration Space Shuttle flights to 90-day-or-longer ISS increments.

Space Station Biological Research Project

NASA Technical Reports Server (NTRS)

Johnson, C. C.; Wade, C. E.; Givens, J. J.

1997-01-01

To meet NASA's objective of using the unique aspects of the space environment to expand fundamental knowledge in the biological sciences, the Space Station Biological Research Project at Ames Research Center is developing, or providing oversight, for two major suites of hardware which will be installed on the International Space Station (ISS). The first, the Gravitational Biology Facility, consists of Habitats to support plants, rodents, cells, aquatic specimens, avian and reptilian eggs, and insects and the Habitat Holding Rack in which to house them at microgravity; the second, the Centrifuge Facility, consists of a 2.5 m diameter centrifuge that will provide acceleration levels between 0.01 g and 2.0 g and a Life Sciences Glovebox. These two facilities will support the conduct of experiments to: 1) investigate the effect of microgravity on living systems; 2) what level of gravity is required to maintain normal form and function, and 3) study the use of artificial gravity as a countermeasure to the deleterious effects of microgravity observed in the crew. Upon completion, the ISS will have three complementary laboratory modules provided by NASA, the European Space Agency and the Japanese space agency, NASDA. Use of all facilities in each of the modules will be available to investigators from participating space agencies. With the advent of the ISS, space-based gravitational biology research will transition from 10-16 day short-duration Space Shuttle flights to 90-day-or-longer ISS increments.

Spatial landscape model to characterize biological diversity using R statistical computing environment.

PubMed

Singh, Hariom; Garg, R D; Karnatak, Harish C; Roy, Arijit

2018-01-15

Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational biology of RNA interactions.

PubMed

Dieterich, Christoph; Stadler, Peter F

2013-01-01

The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNA-RNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNA-RNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments. Copyright © 2012 John Wiley & Sons, Ltd.

Biological Databases for Human Research

PubMed Central

Zou, Dong; Ma, Lina; Yu, Jun; Zhang, Zhang

2015-01-01

The completion of the Human Genome Project lays a foundation for systematically studying the human genome from evolutionary history to precision medicine against diseases. With the explosive growth of biological data, there is an increasing number of biological databases that have been developed in aid of human-related research. Here we present a collection of human-related biological databases and provide a mini-review by classifying them into different categories according to their data types. As human-related databases continue to grow not only in count but also in volume, challenges are ahead in big data storage, processing, exchange and curation. PMID:25712261

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winkler, David A., E-mail: dave.winkler@csiro.au

2016-05-15

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,more » 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.« less

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

PubMed

November, Joseph

2011-06-01

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

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

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

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

GUI to Facilitate Research on Biological Damage from Radiation

NASA Technical Reports Server (NTRS)

Cucinotta, Frances A.; Ponomarev, Artem Lvovich

2010-01-01

A graphical-user-interface (GUI) computer program has been developed to facilitate research on the damage caused by highly energetic particles and photons impinging on living organisms. The program brings together, into one computational workspace, computer codes that have been developed over the years, plus codes that will be developed during the foreseeable future, to address diverse aspects of radiation damage. These include codes that implement radiation-track models, codes for biophysical models of breakage of deoxyribonucleic acid (DNA) by radiation, pattern-recognition programs for extracting quantitative information from biological assays, and image-processing programs that aid visualization of DNA breaks. The radiation-track models are based on transport models of interactions of radiation with matter and solution of the Boltzmann transport equation by use of both theoretical and numerical models. The biophysical models of breakage of DNA by radiation include biopolymer coarse-grained and atomistic models of DNA, stochastic- process models of deposition of energy, and Markov-based probabilistic models of placement of double-strand breaks in DNA. The program is designed for use in the NT, 95, 98, 2000, ME, and XP variants of the Windows operating system.

DNASU plasmid and PSI:Biology-Materials repositories: resources to accelerate biological research

PubMed Central

Seiler, Catherine Y.; Park, Jin G.; Sharma, Amit; Hunter, Preston; Surapaneni, Padmini; Sedillo, Casey; Field, James; Algar, Rhys; Price, Andrea; Steel, Jason; Throop, Andrea; Fiacco, Michael; LaBaer, Joshua

2014-01-01

The mission of the DNASU Plasmid Repository is to accelerate research by providing high-quality, annotated plasmid samples and online plasmid resources to the research community through the curated DNASU database, website and repository (http://dnasu.asu.edu or http://dnasu.org). The collection includes plasmids from grant-funded, high-throughput cloning projects performed in our laboratory, plasmids from external researchers, and large collections from consortia such as the ORFeome Collaboration and the NIGMS-funded Protein Structure Initiative: Biology (PSI:Biology). Through DNASU, researchers can search for and access detailed information about each plasmid such as the full length gene insert sequence, vector information, associated publications, and links to external resources that provide additional protein annotations and experimental protocols. Plasmids can be requested directly through the DNASU website. DNASU and the PSI:Biology-Materials Repositories were previously described in the 2010 NAR Database Issue (Cormier, C.Y., Mohr, S.E., Zuo, D., Hu, Y., Rolfs, A., Kramer, J., Taycher, E., Kelley, F., Fiacco, M., Turnbull, G. et al. (2010) Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community. Nucleic Acids Res., 38, D743–D749.). In this update we will describe the plasmid collection and highlight the new features in the website redesign, including new browse/search options, plasmid annotations and a dynamic vector mapping feature that was developed in collaboration with LabGenius. Overall, these plasmid resources continue to enable research with the goal of elucidating the role of proteins in both normal biological processes and disease. PMID:24225319

77 FR 55200 - Biological and Environmental Research Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-07

... News from the Biological Systems Science and Climate and Environmental Sciences Divisions Discussion of... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Office of... the Biological and Environmental Research Advisory Committee (BERAC). The Federal Advisory Committee...

Biology Education Research: Lessons and Future Directions

ERIC Educational Resources Information Center

Singer, Susan R.; Nielsen, Natalie R.; Schweingruber, Heidi A.

2013-01-01

Biologists have long been concerned about the quality of undergraduate biology education. Over time, however, biology faculty members have begun to study increasingly sophisticated questions about teaching and learning in the discipline. These scholars, often called biology education researchers, are part of a growing field of inquiry called…

Quantitative proteomics in biological research.

PubMed

Wilm, Matthias

2009-10-01

Proteomics has enabled the direct investigation of biological material, at first through the analysis of individual proteins, then of lysates from cell cultures, and finally of extracts from tissues and biopsies from entire organisms. Its latest manifestation - quantitative proteomics - allows deeper insight into biological systems. This article reviews the different methods used to extract quantitative information from mass spectra. It follows the technical developments aimed toward global proteomics, the attempt to characterize every expressed protein in a cell by at least one peptide. When applications of the technology are discussed, the focus is placed on yeast biology. In particular, differential quantitative proteomics, the comparison between an experiment and its control, is very discriminating for proteins involved in the process being studied. When trying to understand biological processes on a molecular level, differential quantitative proteomics tends to give a clearer picture than global transcription analyses. As a result, MS has become an even more indispensable tool for biochemically motivated biological research.

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP),

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA

78 FR 77111 - Biological and Environmental Research Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-20

..., General Services Administration, notice is hereby given that the Biological and Environmental Research... DEPARTMENT OF ENERGY Biological and Environmental Research Advisory Committee AGENCY: Office of... provides advice and recommendations to the Director, Office of Science on the biological and environmental...

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Jaffe, Richard; Liang, Shoudan; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2002-01-01

We present results from several projects in the new field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. We have developed a procedure for calculating long-range effects in molecular dynamics using a plane wave expansion of the electrostatic potential. This method is expected to be highly efficient for simulating biological systems on massively parallel supercomputers. We have perform genomics analysis on a family of actin binding proteins. We have performed quantum mechanical calculations on carbon nanotubes and nucleic acids, which simulations will allow us to investigate possible sources of organic material on the early earth. Finally, we have developed a model of protobiological chemistry using neural networks.

Accelerating Cancer Systems Biology Research through Semantic Web Technology

PubMed Central

Wang, Zhihui; Sagotsky, Jonathan; Taylor, Thomas; Shironoshita, Patrick; Deisboeck, Thomas S.

2012-01-01

Cancer systems biology is an interdisciplinary, rapidly expanding research field in which collaborations are a critical means to advance the field. Yet the prevalent database technologies often isolate data rather than making it easily accessible. The Semantic Web has the potential to help facilitate web-based collaborative cancer research by presenting data in a manner that is self-descriptive, human and machine readable, and easily sharable. We have created a semantically linked online Digital Model Repository (DMR) for storing, managing, executing, annotating, and sharing computational cancer models. Within the DMR, distributed, multidisciplinary, and inter-organizational teams can collaborate on projects, without forfeiting intellectual property. This is achieved by the introduction of a new stakeholder to the collaboration workflow, the institutional licensing officer, part of the Technology Transfer Office. Furthermore, the DMR has achieved silver level compatibility with the National Cancer Institute’s caBIG®, so users can not only interact with the DMR through a web browser but also through a semantically annotated and secure web service. We also discuss the technology behind the DMR leveraging the Semantic Web, ontologies, and grid computing to provide secure inter-institutional collaboration on cancer modeling projects, online grid-based execution of shared models, and the collaboration workflow protecting researchers’ intellectual property. PMID:23188758

Biology of an Enzyme: A Research-Like Experience for Introductory Biology Students.

ERIC Educational Resources Information Center

Towle, David W.

1992-01-01

Presents a series of laboratory exercises designed to introduce students to a realistic experience in biological research that is feasible with large numbers of beginning biology majors. The exercises center on the study of alkaline phosphatase. (DDR)

A unique large-scale undergraduate research experience in molecular systems biology for non-mathematics majors.

PubMed

Kappler, Ulrike; Rowland, Susan L; Pedwell, Rhianna K

2017-05-01

Systems biology is frequently taught with an emphasis on mathematical modeling approaches. This focus effectively excludes most biology, biochemistry, and molecular biology students, who are not mathematics majors. The mathematical focus can also present a misleading picture of systems biology, which is a multi-disciplinary pursuit requiring collaboration between biochemists, bioinformaticians, and mathematicians. This article describes an authentic large-scale undergraduate research experience (ALURE) in systems biology that incorporates proteomics, bacterial genomics, and bioinformatics in the one exercise. This project is designed to engage students who have a basic grounding in protein chemistry and metabolism and no mathematical modeling skills. The pedagogy around the research experience is designed to help students attack complex datasets and use their emergent metabolic knowledge to make meaning from large amounts of raw data. On completing the ALURE, participants reported a significant increase in their confidence around analyzing large datasets, while the majority of the cohort reported good or great gains in a variety of skills including "analysing data for patterns" and "conducting database or internet searches." An environmental scan shows that this ALURE is the only undergraduate-level system-biology research project offered on a large-scale in Australia; this speaks to the perceived difficulty of implementing such an opportunity for students. We argue however, that based on the student feedback, allowing undergraduate students to complete a systems-biology project is both feasible and desirable, even if the students are not maths and computing majors. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(3):235-248, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

Topological properties of robust biological and computational networks

PubMed Central

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

2014-01-01

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

Computers in aeronautics and space research at the Lewis Research Center

NASA Technical Reports Server (NTRS)

1991-01-01

This brochure presents a general discussion of the role of computers in aerospace research at NASA's Lewis Research Center (LeRC). Four particular areas of computer applications are addressed: computer modeling and simulation, computer assisted engineering, data acquisition and analysis, and computer controlled testing.

Discovery of novel bacterial toxins by genomics and computational biology.

PubMed

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.

Delivering The Benefits of Chemical-Biological Integration in ...

EPA Pesticide Factsheets

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 intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy. Presentation at ACS TOXI session on Computational Chemistry and Toxicology in Chemical Discovery and Assessement (QSARs).

Aluminium in Biological Environments: A Computational Approach

PubMed Central

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

2014-01-01

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

United States Department of Agriculture-Agricultural Research Service research on pest biology: weeds.

PubMed

Forcella, Frank

2003-01-01

Over 125 permanent full-time scientists conduct research within the USDA Agricultural Research Service (ARS) on issues related to weeds. The research emphasis of most of these scientists involves ecology and management or biological control of weeds. Many scientists perform research on weed biology as components of their primary projects on weed control and integrated crop and soil management. Describing all ARS projects involved with weed biology is impossible, and consequently only research that falls within the following arbitrarily chosen topics is highlighted in this article: dormancy mechanisms; cell division; diversity of rangeland weeds; soil resources and rangeland weeds; poisonous rangeland plants; horticultural weeds; weed traits limiting chemical control; aquatic and semi-aquatic weeds; weed/transgenic wheat hybrids; seedbanks, seedling emergence and seedling populations; and weed seed production. Within these topics, and others not highlighted, the desire of ARS is that good information on weed biology currently translates or eventually will translate into practical advice for those who must manage weeds.

Computing chemical organizations in biological networks.

PubMed

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.

Systems biology driven software design for the research enterprise.

PubMed

Boyle, John; Cavnor, Christopher; Killcoyne, Sarah; Shmulevich, Ilya

2008-06-25

In systems biology, and many other areas of research, there is a need for the interoperability of tools and data sources that were not originally designed to be integrated. Due to the interdisciplinary nature of systems biology, and its association with high throughput experimental platforms, there is an additional need to continually integrate new technologies. As scientists work in isolated groups, integration with other groups is rarely a consideration when building the required software tools. We illustrate an approach, through the discussion of a purpose built software architecture, which allows disparate groups to reuse tools and access data sources in a common manner. The architecture allows for: the rapid development of distributed applications; interoperability, so it can be used by a wide variety of developers and computational biologists; development using standard tools, so that it is easy to maintain and does not require a large development effort; extensibility, so that new technologies and data types can be incorporated; and non intrusive development, insofar as researchers need not to adhere to a pre-existing object model. By using a relatively simple integration strategy, based upon a common identity system and dynamically discovered interoperable services, a light-weight software architecture can become the focal point through which scientists can both get access to and analyse the plethora of experimentally derived data.

Systems biology driven software design for the research enterprise

PubMed Central

Boyle, John; Cavnor, Christopher; Killcoyne, Sarah; Shmulevich, Ilya

2008-01-01

Background In systems biology, and many other areas of research, there is a need for the interoperability of tools and data sources that were not originally designed to be integrated. Due to the interdisciplinary nature of systems biology, and its association with high throughput experimental platforms, there is an additional need to continually integrate new technologies. As scientists work in isolated groups, integration with other groups is rarely a consideration when building the required software tools. Results We illustrate an approach, through the discussion of a purpose built software architecture, which allows disparate groups to reuse tools and access data sources in a common manner. The architecture allows for: the rapid development of distributed applications; interoperability, so it can be used by a wide variety of developers and computational biologists; development using standard tools, so that it is easy to maintain and does not require a large development effort; extensibility, so that new technologies and data types can be incorporated; and non intrusive development, insofar as researchers need not to adhere to a pre-existing object model. Conclusion By using a relatively simple integration strategy, based upon a common identity system and dynamically discovered interoperable services, a light-weight software architecture can become the focal point through which scientists can both get access to and analyse the plethora of experimentally derived data. PMID:18578887

Metabolomics and malaria biology

PubMed Central

Lakshmanan, Viswanathan; Rhee, Kyu Y.; Daily, Johanna P.

2010-01-01

Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research. PMID:20970461

From Jabberwocky to genome: Lewis Carroll and computational biology.

PubMed

Searls, D B

2001-01-01

In addition to his literary output, Lewis Carroll created a vast range of games and puzzles that depend upon wordplay of various kinds, especially the manipulation of alphabetic symbols in diverse contexts. Such wordplay reveals a turn of mind well suited to methodologies used in modern computational biology.

Biology Students Building Computer Simulations Using StarLogo TNG

ERIC Educational Resources Information Center

Smith, V. Anne; Duncan, Ishbel

2011-01-01

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

Agents in bioinformatics, computational and systems biology.

PubMed

Merelli, Emanuela; Armano, Giuliano; Cannata, Nicola; Corradini, Flavio; d'Inverno, Mark; Doms, Andreas; Lord, Phillip; Martin, Andrew; Milanesi, Luciano; Möller, Steffen; Schroeder, Michael; Luck, Michael

2007-01-01

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1986-01-01

Various graduate research activities in the field of computer science are reported. Among the topics discussed are: (1) failure probabilities in multi-version software; (2) Gaussian Elimination on parallel computers; (3) three dimensional Poisson solvers on parallel/vector computers; (4) automated task decomposition for multiple robot arms; (5) multi-color incomplete cholesky conjugate gradient methods on the Cyber 205; and (6) parallel implementation of iterative methods for solving linear equations.

pClone: Synthetic Biology Tool Makes Promoter Research Accessible to Beginning Biology Students.

PubMed

Campbell, A Malcolm; Eckdahl, Todd; Cronk, Brian; Andresen, Corinne; Frederick, Paul; Huckuntod, Samantha; Shinneman, Claire; Wacker, Annie; Yuan, Jason

2014-01-01

The Vision and Change report recommended genuine research experiences for undergraduate biology students. Authentic research improves science education, increases the number of scientifically literate citizens, and encourages students to pursue research. Synthetic biology is well suited for undergraduate research and is a growing area of science. We developed a laboratory module called pClone that empowers students to use advances in molecular cloning methods to discover new promoters for use by synthetic biologists. Our educational goals are consistent with Vision and Change and emphasize core concepts and competencies. pClone is a family of three plasmids that students use to clone a new transcriptional promoter or mutate a canonical promoter and measure promoter activity in Escherichia coli. We also developed the Registry of Functional Promoters, an open-access database of student promoter research results. Using pre- and posttests, we measured significant learning gains among students using pClone in introductory biology and genetics classes. Student posttest scores were significantly better than scores of students who did not use pClone. pClone is an easy and affordable mechanism for large-enrollment labs to meet the high standards of Vision and Change. © 2014 A. M. Campbell et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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

PubMed Central

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

2014-01-01

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

Computational Biology Methods for Characterization of Pluripotent Cells.

PubMed

Araúzo-Bravo, Marcos J

2016-01-01

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

Integrating Computer Interfaced Videodisc Systems in Introductory College Biology.

ERIC Educational Resources Information Center

Ebert-Zawasky, Kathleen; Abegg, Gerald L.

This study was designed as a systematic investigation of the feasibility and effectiveness of student authored videodisc presentations in a non-major introductory level college biology course. Students (n=66) used a quick-learn authoring system, the Macintosh computer, and videodisc player with color monitor. Results included: (1) students managed…

[Biological research and security institutes].

PubMed

Darsie, G; Falczuk, A J; Bergmann, I E

2006-04-01

The threat of using biological material for ago-bioterrorist ends has risen in recent years, which means that research and diagnostic laboratories, biological agent banks and other institutions authorised to carry out scientific activities have had to implement biosafety and biosecurity measures to counter the threat, while carrying out activities to help prevent and monitor the accidental or intentional introduction of exotic animal diseases. This article briefly sets outthe basic components of biosafety and biosecurity, as well as recommendations on organisational strategies to consider in laboratories that support agro-bioterrorist surveillance and prevention programs.

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

EPA Science Inventory

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

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

Supporting High School Student Accomplishment of Biology Content Using Interactive Computer-Based Curricular Case Studies

NASA Astrophysics Data System (ADS)

Oliver, Joseph Steve; Hodges, Georgia W.; Moore, James N.; Cohen, Allan; Jang, Yoonsun; Brown, Scott A.; Kwon, Kyung A.; Jeong, Sophia; Raven, Sara P.; Jurkiewicz, Melissa; Robertson, Tom P.

2017-11-01

Research into the efficacy of modules featuring dynamic visualizations, case studies, and interactive learning environments is reported here. This quasi-experimental 2-year study examined the implementation of three interactive computer-based instructional modules within a curricular unit covering cellular biology concepts in an introductory high school biology course. The modules featured dynamic visualizations and focused on three processes that underlie much of cellular biology: diffusion, osmosis, and filtration. Pre-tests and post-tests were used to assess knowledge growth across the unit. A mixture Rasch model analysis of the post-test data revealed two groups of students. In both years of the study, a large proportion of the students were classified as low-achieving based on their pre-test scores. The use of the modules in the Cell Unit in year 2 was associated with a much larger proportion of the students having transitioned to the high-achieving group than in year 1. In year 2, the same teachers taught the same concepts as year 1 but incorporated the interactive computer-based modules into the cell biology unit of the curriculum. In year 2, 67% of students initially classified as low-achieving were classified as high-achieving at the end of the unit. Examination of responses to assessments embedded within the modules as well as post-test items linked transition to the high-achieving group with correct responses to items that both referenced the visualization and the contextualization of that visualization within the module. This study points to the importance of dynamic visualization within contextualized case studies as a means to support student knowledge acquisition in biology.

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

NASA Astrophysics Data System (ADS)

Fitch, W. Tecumseh

2014-09-01

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

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

PubMed

Fitch, W Tecumseh

2014-09-01

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

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Developing an online programme in computational biology.

PubMed

Vincent, Heather M; Page, Christopher

2013-11-01

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

VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA

PubMed Central

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.

2010-01-01

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org. PMID:20007449

Biological Research in Support of Project MILES.

DTIC Science & Technology

1981-07-01

E S BEATRICE UNCLASSIFIED LAIR - 9 6 N too INSTITUTE REPORT NO. 96’ 0 BIOLOGICAL RESEARCH IN SUPPORT OF PROJECT MILES DA Via . LUND, aS BRUCE E...ACCESSION NO. 3’ R ENTS CATALOG NUMBER LAIR Drp-Nr96 _ _ _ _ _ _ S5T, F EnI r~,.. VERED Biological Research in Support of Project MILES )n. Anual .je 7...experiments at other agencies did not confirm the LAIR observation of retinal clouding. The ocular effects were studied of lasers operating at infrared

Exploiting graphics processing units for computational biology and bioinformatics.

PubMed

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

2010-09-01

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

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

PubMed

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

2015-01-01

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

The dilemma of dual use biological research: Polish perspective.

PubMed

Czarkowski, Marek

2010-03-01

Biological research with legitimate scientific purpose that may be misused to pose a biological threat to public health and/or national security is termed dual use. In Poland there are adequate conditions for conducting experiments that could be qualified as dual use research, and therefore, a risk of attack on Poland or other countries exists. Optimal solutions for limiting such threats are required, and the national system of biosecurity should enable early, reliable, and complete identification of this type of research. Scientists should have a fundamental role in this process, their duty being to immediately, upon identification, report research with dual use potential. An important entity in the identification system of dual use research should also be the Central Register of Biological and Biomedical Research, which gathers information about all biological and biomedical research being conducted in a given country. Publishers, editors, and review committees of journals and other scientific publications should be involved in evaluating results of clinical trials. The National Council of Biosecurity should be the governmental institution responsible for developing a system of dual use research threat prevention. Its role would be to develop codes of conduct, form counsel of expertise, and monitor the problem at national level, while the Dual Use Research Committee would be responsible for individual cases. In Poland, current actions aiming to provide biological safety were based on developing and passing an act about genetically modified organisms (GMO's) and creating a GMO Committee. Considering experiences of other nations, one should view these actions as fragmentary, and thus insufficient protection against dual use research threats.

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

PubMed Central

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

Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2000-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a

Computers and the Learning of Biological Concepts: Attitudes and Achievement of Nigerian Students.

ERIC Educational Resources Information Center

Jegede, Olugbemiro J.

1991-01-01

Compared attitudes toward computer use and achievement in biology for three groups of Nigerian students (n=64): (1) working alone with computer; (2) working in groups of three on the computer; (3) and a control group that received normal instruction (lecture). Students in the second group had the highest scores on attitude. No significant…

Multiobjective optimization in bioinformatics and computational biology.

PubMed

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

2007-01-01

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

The Implementation of Research-based Learning on Biology Seminar Course in Biology Education Study Program of FKIP UMRAH

NASA Astrophysics Data System (ADS)

Amelia, T.

2018-04-01

Biology Seminar is a course in Biology Education Study Program of Faculty of Teacher Training and Education University of Maritim Raja Ali Haji (FKIP UMRAH) that requires students to have the ability to apply scientific attitudes, perform scientific writing and undertake scientific publications on a small scale. One of the learning strategies that can drive the achievement of learning outcomes in this course is Research-Based Learning. Research-Based Learning principles are considered in accordance with learning outcomes in Biology Seminar courses and generally in accordance with the purpose of higher education. On this basis, this article which is derived from a qualitative research aims at describing Research-based Learning on Biology Seminar course. Based on a case study research, it was known that Research-Based Learning on Biology Seminar courses is applied through: designing learning activities around contemporary research issues; teaching research methods, techniques and skills explicitly within program; drawing on personal research in designing and teaching courses; building small-scale research activities into undergraduate assignment; and infusing teaching with the values of researchers.

pClone: Synthetic Biology Tool Makes Promoter Research Accessible to Beginning Biology Students

PubMed Central

Eckdahl, Todd; Cronk, Brian; Andresen, Corinne; Frederick, Paul; Huckuntod, Samantha; Shinneman, Claire; Wacker, Annie; Yuan, Jason

2014-01-01

The Vision and Change report recommended genuine research experiences for undergraduate biology students. Authentic research improves science education, increases the number of scientifically literate citizens, and encourages students to pursue research. Synthetic biology is well suited for undergraduate research and is a growing area of science. We developed a laboratory module called pClone that empowers students to use advances in molecular cloning methods to discover new promoters for use by synthetic biologists. Our educational goals are consistent with Vision and Change and emphasize core concepts and competencies. pClone is a family of three plasmids that students use to clone a new transcriptional promoter or mutate a canonical promoter and measure promoter activity in Escherichia coli. We also developed the Registry of Functional Promoters, an open-access database of student promoter research results. Using pre- and posttests, we measured significant learning gains among students using pClone in introductory biology and genetics classes. Student posttest scores were significantly better than scores of students who did not use pClone. pClone is an easy and affordable mechanism for large-enrollment labs to meet the high standards of Vision and Change. PMID:26086659

Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research.

PubMed

Erdemir, Ahmet; Hunter, Peter J; Holzapfel, Gerhard A; Loew, Leslie M; Middleton, John; Jacobs, Christopher R; Nithiarasu, Perumal; Löhner, Rainlad; Wei, Guowei; Winkelstein, Beth A; Barocas, Victor H; Guilak, Farshid; Ku, Joy P; Hicks, Jennifer L; Delp, Scott L; Sacks, Michael; Weiss, Jeffrey A; Ateshian, Gerard A; Maas, Steve A; McCulloch, Andrew D; Peng, Grace C Y

2018-02-01

The role of computational modeling for biomechanics research and related clinical care will be increasingly prominent. The biomechanics community has been developing computational models routinely for exploration of the mechanics and mechanobiology of diverse biological structures. As a result, a large array of models, data, and discipline-specific simulation software has emerged to support endeavors in computational biomechanics. Sharing computational models and related data and simulation software has first become a utilitarian interest, and now, it is a necessity. Exchange of models, in support of knowledge exchange provided by scholarly publishing, has important implications. Specifically, model sharing can facilitate assessment of reproducibility in computational biomechanics and can provide an opportunity for repurposing and reuse, and a venue for medical training. The community's desire to investigate biological and biomechanical phenomena crossing multiple systems, scales, and physical domains, also motivates sharing of modeling resources as blending of models developed by domain experts will be a required step for comprehensive simulation studies as well as the enhancement of their rigor and reproducibility. The goal of this paper is to understand current perspectives in the biomechanics community for the sharing of computational models and related resources. Opinions on opportunities, challenges, and pathways to model sharing, particularly as part of the scholarly publishing workflow, were sought. A group of journal editors and a handful of investigators active in computational biomechanics were approached to collect short opinion pieces as a part of a larger effort of the IEEE EMBS Computational Biology and the Physiome Technical Committee to address model reproducibility through publications. A synthesis of these opinion pieces indicates that the community recognizes the necessity and usefulness of model sharing. There is a strong will to facilitate

Biology Education Research Trends in Turkey

ERIC Educational Resources Information Center

Gul, Seyda; Sozbilir, Mustafa

2015-01-01

This paper reports on a content analysis of 633 biology education research [BER] papers published by Turkish science educators in national and international journals. The findings indicate that more research has been undertaken in environment and ecology, the cell and animal form and functions. In addition learning, teaching and attitudes were in…

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

PubMed Central

2015-01-01

In this meeting report, we give an overview of the talks, presentations and posters presented at the third European Symposium of the International Society for Computational Biology (ISCB) Student Council. The event was organized as a satellite meeting of the 13th European Conference for Computational Biology (ECCB) and took place in Strasbourg, France on September 6th, 2014. PMID:25708611

Computational intelligence techniques for biological data mining: An overview

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

Kapetanovic, I.M.

2008-01-01

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

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Colombano, Silvano; Scargle, Jeff; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2003-01-01

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

BrisSynBio: a BBSRC/EPSRC-funded Synthetic Biology Research Centre.

PubMed

Sedgley, Kathleen R; Race, Paul R; Woolfson, Derek N

2016-06-15

BrisSynBio is the Bristol-based Biotechnology and Biological Sciences Research Council (BBSRC)/Engineering and Physical Sciences Research Council (EPSRC)-funded Synthetic Biology Research Centre. It is one of six such Centres in the U.K. BrisSynBio's emphasis is on rational and predictive bimolecular modelling, design and engineering in the context of synthetic biology. It trains the next generation of synthetic biologists in these approaches, to facilitate translation of fundamental synthetic biology research to industry and the clinic, and to do this within an innovative and responsible research framework. © 2016 The Author(s).

Research and the Personal Computer.

ERIC Educational Resources Information Center

Blackburn, D. A.

1989-01-01

Discussed is the history and elements of the personal computer. Its uses as a laboratory assistant and generic toolkit for mathematical analysis and modeling are included. The future of the personal computer in research is addressed. (KR)

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

PubMed

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

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

PubMed Central

2011-01-01

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

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

PubMed Central

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

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved. PMID:24078906

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

PubMed

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

2013-01-01

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

Interactions of dendrimers with biological drug targets: reality or mystery - a gap in drug delivery and development research.

PubMed

Ahmed, Shaimaa; Vepuri, Suresh B; Kalhapure, Rahul S; Govender, Thirumala

2016-07-21

Dendrimers have emerged as novel and efficient materials that can be used as therapeutic agents/drugs or as drug delivery carriers to enhance therapeutic outcomes. Molecular dendrimer interactions are central to their applications and realising their potential. The molecular interactions of dendrimers with drugs or other materials in drug delivery systems or drug conjugates have been extensively reported in the literature. However, despite the growing application of dendrimers as biologically active materials, research focusing on the mechanistic analysis of dendrimer interactions with therapeutic biological targets is currently lacking in the literature. This comprehensive review on dendrimers over the last 15 years therefore attempts to identify the reasons behind the apparent lack of dendrimer-receptor research and proposes approaches to address this issue. The structure, hierarchy and applications of dendrimers are briefly highlighted, followed by a review of their various applications, specifically as biologically active materials, with a focus on their interactions at the target site. It concludes with a technical guide to assist researchers on how to employ various molecular modelling and computational approaches for research on dendrimer interactions with biological targets at a molecular level. This review highlights the impact of a mechanistic analysis of dendrimer interactions on a molecular level, serves to guide and optimise their discovery as medicinal agents, and hopes to stimulate multidisciplinary research between scientific, experimental and molecular modelling research teams.

Graphics supercomputer for computational fluid dynamics research

NASA Astrophysics Data System (ADS)

Liaw, Goang S.

1994-11-01

The objective of this project is to purchase a state-of-the-art graphics supercomputer to improve the Computational Fluid Dynamics (CFD) research capability at Alabama A & M University (AAMU) and to support the Air Force research projects. A cutting-edge graphics supercomputer system, Onyx VTX, from Silicon Graphics Computer Systems (SGI), was purchased and installed. Other equipment including a desktop personal computer, PC-486 DX2 with a built-in 10-BaseT Ethernet card, a 10-BaseT hub, an Apple Laser Printer Select 360, and a notebook computer from Zenith were also purchased. A reading room has been converted to a research computer lab by adding some furniture and an air conditioning unit in order to provide an appropriate working environments for researchers and the purchase equipment. All the purchased equipment were successfully installed and are fully functional. Several research projects, including two existing Air Force projects, are being performed using these facilities.

Computational fluid dynamics research

NASA Technical Reports Server (NTRS)

Chandra, Suresh; Jones, Kenneth; Hassan, Hassan; Mcrae, David Scott

1992-01-01

The focus of research in the computational fluid dynamics (CFD) area is two fold: (1) to develop new approaches for turbulence modeling so that high speed compressible flows can be studied for applications to entry and re-entry flows; and (2) to perform research to improve CFD algorithm accuracy and efficiency for high speed flows. Research activities, faculty and student participation, publications, and financial information are outlined.

Advancing Systems Biology in the International Conference on Intelligent Biology and Medicine (ICIBM) 2015.

PubMed

Zhao, Zhongming; Liu, Yunlong; Huang, Yufei; Huang, Kun; Ruan, Jianhua

2016-08-26

The 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) was held on November 13-15, 2015 in Indianapolis, Indiana, USA. ICIBM 2015 included eight scientific sessions, three tutorial sessions, one poster session, and four keynote presentations that covered the frontier research in broad areas related to bioinformatics, systems biology, big data science, biomedical informatics, pharmacogenomics, and intelligent computing. Here, we present a summary of the 10 research articles that were selected from ICIBM 2015 and included in the supplement to BMC Systems Biology.

Computational adaptive optics for broadband optical interferometric tomography of biological tissue

NASA Astrophysics Data System (ADS)

Boppart, Stephen A.

2015-03-01

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

7th Annual Systems Biology Symposium: Systems Biology and Engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Galitski, Timothy P.

2008-04-01

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

Action Research of Computer-Assisted-Remediation of Basic Research Concepts.

ERIC Educational Resources Information Center

Packard, Abbot L.; And Others

This study investigated the possibility of creating a computer-assisted remediation program to assist students having difficulties in basic college research and statistics courses. A team approach involving instructors and students drove the research into and creation of the computer program. The effect of student use was reviewed by looking at…

When cloud computing meets bioinformatics: a review.

PubMed

Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong

2013-10-01

In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

Highlights from the Eighth International Society for Computational Biology (ISCB) Student Council Symposium 2012

PubMed Central

2012-01-01

The report summarizes the scientific content of the annual symposium organized by the Student Council of the International Society for Computational Biology (ISCB) held in conjunction with the Intelligent Systems for Molecular Biology (ISMB) conference in Long Beach, California on July 13, 2012.

Global biology - An interdisciplinary scientific research program at NASA, Ames Research Center

NASA Technical Reports Server (NTRS)

Lawless, J. G.; Colin, L.

1983-01-01

NASA has initiated new effort in Global Biology, the primary focus of which is to understand biogeochemical cycles. As part of this effort, an interdisciplinary team of scientists has formed at Ames Research Center to investigate the cycling of sulfur in the marine coastal zone and to study the cycling of nitrogen in terrestrial ecosystems. Both studies will use remotely sensed data, coupled with ground-based research, to identify and measure the transfer of major and minor biologically produced gases between these ecosystems and global reservoirs.

Global Biology: An Interdisciplinary Scientific Research Program at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Lawless, James G.; Colin, Lawrence

1984-01-01

NASA has initiated new effort in Global Biology, the primary focus of which is to understand biogeochemical cycles. As part of this effort, an interdisciplinary team of scientists has formed at Ames Research Center to investigate the cycling of sulfur in the marine coastal zone and to study the cycling of nitrogen in terrestrial ecosystems. Both studies will use remotely sensed data, coupled with ground-based research, to identify and measure the transfer of major and minor biologically produced gases between these ecosystems and global reservoirs.

The application of biological motion research: biometrics, sport, and the military.

PubMed

Steel, Kylie; Ellem, Eathan; Baxter, David

2015-02-01

The body of research that examines the perception of biological motion is extensive and explores the factors that are perceived from biological motion and how this information is processed. This research demonstrates that individuals are able to use relative (temporal and spatial) information from a person's movement to recognize factors, including gender, age, deception, emotion, intention, and action. The research also demonstrates that movement presents idiosyncratic properties that allow individual discrimination, thus providing the basis for significant exploration in the domain of biometrics and social signal processing. Medical forensics, safety garments, and victim selection domains also have provided a history of research on the perception of biological motion applications; however, a number of additional domains present opportunities for application that have not been explored in depth. Therefore, the purpose of this paper is to present an overview of the current applications of biological motion-based research and to propose a number of areas where biological motion research, specific to recognition, could be applied in the future.

Mixed-Methods Design in Biology Education Research: Approach and Uses.

PubMed

Warfa, Abdi-Rizak M

Educational research often requires mixing different research methodologies to strengthen findings, better contextualize or explain results, or minimize the weaknesses of a single method. This article provides practical guidelines on how to conduct such research in biology education, with a focus on mixed-methods research (MMR) that uses both quantitative and qualitative inquiries. Specifically, the paper provides an overview of mixed-methods design typologies most relevant in biology education research. It also discusses common methodological issues that may arise in mixed-methods studies and ways to address them. The paper concludes with recommendations on how to report and write about MMR. © 2016 L. A.-R. M. Warfa. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

National Aeronautics and Space Administration Biological and Physical Research Enterprise Strategy

NASA Technical Reports Server (NTRS)

2003-01-01

As the 21st century begins, NASA's new Vision and Mission focuses the Agency's Enterprises toward exploration and discovery.The Biological and Physical Research Enterprise has a unique and enabling role in support of the Agency's Vision and Mission. Our strategic research seeks innovations and solutions to enable the extension of life into deep space safely and productively. Our fundamental research, as well as our research partnerships with industry and other agencies, allow new knowledge and tech- nologies to bring improvements to life on Earth. Our interdisciplinary research in the unique laboratory of microgravity addresses opportunities and challenges on our home planet as well as in space environments. The Enterprise maintains a key role in encouraging and engaging the next generation of explorers from primary school through the grad- uate level via our direct student participation in space research.The Biological and Physical Research Enterprise encompasses three themes. The biological sciences research theme investigates ways to support a safe human presence in space. This theme addresses the definition and control of physiological and psychological risks from the space environment, including radiation,reduced gravity, and isolation. The biological sciences research theme is also responsible for the develop- ment of human support systems technology as well as fundamental biological research spanning topics from genomics to ecologies. The physical sciences research theme supports research that takes advantage of the space environment to expand our understanding of the fundamental laws of nature. This theme also supports applied physical sciences research to improve safety and performance of humans in space. The research partnerships and flight support theme establishes policies and allocates space resources to encourage and develop entrepreneurial partners access to space research.Working together across research disciplines, the Biological and Physical

Meta-Research: Broadening the Scope of PLOS Biology.

PubMed

Kousta, Stavroula; Ferguson, Christine; Ganley, Emma

2016-01-01

In growing recognition of the importance of how scientific research is designed, performed, communicated, and evaluated, PLOS Biology announces a broadening of its scope to cover meta-research articles.

Student Research in Computational Astrophysics

NASA Astrophysics Data System (ADS)

Blondin, J. M.

1999-12-01

Computational physics can shorten the long road from freshman physics major to independent research by providing students with powerful tools to deal with the complexities of modern research problems. At North Carolina State University we have introduced dozens of students to astrophysics research using the tools of computational fluid dynamics. We have used several formats for working with students, including the traditional approach of one-on-one mentoring, a more group-oriented format in which several students work together on one or more related projects, and a novel attempt to involve an entire class in a coordinated semester research project. The advantages and disadvantages of these formats will be discussed at length, but the single most important influence has been peer support. Having students work in teams or learn the tools of research together but tackle different problems has led to more positive experiences than a lone student diving into solo research. This work is supported by an NSF CAREER Award.

Emerging Uses of Computer Technology in Qualitative Research.

ERIC Educational Resources Information Center

Parker, D. Randall

The application of computer technology in qualitative research and evaluation ranges from simple word processing to doing sophisticated data sorting and retrieval. How computer software can be used for qualitative research is discussed. Researchers should consider the use of computers in data analysis in light of their own familiarity and comfort…

Cancer mortality risk among biology research workers in France: first results of two retrospective cohorts studies.

PubMed

Guseva Canu, Irina; Rogel, Agnès; Samson, Eric; Benhamou, Simone; Laplanche, Agnès; Tirmarche, Margot

2008-05-01

To investigate all-cause and cancer mortality of biological research laboratories workers of the French Atomic Energy Commission (CEA) and the National Institute of Health and Medical Research (INSERM). Two cohorts, bioCEA (N = 3,509) and bioINSERM (N = 4,966) were followed from 1968 to 1994 and 1980 to 1993, respectively. The mortality of each cohort was compared with that of the French population by computation of the standardized mortality ratio (SMR) with their 90% confidence interval (90% CI). Trend and heterogeneity tests were computed in order to study SMRs variation by job characteristics. In the bioCEA cohort individual dosimetry data being available, a trend test was also computed according to ionizing radiation cumulative dose. The SMRs were significantly below one in both cohorts for all-cause mortality (bioCEA: SMR = 0.52 [0.46-0.59], bioINSERM: SMR = 0.56 [0.46-0.67]) and for all-cancer mortality (bioCEA: SMR = 0.66 [0.54-0.80], bioINSERM: SMR = 0.55 [0.39-0.75]). There were some specific cancer sites for which the SMR was higher than 1, but not significantly. In the bioCEA cohort a positive trend was observed between ionizing radiation cumulative doses and all-cause as well as all-cancer SMRs. This study on two French cohorts of biological research workers found a favorable mortality pattern. These findings are consistent with recent publications. The positive trend of cancer mortality according to ionizing radiation exposure among bioCEA cohort needs to be confirmed with more precise assessment of exposures and information on individual risk factors.

Considering sex as a biological variable in preclinical research.

PubMed

Miller, Leah R; Marks, Cheryl; Becker, Jill B; Hurn, Patricia D; Chen, Wei-Jung; Woodruff, Teresa; McCarthy, Margaret M; Sohrabji, Farida; Schiebinger, Londa; Wetherington, Cora Lee; Makris, Susan; Arnold, Arthur P; Einstein, Gillian; Miller, Virginia M; Sandberg, Kathryn; Maier, Susan; Cornelison, Terri L; Clayton, Janine A

2017-01-01

In June 2015, the National Institutes of Health (NIH) released a Guide notice (NOT-OD-15-102) that highlighted the expectation of the NIH that the possible role of sex as a biologic variable be factored into research design, analyses, and reporting of vertebrate animal and human studies. Anticipating these guidelines, the NIH Office of Research on Women's Health, in October 2014, convened key stakeholders to discuss methods and techniques for integrating sex as a biologic variable in preclinical research. The workshop focused on practical methods, experimental design, and approaches to statistical analyses in the use of both male and female animals, cells, and tissues in preclinical research. Workshop participants also considered gender as a modifier of biology. This article builds on the workshop and is meant as a guide to preclinical investigators as they consider methods and techniques for inclusion of both sexes in preclinical research and is not intended to prescribe exhaustive/specific approaches for compliance with the new NIH policy.-Miller, L. R., Marks, C., Becker, J. B., Hurn, P. D., Chen, W.-J., Woodruff, T., McCarthy, M. M., Sohrabji, F., Schiebinger, L., Wetherington, C. L., Makris, S., Arnold, A. P., Einstein, G., Miller, V. M., Sandberg, K., Maier, S., Cornelison, T. L., Clayton, J. A. Considering sex as a biological variable in preclinical research. © FASEB.

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

PubMed Central

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

2013-01-01

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

A review on data mining and continuous optimization applications in computational biology and medicine.

PubMed

Weber, Gerhard-Wilhelm; Ozöğür-Akyüz, Süreyya; Kropat, Erik

2009-06-01

An emerging research area in computational biology and biotechnology is devoted to mathematical modeling and prediction of gene-expression patterns; it nowadays requests mathematics to deeply understand its foundations. This article surveys data mining and machine learning methods for an analysis of complex systems in computational biology. It mathematically deepens recent advances in modeling and prediction by rigorously introducing the environment and aspects of errors and uncertainty into the genetic context within the framework of matrix and interval arithmetics. Given the data from DNA microarray experiments and environmental measurements, we extract nonlinear ordinary differential equations which contain parameters that are to be determined. This is done by a generalized Chebychev approximation and generalized semi-infinite optimization. Then, time-discretized dynamical systems are studied. By a combinatorial algorithm which constructs and follows polyhedra sequences, the region of parametric stability is detected. In addition, we analyze the topological landscape of gene-environment networks in terms of structural stability. As a second strategy, we will review recent model selection and kernel learning methods for binary classification which can be used to classify microarray data for cancerous cells or for discrimination of other kind of diseases. This review is practically motivated and theoretically elaborated; it is devoted to a contribution to better health care, progress in medicine, a better education, and more healthy living conditions.

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

Explorations: A Research-Based Program Introducing Undergraduates to Diverse Biology Research Topics Taught by Grad Students and Postdocs

ERIC Educational Resources Information Center

Brownell, Sara E.; Khalfan, Waheeda; Bergmann, Dominique; Simoni, Robert

2013-01-01

Undergraduate biology majors are often overwhelmed by and underinformed about the diversity and complexity of biological research that is conducted on research-intensive campuses. We present a program that introduces undergraduates to the diversity and scope of biological research and also provides unique teaching opportunities for graduate…

ENFIN--A European network for integrative systems biology.

PubMed

Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan

2009-11-01

Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.

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

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

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

Research Activity in Computational Physics utilizing High Performance Computing: Co-authorship Network Analysis

NASA Astrophysics Data System (ADS)

Ahn, Sul-Ah; Jung, Youngim

2016-10-01

The research activities of the computational physicists utilizing high performance computing are analyzed by bibliometirc approaches. This study aims at providing the computational physicists utilizing high-performance computing and policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of researchers for high-performance computational physics as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2004-2013. We extracted the author rank in the physics field utilizing high-performance computing by the number of papers published during ten years from 2004. Finally, we drew the co-authorship network for 45 top-authors and their coauthors, and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Computing Life

ERIC Educational Resources Information Center

National Institute of General Medical Sciences (NIGMS), 2009

2009-01-01

Computer advances now let researchers quickly search through DNA sequences to find gene variations that could lead to disease, simulate how flu might spread through one's school, and design three-dimensional animations of molecules that rival any video game. By teaming computers and biology, scientists can answer new and old questions that could…

Values and Objectives in Computing Education Research

ERIC Educational Resources Information Center

Pears, Arnold; Malmi, Lauri

2009-01-01

What is Computing Education Research (CER), why are we doing this type of research, and what should the community achieve? As associate editors to this special edition we provide our perspectives and discuss how they have influenced the evolution of the Koli Calling International Conference on Computing Education Research over the last nine years.…

Mathematical and Computational Challenges in Population Biology and Ecosystems Science

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Advanced Biomedical Computing Center (ABCC) | DSITP

Cancer.gov

The Advanced Biomedical Computing Center (ABCC), located in Frederick Maryland (MD), provides HPC resources for both NIH/NCI intramural scientists and the extramural biomedical research community. Its mission is to provide HPC support, to provide collaborative research, and to conduct in-house research in various areas of computational biology and biomedical research.

Space Station Biological Research Project: Reference Experiment Book

NASA Technical Reports Server (NTRS)

Johnson, Catherine (Editor); Wade, Charles (Editor)

1996-01-01

The Space Station Biological Research Project (SSBRP), which is the combined efforts of the Centrifuge Facility (CF) and the Gravitational Biology Facility (GBF), is responsible for the development of life sciences hardware to be used on the International Space Station to support cell, developmental, and plant biology research. The SSBRP Reference Experiment Book was developed to use as a tool for guiding this development effort. The reference experiments characterize the research interests of the international scientific community and serve to identify the hardware capabilities and support equipment needed to support such research. The reference experiments also serve as a tool for understanding the operational aspects of conducting research on board the Space Station. This material was generated by the science community by way of their responses to reference experiment solicitation packages sent to them by SSBRP scientists. The solicitation process was executed in two phases. The first phase was completed in February of 1992 and the second phase completed in November of 1995. Representing these phases, the document is subdivided into a Section 1 and a Section 2. The reference experiments contained in this document are only representative microgravity experiments. They are not intended to define actual flight experiments. Ground and flight experiments will be selected through the formal NASA Research Announcement (NRA) and Announcement of Opportunity (AO) experiment solicitation, review, and selection process.

Ethical issues in biological psychiatric research with children and adolescents.

PubMed

Arnold, L E; Stoff, D M; Cook, E; Cohen, D J; Kruesi, M; Wright, C; Hattab, J; Graham, P; Zametkin, A; Castellanos, F X

1995-07-01

This article reviews, discusses, and elaborates considerations and recommendations summarized by the biological research working group at the May 1993 NIMH conference on ethical issues in mental health research on children and adolescents. Notes from the conference were summarized and supplemented by a computer search of relevant literature. Drafts were circulated for comment to national and international experts, some of whom joined as coauthors. Issues addressed include possible overprotection by policy makers and institutional review boards arising out of the recognition of children's special vulnerability without equal recognition of their need for research; the definition of minimal risk, which has often been equated with no risk in the case of children; assessment of the risk-benefit ratio; procedures for minimization of risk, such as improved technology, "piggybacking" onto clinical tests, and age-appropriate preparation; the difficulty of justifying risk for normal controls; age-graded consent; special considerations about neuroimaging; "coercive" inducement, both material and psychological; disposition of unexpected or unwanted knowledge about individuals, including the subject's right not to know and parent's right not to tell; and socioeconomic status and cultural/ethnic equity. The working group adopted a position of advocacy for children's right to research access while recognizing that this advocacy must be tempered by thoughtful protections for child and adolescent subjects.

Computation of forces from deformed visco-elastic biological tissues

NASA Astrophysics Data System (ADS)

Muñoz, José J.; Amat, David; Conte, Vito

2018-04-01

We present a least-squares based inverse analysis of visco-elastic biological tissues. The proposed method computes the set of contractile forces (dipoles) at the cell boundaries that induce the observed and quantified deformations. We show that the computation of these forces requires the regularisation of the problem functional for some load configurations that we study here. The functional measures the error of the dynamic problem being discretised in time with a second-order implicit time-stepping and in space with standard finite elements. We analyse the uniqueness of the inverse problem and estimate the regularisation parameter by means of an L-curved criterion. We apply the methodology to a simple toy problem and to an in vivo set of morphogenetic deformations of the Drosophila embryo.

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

PubMed

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.

NASA Space Biology Research Associate Program for the 21st Century

NASA Technical Reports Server (NTRS)

Sonnenfeld, Gerald

2000-01-01

The Space Biology Research Associate Program for the 21st Century provided a unique opportunity to train individuals to conduct biological research in hypo- and hyper-gravity, and to conduct ground-based research. This grant was developed to maximize the potential for Space Biology as an emerging discipline and to train a cadre of space biologists. The field of gravitational and space biology is rapidly growing at the future of the field is reflected in the quality and education of its personnel. Our chief objective was to train and develop these scientists rapidly and in a cost effective model.

[Activities of Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2001-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1985-01-01

Synopses are given for NASA supported work in computer science at the University of Virginia. Some areas of research include: error seeding as a testing method; knowledge representation for engineering design; analysis of faults in a multi-version software experiment; implementation of a parallel programming environment; two computer graphics systems for visualization of pressure distribution and convective density particles; task decomposition for multiple robot arms; vectorized incomplete conjugate gradient; and iterative methods for solving linear equations on the Flex/32.

Information science and technology developments within the National Biological Information Infrastructure

USGS Publications Warehouse

Frame, M.T.; Cotter, G.; Zolly, L.; Little, J.

2002-01-01

Whether your vantage point is that of an office window or a national park, your view undoubtedly encompasses a rich diversity of life forms, all carefully studied or managed by some scientist, resource manager, or planner. A few simple calculations - the number of species, their interrelationships, and the many researchers studying them - and you can easily see the tremendous challenges that the resulting biological data presents to the information and computer science communities. Biological information varies in format and content: it may pertain to a particular species or an entire ecosystem; it can contain land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents, the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993 on the recommendation of the National Research Council (National Research Council 1993). The NBII is designed to address these issues on a national scale, and through international partnerships. This paper discusses current information and computer science efforts within the National Biological Information Infrastructure Program, and future computer science research endeavors that are needed to address the ever-growing issues related to our nation's biological concerns. ?? 2003 by The Haworth Press, Inc. All rights reserved.

Impact of Interdisciplinary Undergraduate Research in Mathematics and Biology on the Development of a New Course Integrating Five STEM Disciplines

ERIC Educational Resources Information Center

Caudill, Lester; Hill, April; Hoke, Kathy; Lipan, Ovidiu

2010-01-01

Funded by innovative programs at the National Science Foundation and the Howard Hughes Medical Institute, University of Richmond faculty in biology, chemistry, mathematics, physics, and computer science teamed up to offer first- and second-year students the opportunity to contribute to vibrant, interdisciplinary research projects. The result was…

Analysis of Nonstationary Time Series for Biological Rhythms Research.

PubMed

Leise, Tanya L

2017-06-01

This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time. We illustrate these methods using simulated and real time series.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2016-01-01

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

Parameter Estimation and Model Selection in Computational Biology

PubMed Central

Lillacci, Gabriele; Khammash, Mustafa

2010-01-01

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

A biologically consistent hierarchical framework for self-referencing survivalist computation

NASA Astrophysics Data System (ADS)

Cottam, Ron; Ranson, Willy; Vounckx, Roger

2000-05-01

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

Integrating Mathematics into the Introductory Biology Laboratory Course

ERIC Educational Resources Information Center

White, James D.; Carpenter, Jenna P.

2008-01-01

Louisiana Tech University has an integrated science curriculum for its mathematics, chemistry, physics, computer science, biology-research track and secondary mathematics and science education majors. The curriculum focuses on the calculus sequence and introductory labs in biology, physics, and chemistry. In the introductory biology laboratory…

Computing through Scientific Abstractions in SysBioPS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, George; Stephan, Eric G.; Gracio, Deborah K.

2004-10-13

Today, biologists and bioinformaticists have a tremendous amount of computational power at their disposal. With the availability of supercomputers, burgeoning scientific databases and digital libraries such as GenBank and PubMed, and pervasive computational environments such as the Grid, biologists have access to a wealth of computational capabilities and scientific data at hand. Yet, the rapid development of computational technologies has far exceeded the typical biologist’s ability to effectively apply the technology in their research. Computational sciences research and development efforts such as the Biology Workbench, BioSPICE (Biological Simulation Program for Intra-Cellular Evaluation), and BioCoRE (Biological Collaborative Research Environment) are importantmore » in connecting biologists and their scientific problems to computational infrastructures. On the Computational Cell Environment and Heuristic Entity-Relationship Building Environment projects at the Pacific Northwest National Laboratory, we are jointly developing a new breed of scientific problem solving environment called SysBioPSE that will allow biologists to access and apply computational resources in the scientific research context. In contrast to other computational science environments, SysBioPSE operates as an abstraction layer above a computational infrastructure. The goal of SysBioPSE is to allow biologists to apply computational resources in the context of the scientific problems they are addressing and the scientific perspectives from which they conduct their research. More specifically, SysBioPSE allows biologists to capture and represent scientific concepts and theories and experimental processes, and to link these views to scientific applications, data repositories, and computer systems.« less

A Research Program in Computer Technology. 1982 Annual Technical Report

DTIC Science & Technology

1983-03-01

for the Defense Advanced Research Projects Agency. The research applies computer science and technology to areas of high DoD/ military impact. The ISI...implement the plan; New Computing Environment - investigation and adaptation of developing computer technologies to serve the research and military ...Computing Environment - ,.*_i;.;"’.)n and adaptation of developing computer technologies to serve the research and military tser communities; and Computer

Computer-Assisted Microscopy in Science Teaching and Research.

ERIC Educational Resources Information Center

Radice, Gary P.

1997-01-01

Describes a technological approach to teaching the relationships between biological form and function. Computer-assisted image analysis was integrated into a microanatomy course. Students spend less time memorizing and more time observing, measuring, and interpreting, building technical and analytical skills. Appendices list hardware and software…

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

PubMed

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.

Computational oncology.

PubMed

Lefor, Alan T

2011-08-01

Oncology research has traditionally been conducted using techniques from the biological sciences. The new field of computational oncology has forged a new relationship between the physical sciences and oncology to further advance research. By applying physics and mathematics to oncologic problems, new insights will emerge into the pathogenesis and treatment of malignancies. One major area of investigation in computational oncology centers around the acquisition and analysis of data, using improved computing hardware and software. Large databases of cellular pathways are being analyzed to understand the interrelationship among complex biological processes. Computer-aided detection is being applied to the analysis of routine imaging data including mammography and chest imaging to improve the accuracy and detection rate for population screening. The second major area of investigation uses computers to construct sophisticated mathematical models of individual cancer cells as well as larger systems using partial differential equations. These models are further refined with clinically available information to more accurately reflect living systems. One of the major obstacles in the partnership between physical scientists and the oncology community is communications. Standard ways to convey information must be developed. Future progress in computational oncology will depend on close collaboration between clinicians and investigators to further the understanding of cancer using these new approaches.

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

ERIC Educational Resources Information Center

Elangovan, Tavasuria; Ismail, Zurida

2014-01-01

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

Opportunities in plant synthetic biology.

PubMed

Cook, Charis; Martin, Lisa; Bastow, Ruth

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

Kaski, K.; Salomaa, M.

1990-01-01

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

Fundamental Biological Research on the International Space Station

NASA Technical Reports Server (NTRS)

Souza, K. A.; Yost, Bruce; Fletcher, L.; Dalton, Bonnie P. (Technical Monitor)

2000-01-01

The fundamental Biology Program of NASA's Life Sciences Division is chartered with enabling and sponsoring research on the International Space Station (ISS) in order to understand the effects of the space flight environment, particularly microgravity, on living systems. To accomplish this goal, NASA Ames Research Center (ARC) has been tasked with managing the development of a number of biological habitats, along with their support systems infrastructure. This integrated suite of habitats and support systems is being designed to support research requirements identified by the scientific community. As such, it will support investigations using cells and tissues, avian eggs, insects, plants, aquatic organisms and rodents. Studies following organisms through complete life cycles and over multiple generations will eventually be possible. As an adjunct to the development of these basic habitats, specific analytical and monitoring technologies are being targeted for maturation to complete the research cycle by transferring existing or emerging analytical techniques, sensors, and processes from the laboratory bench to the ISS research platform.

Biological and Physical Space Research Laboratory 2002 Science Review

NASA Technical Reports Server (NTRS)

Curreri, P. A. (Editor); Robinson, M. B. (Editor); Murphy, K. L. (Editor)

2003-01-01

With the International Space Station Program approaching core complete, our NASA Headquarters sponsor, the new Code U Enterprise, Biological and Physical Research, is shifting its research emphasis from purely fundamental microgravity and biological sciences to strategic research aimed at enabling human missions beyond Earth orbit. Although we anticipate supporting microgravity research on the ISS for some time to come, our laboratory has been vigorously engaged in developing these new strategic research areas.This Technical Memorandum documents the internal science research at our laboratory as presented in a review to Dr. Ann Whitaker, MSFC Science Director, in July 2002. These presentations have been revised and updated as appropriate for this report. It provides a snapshot of the internal science capability of our laboratory as an aid to other NASA organizations and the external scientific community.

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

PubMed Central

Gilbert, David

2016-01-01

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

Malaria Research

MedlinePlus

... Operations Administrative Services Office of Biodefense Research & Surety Communications Government Relations Cyber Infrastructure Computational Biology Equal Employment Opportunity Ethics Global Research Office of Mission Integration and Financial ...

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

ERIC Educational Resources Information Center

Wilder, Anna; Brinkerhoff, Jonathan

2007-01-01

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

Mixed-Methods Design in Biology Education Research: Approach and Uses

PubMed Central

Warfa, Abdi-Rizak M.

2016-01-01

Educational research often requires mixing different research methodologies to strengthen findings, better contextualize or explain results, or minimize the weaknesses of a single method. This article provides practical guidelines on how to conduct such research in biology education, with a focus on mixed-methods research (MMR) that uses both quantitative and qualitative inquiries. Specifically, the paper provides an overview of mixed-methods design typologies most relevant in biology education research. It also discusses common methodological issues that may arise in mixed-methods studies and ways to address them. The paper concludes with recommendations on how to report and write about MMR. PMID:27856556

Information technology developments within the national biological information infrastructure

USGS Publications Warehouse

Cotter, G.; Frame, M.T.

2000-01-01

Looking out an office window or exploring a community park, one can easily see the tremendous challenges that biological information presents the computer science community. Biological information varies in format and content depending whether or not it is information pertaining to a particular species (i.e. Brown Tree Snake), or a specific ecosystem, which often includes multiple species, land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993. The NBII is designed to address these issues on a National scale within the United States, and through international partnerships abroad. This paper discusses current computer science efforts within the National Biological Information Infrastructure Program and future computer science research endeavors that are needed to address the ever-growing issues related to our Nation's biological concerns.

Using Biological-Control Research in the Classroom to Promote Scientific Inquiry & Literacy

ERIC Educational Resources Information Center

Richardson, Matthew L.; Richardson, Scott L.; Hall, David G.

2012-01-01

Scientists researching biological control should engage in education because translating research programs into classroom activities is a pathway to increase scientific literacy among students. Classroom activities focused on biological control target all levels of biological organization and can be cross-disciplinary by drawing from subject areas…

Bridging Emotion Research: From Biology to Social Structure

ERIC Educational Resources Information Center

Rogers, Kimberly B.; Kavanagh, Liam

2010-01-01

Emotion research demonstrates that problems of theoretical interest or practical significance are not divided neatly along disciplinary boundaries. Researchers acknowledge both organic and social underpinnings of emotion, but the intersections between biological and structural processes can be difficult to negotiate. In this article, the authors…

The value of closed-circuit rebreathers for biological research

USGS Publications Warehouse

Pyle, Richrad L.; Lobel, Phillip S.; Tomoleoni, Joseph

2016-01-01

Closed-circuit rebreathers have been used for underwater biological research since the late 1960s, but have only started to gain broader application within scientific diving organizations within the past two decades. Rebreathers offer certain specific advantages for such research, especially for research involving behavior and surveys that depend on unobtrusive observers or for a stealthy approach to wildlife for capture and tagging, research that benefits from extended durations underwater, and operations requiring access to relatively deep (>50 m) environments (especially in remote locations). Although many institutions have been slow to adopt rebreather technology within their diving programs, recent developments in rebreather technology that improve safety, standardize training requirements, and reduce costs of equipment and maintenance, will likely result in a trend of increasing utilization of rebreathers for underwater biological research.

Biologically Enhanced Carbon Sequestration: Research Needs and Opportunities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oldenburg, Curtis; Oldenburg, Curtis M.; Torn, Margaret S.

2008-03-21

Fossil fuel combustion, deforestation, and biomass burning are the dominant contributors to increasing atmospheric carbon dioxide (CO{sub 2}) concentrations and global warming. Many approaches to mitigating CO{sub 2} emissions are being pursued, and among the most promising are terrestrial and geologic carbon sequestration. Recent advances in ecology and microbial biology offer promising new possibilities for enhancing terrestrial and geologic carbon sequestration. A workshop was held October 29, 2007, at Lawrence Berkeley National Laboratory (LBNL) on Biologically Enhanced Carbon Sequestration (BECS). The workshop participants (approximately 30 scientists from California, Illinois, Oregon, Montana, and New Mexico) developed a prioritized list of researchmore » needed to make progress in the development of biological enhancements to improve terrestrial and geologic carbon sequestration. The workshop participants also identified a number of areas of supporting science that are critical to making progress in the fundamental research areas. The purpose of this position paper is to summarize and elaborate upon the findings of the workshop. The paper considers terrestrial and geologic carbon sequestration separately. First, we present a summary in outline form of the research roadmaps for terrestrial and geologic BECS. This outline is elaborated upon in the narrative sections that follow. The narrative sections start with the focused research priorities in each area followed by critical supporting science for biological enhancements as prioritized during the workshop. Finally, Table 1 summarizes the potential significance or 'materiality' of advances in these areas for reducing net greenhouse gas emissions.« less

Biological Research in Canisters (BRIC) - Light Emitting Diode (LED)

NASA Technical Reports Server (NTRS)

Levine, Howard G.; Caron, Allison

2016-01-01

The Biological Research in Canisters - LED (BRIC-LED) is a biological research system that is being designed to complement the capabilities of the existing BRIC-Petri Dish Fixation Unit (PDFU) for the Space Life and Physical Sciences (SLPS) Program. A diverse range of organisms can be supported, including plant seedlings, callus cultures, Caenorhabditis elegans, microbes, and others. In the event of a launch scrub, the entire assembly can be replaced with an identical back-up unit containing freshly loaded specimens.

Biological modelling of a computational spiking neural network with neuronal avalanches

NASA Astrophysics Data System (ADS)

Li, Xiumin; Chen, Qing; Xue, Fangzheng

2017-05-01

In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs). In this paper, we investigated the role of the critical state in neural computations based on liquid-state machines, a biologically plausible computational neural network model for real-time computing. The computational performance of an SNN when operating at the critical state and, in particular, with spike-timing-dependent plasticity for updating synaptic weights is investigated. The network is found to show the best computational performance when it is subjected to critical dynamic states. Moreover, the active-neuron-dominant structure refined from synaptic learning can remarkably enhance the robustness of the critical state and further improve computational accuracy. These results may have important implications in the modelling of spiking neural networks with optimal computational performance. This article is part of the themed issue `Mathematical methods in medicine: neuroscience, cardiology and pathology'.

Research Programs Constituting U.S. Participation in the International Biological Program.

ERIC Educational Resources Information Center

National Academy of Sciences--National Research Council, Washington, DC. Div. of Biology and Agriculture.

The United States contribution to the International Biological Program, which aims to understand more clearly the interrelationships within ecosystems, is centered on multidisciplinary research programs investigating the biological basis of ecological productivity and human welfare. Integrated research programs have been established for the…

Current dichotomy between traditional molecular biological and omic research in cancer biology and pharmacology.

PubMed

Reinhold, William C

2015-12-10

There is currently a split within the cancer research community between traditional molecular biological hypothesis-driven and the more recent "omic" forms or research. While the molecular biological approach employs the tried and true single alteration-single response formulations of experimentation, the omic employs broad-based assay or sample collection approaches that generate large volumes of data. How to integrate the benefits of these two approaches in an efficient and productive fashion remains an outstanding issue. Ideally, one would merge the understandability, exactness, simplicity, and testability of the molecular biological approach, with the larger amounts of data, simultaneous consideration of multiple alterations, consideration of genes both of known interest along with the novel, cross-sample comparisons among cell lines and patient samples, and consideration of directed questions while simultaneously gaining exposure to the novel provided by the omic approach. While at the current time integration of the two disciplines remains problematic, attempts to do so are ongoing, and will be necessary for the understanding of the large cell line screens including the Developmental Therapeutics Program's NCI-60, the Broad Institute's Cancer Cell Line Encyclopedia, and the Wellcome Trust Sanger Institute's Cancer Genome Project, as well as the the Cancer Genome Atlas clinical samples project. Going forward there is significant benefit to be had from the integration of the molecular biological and the omic forms or research, with the desired goal being improved translational understanding and application.

An overview of bioinformatics methods for modeling biological pathways in yeast

PubMed Central

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao

2016-01-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein–protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae. In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways in S. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. PMID:26476430

Through Microgravity and Towards the Stars: Microgravity and Strategic Research at Marshall's Biological and Physical Space Research Laboratory

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2003-01-01

The Microgravity and Strategic research at Marshall s Biological and Physical Space Research Laboratory will be reviewed. The environment in orbit provides a unique opportunity to study Materials Science and Biotechnology in the absence of sedimentation and convection. There are a number of peer-selected investigations that have been selected to fly on the Space Station that have been conceived and are led by Marshall s Biological and Physical Research Laboratory s scientists. In addition to Microgravity research the Station will enable research in "Strategic" Research Areas that focus on enabling humans to live, work, and explore the solar system safely. New research in Radiation Protection, Strategic Molecular Biology, and In-Space Fabrication will be introduced.

Computational Approaches to Phenotyping

PubMed Central

Lussier, Yves A.; Liu, Yang

2007-01-01

The recent completion of the Human Genome Project has made possible a high-throughput “systems approach” for accelerating the elucidation of molecular underpinnings of human diseases, and subsequent derivation of molecular-based strategies to more effectively prevent, diagnose, and treat these diseases. Although altered phenotypes are among the most reliable manifestations of altered gene functions, research using systematic analysis of phenotype relationships to study human biology is still in its infancy. This article focuses on the emerging field of high-throughput phenotyping (HTP) phenomics research, which aims to capitalize on novel high-throughput computation and informatics technology developments to derive genomewide molecular networks of genotype–phenotype associations, or “phenomic associations.” The HTP phenomics research field faces the challenge of technological research and development to generate novel tools in computation and informatics that will allow researchers to amass, access, integrate, organize, and manage phenotypic databases across species and enable genomewide analysis to associate phenotypic information with genomic data at different scales of biology. Key state-of-the-art technological advancements critical for HTP phenomics research are covered in this review. In particular, we highlight the power of computational approaches to conduct large-scale phenomics studies. PMID:17202287

Standard Biological Parts Knowledgebase

PubMed Central

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

2011-01-01

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

Standard biological parts knowledgebase.

PubMed

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

2011-02-24

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

Argonne's Magellan Cloud Computing Research Project

ScienceCinema

Beckman, Pete

2017-12-11

Pete Beckman, head of Argonne's Leadership Computing Facility (ALCF), discusses the Department of Energy's new $32-million Magellan project, which designed to test how cloud computing can be used for scientific research. More information: http://www.anl.gov/Media_Center/News/2009/news091014a.html

Argonne's Magellan Cloud Computing Research Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beckman, Pete

Pete Beckman, head of Argonne's Leadership Computing Facility (ALCF), discusses the Department of Energy's new $32-million Magellan project, which designed to test how cloud computing can be used for scientific research. More information: http://www.anl.gov/Media_Center/News/2009/news091014a.html

Activities of the Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1994-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.

Computer Plotting Data Points in the Engine Research Building

NASA Image and Video Library

1956-09-21

A female computer plotting compressor data in the Engine Research Building at the NACA’s Lewis Flight Propulsion Laboratory. The Computing Section was introduced during World War II to relieve short-handed research engineers of some of the tedious data-taking work. The computers made the initial computations and plotted the data graphically. The researcher then analyzed the data and either summarized the findings in a report or made modifications or ran the test again. With the introduction of mechanical computer systems in the 1950s the female computers learned how to encode the punch cards. As the data processing capabilities increased, fewer female computers were needed. Many left on their own to start families, while others earned mathematical degrees and moved into advanced positions.

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

PubMed

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

Structural and Computational Biology in the Design of Immunogenic Vaccine Antigens

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Computer science security research and human subjects: emerging considerations for research ethics boards.

PubMed

Buchanan, Elizabeth; Aycock, John; Dexter, Scott; Dittrich, David; Hvizdak, Erin

2011-06-01

This paper explores the growing concerns with computer science research, and in particular, computer security research and its relationship with the committees that review human subjects research. It offers cases that review boards are likely to confront, and provides a context for appropriate consideration of such research, as issues of bots, clouds, and worms enter the discourse of human subjects review.

Advancing vector biology research: a community survey for future directions, research applications and infrastructure requirements

PubMed Central

Kohl, Alain; Pondeville, Emilie; Schnettler, Esther; Crisanti, Andrea; Supparo, Clelia; Christophides, George K.; Kersey, Paul J.; Maslen, Gareth L.; Takken, Willem; Koenraadt, Constantianus J. M.; Oliva, Clelia F.; Busquets, Núria; Abad, F. Xavier; Failloux, Anna-Bella; Levashina, Elena A.; Wilson, Anthony J.; Veronesi, Eva; Pichard, Maëlle; Arnaud Marsh, Sarah; Simard, Frédéric; Vernick, Kenneth D.

2016-01-01

Vector-borne pathogens impact public health, animal production, and animal welfare. Research on arthropod vectors such as mosquitoes, ticks, sandflies, and midges which transmit pathogens to humans and economically important animals is crucial for development of new control measures that target transmission by the vector. While insecticides are an important part of this arsenal, appearance of resistance mechanisms is increasingly common. Novel tools for genetic manipulation of vectors, use of Wolbachia endosymbiotic bacteria, and other biological control mechanisms to prevent pathogen transmission have led to promising new intervention strategies, adding to strong interest in vector biology and genetics as well as vector–pathogen interactions. Vector research is therefore at a crucial juncture, and strategic decisions on future research directions and research infrastructure investment should be informed by the research community. A survey initiated by the European Horizon 2020 INFRAVEC-2 consortium set out to canvass priorities in the vector biology research community and to determine key activities that are needed for researchers to efficiently study vectors, vector-pathogen interactions, as well as access the structures and services that allow such activities to be carried out. We summarize the most important findings of the survey which in particular reflect the priorities of researchers in European countries, and which will be of use to stakeholders that include researchers, government, and research organizations. PMID:27677378

Evolutionary Developmental Biology (Evo-Devo) Research in Latin America.

PubMed

Marcellini, Sylvain; González, Favio; Sarrazin, Andres F; Pabón-Mora, Natalia; Benítez, Mariana; Piñeyro-Nelson, Alma; Rezende, Gustavo L; Maldonado, Ernesto; Schneider, Patricia Neiva; Grizante, Mariana B; Da Fonseca, Rodrigo Nunes; Vergara-Silva, Francisco; Suaza-Gaviria, Vanessa; Zumajo-Cardona, Cecilia; Zattara, Eduardo E; Casasa, Sofia; Suárez-Baron, Harold; Brown, Federico D

2017-01-01

Famous for its blind cavefish and Darwin's finches, Latin America is home to some of the richest biodiversity hotspots of our planet. The Latin American fauna and flora inspired and captivated naturalists from the nineteenth and twentieth centuries, including such notable pioneers such as Fritz Müller, Florentino Ameghino, and Léon Croizat who made a significant contribution to the study of embryology and evolutionary thinking. But, what are the historical and present contributions of the Latin American scientific community to Evo-Devo? Here, we provide the first comprehensive overview of the Evo-Devo laboratories based in Latin America and describe current lines of research based on endemic species, focusing on body plans and patterning, systematics, physiology, computational modeling approaches, ecology, and domestication. Literature searches reveal that Evo-Devo in Latin America is still in its early days; while showing encouraging indicators of productivity, it has not stabilized yet, because it relies on few and sparsely distributed laboratories. Coping with the rapid changes in national scientific policies and contributing to solve social and health issues specific to each region are among the main challenges faced by Latin American researchers. The 2015 inaugural meeting of the Pan-American Society for Evolutionary Developmental Biology played a pivotal role in bringing together Latin American researchers eager to initiate and consolidate regional and worldwide collaborative networks. Such networks will undoubtedly advance research on the extremely high genetic and phenotypic biodiversity of Latin America, bound to be an almost infinite source of amazement and fascinating findings for the Evo-Devo community. © 2016 Wiley Periodicals, Inc.

An overview of computer viruses in a research environment

NASA Technical Reports Server (NTRS)

Bishop, Matt

1991-01-01

The threat of attack by computer viruses is in reality a very small part of a much more general threat, specifically threats aimed at subverting computer security. Here, computer viruses are examined as a malicious logic in a research and development environment. A relation is drawn between the viruses and various models of security and integrity. Current research techniques aimed at controlling the threats posed to computer systems by threatening viruses in particular and malicious logic in general are examined. Finally, a brief examination of the vulnerabilities of research and development systems that malicious logic and computer viruses may exploit is undertaken.

Demystifying computer science for molecular ecologists.

PubMed

Belcaid, Mahdi; Toonen, Robert J

2015-06-01

In this age of data-driven science and high-throughput biology, computational thinking is becoming an increasingly important skill for tackling both new and long-standing biological questions. However, despite its obvious importance and conspicuous integration into many areas of biology, computer science is still viewed as an obscure field that has, thus far, permeated into only a few of the biology curricula across the nation. A national survey has shown that lack of computational literacy in environmental sciences is the norm rather than the exception [Valle & Berdanier (2012) Bulletin of the Ecological Society of America, 93, 373-389]. In this article, we seek to introduce a few important concepts in computer science with the aim of providing a context-specific introduction aimed at research biologists. Our goal was to help biologists understand some of the most important mainstream computational concepts to better appreciate bioinformatics methods and trade-offs that are not obvious to the uninitiated. © 2015 John Wiley & Sons Ltd.

The Colorado Plateau: cultural, biological, and physical research

USGS Publications Warehouse

Cole, Kenneth L.; van Riper, Charles

2004-01-01

Stretching from the four corners of Arizona, New Mexico, Colorado, and Utah, the Colorado Plateau is a natural laboratory for a wide range of studies. This volume presents 23 original articles drawn from more than 100 research projects presented at the Sixth Biennial Conference of Research on the Colorado Plateau. This scientific gathering revolved around research, inventory, and monitoring of lands in the region. The book's contents cover management techniques for cultural, biological, and physical resources, representing collaborative efforts among federal, university, and private sector scientists and land managers. Chapters on cultural concerns cover benchmarks of modern southwestern anthropological knowledge, models of past human activity and impact of modern visitation at newly established national monuments, challenges in implementing the 1964 Wilderness Act, and opportunities for increased federal research on Native American lands. The section on biological resources comprises sixteen chapters, with coverage that ranges from mammalian biogeography to responses of elk at the urban-wildland interface. Additional biological studies include the effects of fire and grazing on vegetation; research on bald eagles at Grand Canyon and tracking wild turkeys using radio collars; and management of palentological resources. Two final chapters on physical resources consider a proposed rerouting of the Rio de Flag River in urban Flagstaff, Arizona, and an examination of past climate patterns over the Plateau, using stream flow records and tree ring data. In light of similarities in habitat and climate across the Colorado Plateau, techniques useful to particular management units have been found to be applicable in many locations. This volume highlights an abundance of research that will prove useful for all of those working in the region, as well as for others seeking comparative studies that integrate research into land management actions.

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Intelligent biology and medicine in 2015: advancing interdisciplinary education, collaboration, and data science.

PubMed

Huang, Kun; Liu, Yunlong; Huang, Yufei; Li, Lang; Cooper, Lee; Ruan, Jianhua; Zhao, Zhongming

2016-08-22

We summarize the 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) and the editorial report of the supplement to BMC Genomics. The supplement includes 20 research articles selected from the manuscripts submitted to ICIBM 2015. The conference was held on November 13-15, 2015 at Indianapolis, Indiana, USA. It included eight scientific sessions, three tutorials, four keynote presentations, three highlight talks, and a poster session that covered current research in bioinformatics, systems biology, computational biology, biotechnologies, and computational medicine.

FAIRDOMHub: a repository and collaboration environment for sharing systems biology research.

PubMed

Wolstencroft, Katherine; Krebs, Olga; Snoep, Jacky L; Stanford, Natalie J; Bacall, Finn; Golebiewski, Martin; Kuzyakiv, Rostyk; Nguyen, Quyen; Owen, Stuart; Soiland-Reyes, Stian; Straszewski, Jakub; van Niekerk, David D; Williams, Alan R; Malmström, Lars; Rinn, Bernd; Müller, Wolfgang; Goble, Carole

2017-01-04

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

Allen, Edward J

2014-06-01

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

BIOPACK: the ground controlled late access biological research facility.

PubMed

van Loon, Jack J W A

2004-03-01

Future Space Shuttle flights shall be characterized by activities necessary to further build the International Space Station, ISS. During these missions limited resources are available to conduct biological experiments in space. The Shuttles' Middeck is a very suitable place to conduct science during the ISS assembly missions or dedicated science missions. The BIOPACK, which flew its first mission during the STS-107, provides a versatile Middeck Locker based research tool for gravitational biology studies. The core facility occupies the space of only two Middeck Lockers. Experiment temperatures are controlled for bacteria, plant, invertebrate and mammalian cultures. Gravity levels and profiles can be set ranging from 0 to 2.0 x g on three independent centrifuges. This provides the experimenter with a 1.0 x g on-board reference and intermediate hypogravity and hypergravity data points to investigate e.g. threshold levels in biological responses. Temperature sensitive items can be stored in the facilities' -10 degrees C and +4 degrees C stowage areas. During STS-107 the facility also included a small glovebox (GBX) and passive temperature controlled units (PTCU). The GBX provides the experimenter with two extra levels of containment for safe sample handling. This biological research facility is a late access (L-10 hrs) laboratory, which, when reaching orbit, could automatically be starting up reducing important experiment lag-time and valuable crew time. The system is completely telecommanded when needed. During flight system parameters like temperatures, centrifuge speeds, experiment commanding or sensor readouts can be monitored and changed when needed. Although ISS provides a wide range of research facilities there is still need for an STS-based late access facility such as the BIOPACK providing experimenters with a very versatile research cabinet for biological experiments under microgravity and in-flight control conditions.

A practical workflow for making anatomical atlases for biological research.

PubMed

Wan, Yong; Lewis, A Kelsey; Colasanto, Mary; van Langeveld, Mark; Kardon, Gabrielle; Hansen, Charles

2012-01-01

The anatomical atlas has been at the intersection of science and art for centuries. These atlases are essential to biological research, but high-quality atlases are often scarce. Recent advances in imaging technology have made high-quality 3D atlases possible. However, until now there has been a lack of practical workflows using standard tools to generate atlases from images of biological samples. With certain adaptations, CG artists' workflow and tools, traditionally used in the film industry, are practical for building high-quality biological atlases. Researchers have developed a workflow for generating a 3D anatomical atlas using accessible artists' tools. They used this workflow to build a mouse limb atlas for studying the musculoskeletal system's development. This research aims to raise the awareness of using artists' tools in scientific research and promote interdisciplinary collaborations between artists and scientists. This video (http://youtu.be/g61C-nia9ms) demonstrates a workflow for creating an anatomical atlas.

Training Under-Represented Students in Biological Research at Fisk University

NASA Technical Reports Server (NTRS)

Gunasekaran, Muthukumaran

1999-01-01

The objectives of our training and research project in biology at Fisk are to motivate and train our African-American undergraduate and graduate students by (a) teaching the basic principles and applications of different biological, biochemical and biophysical research techniques; (b) providing a "hands on experience" with laboratory instrumentation (c) requiring the students to participate in the proposed research project entitled "Cyanobacterial Bioreactors for Oxygen and Ammonia Production under "CELSS" Conditions" to gain confidence in independently conducting experiments and (d) providing training in scientific data collection and presentation to peers in scientific conferences or meetings.

[New materia medica project: synthetic biology based bioactive metabolites research in medicinal plant].

PubMed

Wang, Yong

2017-03-25

In the last decade, synthetic biology research has been gradually transited from monocellular parts or devices toward more complex multicellular systems. The emerging plant synthetic biology is regarded as the "next chapter" of synthetic biology. The complex and diverse plant metabolism as the entry point, plant synthetic biology research not only helps us understand how real life is working, but also facilitates us to learn how to design and construct more complex artificial life. Bioactive compounds innovation and large-scale production are expected to be breakthrough with the redesigned plant metabolism as well. In this review, we discuss the research progress in plant synthetic biology and propose the new materia medica project to lift the level of traditional Chinese herbal medicine research.

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

PubMed Central

Bentley, Peter J.

2009-01-01

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

Biological modelling of a computational spiking neural network with neuronal avalanches.

PubMed

Li, Xiumin; Chen, Qing; Xue, Fangzheng

2017-06-28

In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs). In this paper, we investigated the role of the critical state in neural computations based on liquid-state machines, a biologically plausible computational neural network model for real-time computing. The computational performance of an SNN when operating at the critical state and, in particular, with spike-timing-dependent plasticity for updating synaptic weights is investigated. The network is found to show the best computational performance when it is subjected to critical dynamic states. Moreover, the active-neuron-dominant structure refined from synaptic learning can remarkably enhance the robustness of the critical state and further improve computational accuracy. These results may have important implications in the modelling of spiking neural networks with optimal computational performance.This article is part of the themed issue 'Mathematical methods in medicine: neuroscience, cardiology and pathology'. © 2017 The Author(s).

Publication Bias in Methodological Computational Research.

PubMed

Boulesteix, Anne-Laure; Stierle, Veronika; Hapfelmeier, Alexander

2015-01-01

The problem of publication bias has long been discussed in research fields such as medicine. There is a consensus that publication bias is a reality and that solutions should be found to reduce it. In methodological computational research, including cancer informatics, publication bias may also be at work. The publication of negative research findings is certainly also a relevant issue, but has attracted very little attention to date. The present paper aims at providing a new formal framework to describe the notion of publication bias in the context of methodological computational research, facilitate and stimulate discussions on this topic, and increase awareness in the scientific community. We report an exemplary pilot study that aims at gaining experiences with the collection and analysis of information on unpublished research efforts with respect to publication bias, and we outline the encountered problems. Based on these experiences, we try to formalize the notion of publication bias.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology.

PubMed

Goff, Stephen A; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B S; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M; Cranston, Karen A; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J; White, Jeffery W; Leebens-Mack, James; Donoghue, Michael J; Spalding, Edgar P; Vision, Todd J; Myers, Christopher R; Lowenthal, David; Enquist, Brian J; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

PubMed Central

Goff, Stephen A.; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E.; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H.; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B. S.; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M.; Cranston, Karen A.; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J.; White, Jeffery W.; Leebens-Mack, James; Donoghue, Michael J.; Spalding, Edgar P.; Vision, Todd J.; Myers, Christopher R.; Lowenthal, David; Enquist, Brian J.; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services. PMID:22645531

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

PubMed

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.

Computational structural mechanics methods research using an evolving framework

NASA Technical Reports Server (NTRS)

Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.

1990-01-01

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

An overview of bioinformatics methods for modeling biological pathways in yeast.

PubMed

Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

2016-03-01

The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Applying systems biology methods to the study of human physiology in extreme environments

PubMed Central

2013-01-01

Systems biology is defined in this review as ‘an iterative process of computational model building and experimental model revision with the aim of understanding or simulating complex biological systems’. We propose that, in practice, systems biology rests on three pillars: computation, the omics disciplines and repeated experimental perturbation of the system of interest. The number of ethical and physiologically relevant perturbations that can be used in experiments on healthy humans is extremely limited and principally comprises exercise, nutrition, infusions (e.g. Intralipid), some drugs and altered environment. Thus, we argue that systems biology and environmental physiology are natural symbionts for those interested in a system-level understanding of human biology. However, despite excellent progress in high-altitude genetics and several proteomics studies, systems biology research into human adaptation to extreme environments is in its infancy. A brief description and overview of systems biology in its current guise is given, followed by a mini review of computational methods used for modelling biological systems. Special attention is given to high-altitude research, metabolic network reconstruction and constraint-based modelling. PMID:23849719

Computer architectures for computational physics work done by Computational Research and Technology Branch and Advanced Computational Concepts Group

NASA Technical Reports Server (NTRS)

1985-01-01

Slides are reproduced that describe the importance of having high performance number crunching and graphics capability. They also indicate the types of research and development underway at Ames Research Center to ensure that, in the near term, Ames is a smart buyer and user, and in the long-term that Ames knows the best possible solutions for number crunching and graphics needs. The drivers for this research are real computational physics applications of interest to Ames and NASA. They are concerned with how to map the applications, and how to maximize the physics learned from the results of the calculations. The computer graphics activities are aimed at getting maximum information from the three-dimensional calculations by using the real time manipulation of three-dimensional data on the Silicon Graphics workstation. Work is underway on new algorithms that will permit the display of experimental results that are sparse and random, the same way that the dense and regular computed results are displayed.

Open-Source Software in Computational Research: A Case Study

DOE PAGES

Syamlal, Madhava; O'Brien, Thomas J.; Benyahia, Sofiane; ...

2008-01-01

A case study of open-source (OS) development of the computational research software MFIX, used for multiphase computational fluid dynamics simulations, is presented here. The verification and validation steps required for constructing modern computational software and the advantages of OS development in those steps are discussed. The infrastructure used for enabling the OS development of MFIX is described. The impact of OS development on computational research and education in gas-solids flow, as well as the dissemination of information to other areas such as geophysical and volcanology research, is demonstrated. This study shows that the advantages of OS development were realized inmore » the case of MFIX: verification by many users, which enhances software quality; the use of software as a means for accumulating and exchanging information; the facilitation of peer review of the results of computational research.« less

United States Department of Agriculture-Agricultural Research Service research on biological control of arthropods.

PubMed

Hopper, Keith R

2003-01-01

During 1999-2001, ARS scientists published over 100 papers on more than 30 species of insect pest and 60 species of predator and parasitoid. These papers address issues crucial to the three strategies of biological control: conservation, augmentation and introduction. Conservation biological control includes both conserving extant populations of natural enemies by using relatively non-toxic pesticides and increasing the abundance of natural enemies in crops by providing or improving refuges for population growth and dispersal into crops. ARS scientists have been very active in determining the effects of pesticides on beneficial arthropods and in studying movement of natural enemies from refuges into crops. Augmentation involves repeated releases of natural enemies in the field, which can be inoculative or inundative. Inoculative releases are used to initiate self-propagating populations at times or in places where they would be slow to colonize. ARS scientists have studied augmentative biological control of a variety of pest insects. The targets are mostly pests in annual crops or other ephemeral habitats, where self-reproducing populations of natural enemies are not sufficiently abundant early enough to keep pest populations in check. ARS research in augmentative biological control centers on methods for rearing large numbers of healthy, effective natural enemies and for releasing them where and when they are needed at a cost less than the value of the reduction in damage to the crop. ARS scientists have researched various aspects of introductions of exotic biological control agents against a diversity of pest insects. The major issues in biological control introductions are accurate identification and adequate systematics of both natural enemies and target pests, exploration for natural enemies, predicting the success of candidates for introduction and the likelihood of non-target impacts, quarantine and rearing methods, and post-introduction evaluation of

The Increasing Urgency for Standards in Basic Biological Research

PubMed Central

Freedman, Leonard P.; Inglese, James

2016-01-01

Research advances build upon the validity and reproducibility of previously published data and findings. Yet irreproducibility in basic biological and preclinical research is pervasive in both academic and commercial settings. Lack of reproducibility has led to invalidated research breakthroughs, retracted papers, and aborted clinical trials. Concerns and requirements for transparent, reproducible, and translatable research are accelerated by the rapid growth of “post-publication peer review,” open access publishing, and data sharing that facilitate the identification of irreproducible data/studies; they are magnified by the explosion of high-throughput technologies, genomics, and other data-intensive disciplines. Collectively, these changes and challenges are decreasing the effectiveness of traditional research quality mechanisms and are contributing to unacceptable—and unsustainable—levels of irreproducibility. The global oncology and basic biological research communities can no longer tolerate or afford widespread irreproducible research. This article discusses (1) how irreproducibility in preclinical research can ultimately be traced to an absence of a unifying life science standards framework, and (2) makes an urgent case for the expanded development and use of consensus-based standards to both enhance reproducibility and drive innovations in cancer research. PMID:25035389

Space Station Biological Research Project

NASA Technical Reports Server (NTRS)

Johnson, Catherine C.; Hargens, Alan R.; Wade, Charles E.

1995-01-01

NASA Ames Research Center is responsible for the development of the Space Station Biological Research Project (SSBRP) which will support non-human life sciences research on the International Space Station Alpha (ISSA). The SSBRP is designed to support both basic research to understand the effect of altered gravity fields on biological systems and applied research to investigate the effects of space flight on biological systems. The SSBRP will provide the necessary habitats to support avian and reptile eggs, cells and tissues, plants and rodents. In addition a habitat to support aquatic specimens will be provided by our international partners. Habitats will be mounted in ISSA compatible racks at u-g and will also be mounted on a 2.5 m diameter centrifuge except for the egg incubator which has an internal centrifuge. The 2.5 m centrifuge will provide artificial gravity levels over the range of 0.01 G to 2 G. The current schedule is to launch the first rack in 1999, the Life Sciences glovebox and a second rack early in 2001, a 4 habitat 2.5 in centrifuge later the same year in its own module, and to upgrade the centrifuge to 8 habitats in 2004. The rodent habitats will be derived from the Advanced Animal Habitat currently under development for the Shuttle program and will be capable of housing either rats or mice individually or in groups (6 rats/group and at least 12 mice/group). The egg incubator will be an upgraded Avian Development Facility also developed for the Shuttle program through a Small Business and Innovative Research grant. The Space Tissue Loss cell culture apparatus, developed by Walter Reed Army Institute of Research, is being considered for the cell and tissue culture habitat. The Life Sciences Glovebox is crucial to all life sciences experiments for specimen manipulation and performance of science procedures. It will provide two levels of containment between the work volume and the crew through the use of seals and negative pressure. The glovebox

Computational fluid dynamics research at the United Technologies Research Center requiring supercomputers

NASA Technical Reports Server (NTRS)

Landgrebe, Anton J.

1987-01-01

An overview of research activities at the United Technologies Research Center (UTRC) in the area of Computational Fluid Dynamics (CFD) is presented. The requirement and use of various levels of computers, including supercomputers, for the CFD activities is described. Examples of CFD directed toward applications to helicopters, turbomachinery, heat exchangers, and the National Aerospace Plane are included. Helicopter rotor codes for the prediction of rotor and fuselage flow fields and airloads were developed with emphasis on rotor wake modeling. Airflow and airload predictions and comparisons with experimental data are presented. Examples are presented of recent parabolized Navier-Stokes and full Navier-Stokes solutions for hypersonic shock-wave/boundary layer interaction, and hydrogen/air supersonic combustion. In addition, other examples of CFD efforts in turbomachinery Navier-Stokes methodology and separated flow modeling are presented. A brief discussion of the 3-tier scientific computing environment is also presented, in which the researcher has access to workstations, mid-size computers, and supercomputers.

Computational fluid dynamics research at the United Technologies Research Center requiring supercomputers

NASA Astrophysics Data System (ADS)

Landgrebe, Anton J.

1987-03-01

An overview of research activities at the United Technologies Research Center (UTRC) in the area of Computational Fluid Dynamics (CFD) is presented. The requirement and use of various levels of computers, including supercomputers, for the CFD activities is described. Examples of CFD directed toward applications to helicopters, turbomachinery, heat exchangers, and the National Aerospace Plane are included. Helicopter rotor codes for the prediction of rotor and fuselage flow fields and airloads were developed with emphasis on rotor wake modeling. Airflow and airload predictions and comparisons with experimental data are presented. Examples are presented of recent parabolized Navier-Stokes and full Navier-Stokes solutions for hypersonic shock-wave/boundary layer interaction, and hydrogen/air supersonic combustion. In addition, other examples of CFD efforts in turbomachinery Navier-Stokes methodology and separated flow modeling are presented. A brief discussion of the 3-tier scientific computing environment is also presented, in which the researcher has access to workstations, mid-size computers, and supercomputers.

Research on Computers in Mathematics Education, IV. The Use of Computers in Mathematics Education Resource Series.

ERIC Educational Resources Information Center

Kieren, Thomas E.

This last paper in a set of four reviews research on a wide variety of computer applications in the mathematics classroom. It covers computer-based instruction, especially drill-and-practice and tutorial modes; computer-managed instruction; and computer-augmented problem-solving. Analytical comments on the findings and status of the research are…

Research in applied mathematics, numerical analysis, and computer science

NASA Technical Reports Server (NTRS)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Low-gravity Orbiting Research Laboratory Environment Potential Impact on Space Biology Research

NASA Technical Reports Server (NTRS)

Jules, Kenol

2006-01-01

One of the major objectives of any orbital space research platform is to provide a quiescent low gravity, preferably a zero gravity environment, to perform fundamental as well as applied research. However, small disturbances exist onboard any low earth orbital research platform. The impact of these disturbances must be taken into account by space research scientists during their research planning, design and data analysis in order to avoid confounding factors in their science results. The reduced gravity environment of an orbiting research platform in low earth orbit is a complex phenomenon. Many factors, among others, such as experiment operations, equipment operation, life support systems and crew activity (if it is a crewed platform), aerodynamic drag, gravity gradient, rotational effects as well as the vehicle structural resonance frequencies (structural modes) contribute to form the overall reduced gravity environment in which space research is performed. The contribution of these small disturbances or accelerations is precisely why the environment is NOT a zero gravity environment, but a reduced acceleration environment. This paper does not discuss other factors such as radiation, electromagnetic interference, thermal and pressure gradient changes, acoustic and CO2 build-up to name a few that affect the space research environment as well, but it focuses solely on the magnitude of the acceleration level found on orbiting research laboratory used by research scientists to conduct space research. For ease of analysis this paper divides the frequency spectrum relevant to most of the space research disciplines into three regimes: a) quasi-steady, b) vibratory and c) transient. The International Space Station is used as an example to illustrate the point. The paper discusses the impact of these three regimes on space biology research and results from space flown experiments are used to illustrate the potential negative impact of these disturbances (accelerations

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

PubMed

Singh, Rahul; Yang, Hui; Dalziel, Ben; Asarnow, Daniel; Murad, William; Foote, David; Gormley, Matthew; Stillman, Jonathan; Fisher, Susan

2013-01-01

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

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

PubMed Central

2013-01-01

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

ISCB: past-present perspective for the International Society for Computational Biology.

PubMed

Rost, Burkhard