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

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

Arkin, Adam; Bader, David C.; Coffey, Richard

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

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…

Graduate Training at the Interface of Computational and Experimental Biology: An Outcome Report from a Partnership of Volunteers between a University and a National Laboratory.

PubMed

von Arnim, Albrecht G; Missra, Anamika

2017-01-01

Leading voices in the biological sciences have called for a transformation in graduate education leading to the PhD degree. One area commonly singled out for growth and innovation is cross-training in computational science. In 1998, the University of Tennessee (UT) founded an intercollegiate graduate program called the UT-ORNL Graduate School of Genome Science and Technology in partnership with the nearby Oak Ridge National Laboratory. Here, we report outcome data that attest to the program's effectiveness in graduating computationally enabled biologists for diverse careers. Among 77 PhD graduates since 2003, the majority came with traditional degrees in the biological sciences, yet two-thirds moved into computational or hybrid (computational-experimental) positions. We describe the curriculum of the program and how it has changed. We also summarize how the program seeks to establish cohesion between computational and experimental biologists. This type of program can respond flexibly and dynamically to unmet training needs. In conclusion, this study from a flagship, state-supported university may serve as a reference point for creating a stable, degree-granting, interdepartmental graduate program in computational biology and allied areas. © 2017 A. G. von Arnim and A. Missra. CBE—Life Sciences Education © 2017 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).

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

Hules, John

This 1998 annual report from the National Scientific Energy Research Computing Center (NERSC) presents the year in review of the following categories: Computational Science; Computer Science and Applied Mathematics; and Systems and Services. Also presented are science highlights in the following categories: Basic Energy Sciences; Biological and Environmental Research; Fusion Energy Sciences; High Energy and Nuclear Physics; and Advanced Scientific Computing Research and Other Projects.

Focus issue: series on computational and systems biology.

PubMed

Gough, Nancy R

2011-09-06

The application of computational biology and systems biology is yielding quantitative insight into cellular regulatory phenomena. For the month of September, Science Signaling highlights research featuring computational approaches to understanding cell signaling and investigation of signaling networks, a series of Teaching Resources from a course in systems biology, and various other articles and resources relevant to the application of computational biology and systems biology to the study of signal transduction.

ISMB 2016 offers outstanding science, networking, and celebration

PubMed Central

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392

ISMB 2016 offers outstanding science, networking, and celebration.

PubMed

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Graduate Training at the Interface of Computational and Experimental Biology: An Outcome Report from a Partnership of Volunteers between a University and a National Laboratory

PubMed Central

von Arnim, Albrecht G.; Missra, Anamika

2017-01-01

Leading voices in the biological sciences have called for a transformation in graduate education leading to the PhD degree. One area commonly singled out for growth and innovation is cross-training in computational science. In 1998, the University of Tennessee (UT) founded an intercollegiate graduate program called the UT-ORNL Graduate School of Genome Science and Technology in partnership with the nearby Oak Ridge National Laboratory. Here, we report outcome data that attest to the program’s effectiveness in graduating computationally enabled biologists for diverse careers. Among 77 PhD graduates since 2003, the majority came with traditional degrees in the biological sciences, yet two-thirds moved into computational or hybrid (computational–experimental) positions. We describe the curriculum of the program and how it has changed. We also summarize how the program seeks to establish cohesion between computational and experimental biologists. This type of program can respond flexibly and dynamically to unmet training needs. In conclusion, this study from a flagship, state-supported university may serve as a reference point for creating a stable, degree-granting, interdepartmental graduate program in computational biology and allied areas. PMID:29167223

Computers in Science: Thinking Outside the Discipline.

ERIC Educational Resources Information Center

Hamilton, Todd M.

2003-01-01

Describes the Computers in Science course which integrates computer-related techniques into the science disciplines of chemistry, physics, biology, and Earth science. Uses a team teaching approach and teaches students how to solve chemistry problems with spreadsheets, identify minerals with X-rays, and chemical and force analysis. (Contains 14…

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 ...

Visualising "Junk" DNA through Bioinformatics

ERIC Educational Resources Information Center

Elwess, Nancy L.; Latourelle, Sandra M.; Cauthorn, Olivia

2005-01-01

One of the hottest areas of science today is the field in which biology, information technology,and computer science are merged into a single discipline called bioinformatics. This field enables the discovery and analysis of biological data, including nucleotide and amino acid sequences that are easily accessed through the use of computers. As…

BASIC Simulation Programs; Volumes I and II. Biology, Earth Science, Chemistry.

ERIC Educational Resources Information Center

Digital Equipment Corp., Maynard, MA.

Computer programs which teach concepts and processes related to biology, earth science, and chemistry are presented. The seven biology problems deal with aspects of genetics, evolution and natural selection, gametogenesis, enzymes, photosynthesis, and the transport of material across a membrane. Four earth science problems concern climates, the…

Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges.

PubMed

Stein, Lincoln D

2008-09-01

Biology is an information-driven science. Large-scale data sets from genomics, physiology, population genetics and imaging are driving research at a dizzying rate. Simultaneously, interdisciplinary collaborations among experimental biologists, theorists, statisticians and computer scientists have become the key to making effective use of these data sets. However, too many biologists have trouble accessing and using these electronic data sets and tools effectively. A 'cyberinfrastructure' is a combination of databases, network protocols and computational services that brings people, information and computational tools together to perform science in this information-driven world. This article reviews the components of a biological cyberinfrastructure, discusses current and pending implementations, and notes the many challenges that lie ahead.

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.

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators

PubMed Central

2017-01-01

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology. PMID:29049281

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators.

PubMed

Barone, Lindsay; Williams, Jason; Micklos, David

2017-10-01

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC-acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.

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 their instruction. The results are of interest to science teachers, those whose decisions affect the meaningful integration of technology in science education, those researching the teaching of science in secondary schools and those who prepare science graduates to teach at this level. Key Words: innovation, laptop, computer, biology, science, secondary, implementation, perceptions, instruction, professional development, qualitative, descriptive.

Bioinformatics in high school biology curricula: a study of state science standards.

PubMed

Wefer, Stephen H; Sheppard, Keith

2008-01-01

The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics content of each state's biology standards was analyzed and categorized into nine areas: Human Genome Project/genomics, forensics, evolution, classification, nucleotide variations, medicine, computer use, agriculture/food technology, and science technology and society/socioscientific issues. Findings indicated a generally low representation of bioinformatics-related content, which varied substantially across the different areas, with Human Genome Project/genomics and computer use being the lowest (8%), and evolution being the highest (64%) among states' science frameworks. This essay concludes with recommendations for reworking/rewording existing standards to facilitate the goal of promoting science literacy among secondary school students.

Bioinformatics in High School Biology Curricula: A Study of State Science Standards

PubMed Central

Sheppard, Keith

2008-01-01

The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics content of each state's biology standards was analyzed and categorized into nine areas: Human Genome Project/genomics, forensics, evolution, classification, nucleotide variations, medicine, computer use, agriculture/food technology, and science technology and society/socioscientific issues. Findings indicated a generally low representation of bioinformatics-related content, which varied substantially across the different areas, with Human Genome Project/genomics and computer use being the lowest (8%), and evolution being the highest (64%) among states' science frameworks. This essay concludes with recommendations for reworking/rewording existing standards to facilitate the goal of promoting science literacy among secondary school students. PMID:18316818

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.

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.

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).

Partly cloudy with a chance of migration: Weather, radars, and aeroecology

USDA-ARS?s Scientific Manuscript database

Aeroecology is an emerging scientific discipline that integrates atmospheric science, terrestrial science, geography, ecology, computer science, computational biology, and engineering to further the understanding of ecological patterns and processes. The unifying concept underlying this new transdis...

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…

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.

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

NASA Astrophysics Data System (ADS)

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-10-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach. This study describes and evaluates a computer-based simulation to train advanced placement high school science students in laboratory protocols, a transgenic mouse model was produced. A simulation module on preparing a gene construct in the molecular biology lab was evaluated using a randomized clinical control design with advanced placement high school biology students in Mercedes, Texas ( n = 44). Pre-post tests assessed procedural and declarative knowledge, time on task, attitudes toward computers for learning and towards science careers. Students who used the simulation increased their procedural and declarative knowledge regarding molecular biology compared to those in the control condition (both p < 0.005). Significant increases continued to occur with additional use of the simulation ( p < 0.001). Students in the treatment group became more positive toward using computers for learning ( p < 0.001). The simulation did not significantly affect attitudes toward science in general. Computer simulation of complex transgenic protocols have potential to provide a "virtual" laboratory experience as an adjunct to conventional educational approaches.

Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo.

PubMed

Kawano, Tomonori; Bouteau, François; Mancuso, Stefano

2012-11-01

The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed.

Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo

PubMed Central

Kawano, Tomonori; Bouteau, François; Mancuso, Stefano

2012-01-01

The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed. PMID:23336016

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.

A Computer-Based Instrument That Identifies Common Science Misconceptions

ERIC Educational Resources Information Center

Larrabee, Timothy G.; Stein, Mary; Barman, Charles

2006-01-01

This article describes the rationale for and development of a computer-based instrument that helps identify commonly held science misconceptions. The instrument, known as the Science Beliefs Test, is a 47-item instrument that targets topics in chemistry, physics, biology, earth science, and astronomy. The use of an online data collection system…

The Effect of a Computer Program Designed with Constructivist Principles for College Non-Science Majors on Understanding of Photosynthesis and Cellular Respiration

ERIC Educational Resources Information Center

Wielard, Valerie Michelle

2013-01-01

The primary objective of this project was to learn what effect a computer program would have on academic achievement and attitude toward science of college students enrolled in a biology class for non-science majors. It became apparent that the instructor also had an effect on attitudes toward science. The researcher designed a computer program,…

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Biological mechanisms beyond network analysis via mathematical modeling. Comment on "Network science of biological systems at different scales: A review" by Marko Gosak et al.

NASA Astrophysics Data System (ADS)

Pedersen, Morten Gram

2018-03-01

Methods from network theory are increasingly used in research spanning from engineering and computer science to psychology and the social sciences. In this issue, Gosak et al. [1] provide a thorough review of network science applications to biological systems ranging from the subcellular world via neuroscience to ecosystems, with special attention to the insulin-secreting beta-cells in pancreatic islets.

Primary and Secondary School Science.

ERIC Educational Resources Information Center

Educational Documentation and Information, 1984

1984-01-01

This 344-item annotated bibliography presents overview of science teaching in following categories: science education; primary school science; integrated science teaching; teaching of biology, chemistry, physics, earth/space science; laboratory work; computer technology; out-of-school science; science and society; science education at…

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1983

1983-01-01

Highlights important 1983 news stories reported in Science News. Stories are categorized under: anthropology/paleontology; behavior; biology; chemistry; earth sciences; energy; environment; medicine; physics; science and society; space sciences and astronomy; and technology and computers. (JN)

Graduate Training at the Interface of Computational and Experimental Biology: An Outcome Report from a Partnership of Volunteers between a University and a National Laboratory

ERIC Educational Resources Information Center

von Arnim, Albrecht G.; Missra, Anamika

2017-01-01

Leading voices in the biological sciences have called for a transformation in graduate education leading to the PhD degree. One area commonly singled out for growth and innovation is cross-training in computational science. In 1998, the University of Tennessee (UT) founded an intercollegiate graduate program called the UT-ORNL Graduate School of…

European Science Notes Information Bulletin, October 1988

DTIC Science & Technology

1988-10-01

D TIC Biological Sciences .................... 18 ELECTE Computer Sciences .................... 20 SP 2 5i Control Systems .............. ..... . . 24...of his research on the impact of frequent relocation on families and the individuals subject to such experience. BIOLOGICAL SCIENCES Imaging Cerebral... Bioethics : A seminar was held in Brussels to study the the Ministers also exchanged views on: various ethical aspects of biotechnology and genetic

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...

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…

A Portable Bioinformatics Course for Upper-Division Undergraduate Curriculum in Sciences

ERIC Educational Resources Information Center

Floraino, Wely B.

2008-01-01

This article discusses the challenges that bioinformatics education is facing and describes a bioinformatics course that is successfully taught at the California State Polytechnic University, Pomona, to the fourth year undergraduate students in biological sciences, chemistry, and computer science. Information on lecture and computer practice…

Combining Art and Science in "Arts and Sciences" Education

ERIC Educational Resources Information Center

Needle, Andrew; Corbo, Christopher; Wong, Denise; Greenfeder, Gary; Raths, Linda; Fulop, Zoltan

2007-01-01

Two of this article's authors--an art professor and a biology professor--shared a project for advanced biology, art, nursing, and computer science majors involving scientific research that used digital imaging of the brain of the zebrafish, a newly favored laboratory animal. These contemporary and innovative teaching and learning practices were a…

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.

Synthetic Biology: Knowledge Accessed by Everyone (Open Sources)

ERIC Educational Resources Information Center

Sánchez Reyes, Patricia Margarita

2016-01-01

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

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1988

1988-01-01

Reviews major science news stories of 1988 as reported in the pages of Science News. Covers the areas of anthropology, astronomy, behavior, biology, biomedicine, chemistry, earth sciences, environment, food science, mathematics and computers, paleobiology, physics, science and society, space sciences, and technology. (YP)

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1985

1985-01-01

Highlights important 1985 science stories appearing in "Science News" under these headings: anthropology and paleontology, astronomy, behavior, biology, biomedicine, chemistry, computers and mathematics, earth sciences, environment, physics, science and society, space sciences, and technology. Each entry includes the volume and page…

Employee Spotlight: Clarence Chang | Argonne National Laboratory

Science.gov Websites

batteries --Electricity transmission --Smart Grid Environment -Biology --Computational biology --Environmental biology ---Metagenomics ---Terrestrial ecology --Molecular biology ---Clinical proteomics and biomarker discovery ---Interventional biology ---Proteomics --Structural biology -Environmental science &

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.

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)

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.

Non-parallel processing: Gendered attrition in academic computer science

NASA Astrophysics Data System (ADS)

Cohoon, Joanne Louise Mcgrath

2000-10-01

This dissertation addresses the issue of disproportionate female attrition from computer science as an instance of gender segregation in higher education. By adopting a theoretical framework from organizational sociology, it demonstrates that the characteristics and processes of computer science departments strongly influence female retention. The empirical data identifies conditions under which women are retained in the computer science major at comparable rates to men. The research for this dissertation began with interviews of students, faculty, and chairpersons from five computer science departments. These exploratory interviews led to a survey of faculty and chairpersons at computer science and biology departments in Virginia. The data from these surveys are used in comparisons of the computer science and biology disciplines, and for statistical analyses that identify which departmental characteristics promote equal attrition for male and female undergraduates in computer science. This three-pronged methodological approach of interviews, discipline comparisons, and statistical analyses shows that departmental variation in gendered attrition rates can be explained largely by access to opportunity, relative numbers, and other characteristics of the learning environment. Using these concepts, this research identifies nine factors that affect the differential attrition of women from CS departments. These factors are: (1) The gender composition of enrolled students and faculty; (2) Faculty turnover; (3) Institutional support for the department; (4) Preferential attitudes toward female students; (5) Mentoring and supervising by faculty; (6) The local job market, starting salaries, and competitiveness of graduates; (7) Emphasis on teaching; and (8) Joint efforts for student success. This work contributes to our understanding of the gender segregation process in higher education. In addition, it contributes information that can lead to effective solutions for an economically significant issue in modern American society---gender equality in computer science.

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1989

1989-01-01

Presented is a review of important science news stories of 1989 as reported in the pages of "Science News." Topics include anthropology, astronomy, behavior, biology, biomedicine, chemistry, environment, food science, math and computers, paleobiology, physics, science and society, space sciences, and technology. (CW)

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1984

1984-01-01

Reviews important science news stories reported during 1984 in "Science News" magazine. These stories are in the categories of: anthropology and paleontology; behavior; biology; chemistry; computers; mathematics; earth science; the environment; medicine; physics; science and society; space sciences and astronomy; and technology. (JN)

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

BioSIGHT: Interactive Visualization Modules for Science Education

NASA Technical Reports Server (NTRS)

Wong, Wee Ling

1998-01-01

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.

Systems Biology and Cancer Prevention: All Options on the Table

PubMed Central

Rosenfeld, Simon; Kapetanovic, Izet

2008-01-01

In this paper, we outline the status quo and approaches to further development of the systems biology concepts with focus on applications in cancer prevention science. We discuss the biological aspects of cancer research that are of primary importance in cancer prevention, motivations for their mathematical modeling and some recent advances in computational oncology. We also make an attempt to outline in big conceptual terms the contours of future work aimed at creation of large-scale computational and informational infrastructure for using as a routine tool in cancer prevention science and decision making. PMID:19787092

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.

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1990

1990-01-01

This is a review of important science news stories of 1990 as reported in the pages of this journal. Areas covered include anthropology, astronomy, behavior, biology, biomedicine, chemistry, computers and math, earth sciences, environment, food science, materials science, paleobiology, physics, science and society, and space sciences. (CW)

Crossing over...Markov meets Mendel.

PubMed

Mneimneh, Saad

2012-01-01

Chromosomal crossover is a biological mechanism to combine parental traits. It is perhaps the first mechanism ever taught in any introductory biology class. The formulation of crossover, and resulting recombination, came about 100 years after Mendel's famous experiments. To a great extent, this formulation is consistent with the basic genetic findings of Mendel. More importantly, it provides a mathematical insight for his two laws (and corrects them). From a mathematical perspective, and while it retains similarities, genetic recombination guarantees diversity so that we do not rapidly converge to the same being. It is this diversity that made the study of biology possible. In particular, the problem of genetic mapping and linkage-one of the first efforts towards a computational approach to biology-relies heavily on the mathematical foundation of crossover and recombination. Nevertheless, as students we often overlook the mathematics of these phenomena. Emphasizing the mathematical aspect of Mendel's laws through crossover and recombination will prepare the students to make an early realization that biology, in addition to being experimental, IS a computational science. This can serve as a first step towards a broader curricular transformation in teaching biological sciences. I will show that a simple and modern treatment of Mendel's laws using a Markov chain will make this step possible, and it will only require basic college-level probability and calculus. My personal teaching experience confirms that students WANT to know Markov chains because they hear about them from bioinformaticists all the time. This entire exposition is based on three homework problems that I designed for a course in computational biology. A typical reader is, therefore, an instructional staff member or a student in a computational field (e.g., computer science, mathematics, statistics, computational biology, bioinformatics). However, other students may easily follow by omitting the mathematically more elaborate parts. I kept those as separate sections in the exposition.

Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

ERIC Educational Resources Information Center

Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

2016-01-01

In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

Slime mould biotechnology

NASA Astrophysics Data System (ADS)

Mayne, Richard

2015-03-01

Slime mould computing is an inherently multi-disciplinary subfield of unconventional computing that draws upon aspects of not only theoretical computer science and electronics, but also the natural sciences. This chapter focuses on the biology of slime moulds and expounds the viewpoint that a deep, intuitive understanding of slime mould life processes is a fundamental requirement for understanding -- and, hence, harnessing -- the incredible behaviour patterns we may characterise as "computation"...

Computational biology and bioinformatics in Nigeria.

PubMed

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

2014-04-01

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

Computational Biology and Bioinformatics in Nigeria

PubMed Central

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

2014-01-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310

Information Science Research: The Search for the Nature of Information.

ERIC Educational Resources Information Center

Kochen, Manfred

1984-01-01

High-level scientific research in the information sciences is illustrated by sampling of recent discoveries involving adaptive information processing strategies, computer and information systems, centroid scaling, economic growth of computer and communication industries, and information flow in biological systems. Relationship of information…

Bioinformatics.

PubMed

Moore, Jason H

2007-11-01

Bioinformatics is an interdisciplinary field that blends computer science and biostatistics with biological and biomedical sciences such as biochemistry, cell biology, developmental biology, genetics, genomics, and physiology. An important goal of bioinformatics is to facilitate the management, analysis, and interpretation of data from biological experiments and observational studies. The goal of this review is to introduce some of the important concepts in bioinformatics that must be considered when planning and executing a modern biological research study. We review database resources as well as data mining software tools.

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…

Three-Dimensional Printing of Human Skeletal Muscle Cells: An Interdisciplinary Approach for Studying Biological Systems

ERIC Educational Resources Information Center

Bagley, James R.; Galpin, Andrew J.

2015-01-01

Interdisciplinary exploration is vital to education in the 21st century. This manuscript outlines an innovative laboratory-based teaching method that combines elements of biochemistry/molecular biology, kinesiology/health science, computer science, and manufacturing engineering to give students the ability to better conceptualize complex…

Students from Pueblo Triumph in Colorado Science Bowl

Science.gov Websites

questions about physics, math, biology, astronomy, chemistry, computers and the earth sciences, students science and math. The competition has evolved into one of the Energy Department's premier educational

Students from Aurora Triumph in Denver Regional Science Bowl

Science.gov Websites

questions about physics, math, biology, astronomy, chemistry, computers and the earth sciences, students science and math. The competition has evolved into one of the Energy Department's premier educational

Bio and health informatics meets cloud : BioVLab as an example.

PubMed

Chae, Heejoon; Jung, Inuk; Lee, Hyungro; Marru, Suresh; Lee, Seong-Whan; Kim, Sun

2013-01-01

The exponential increase of genomic data brought by the advent of the next or the third generation sequencing (NGS) technologies and the dramatic drop in sequencing cost have driven biological and medical sciences to data-driven sciences. This revolutionary paradigm shift comes with challenges in terms of data transfer, storage, computation, and analysis of big bio/medical data. Cloud computing is a service model sharing a pool of configurable resources, which is a suitable workbench to address these challenges. From the medical or biological perspective, providing computing power and storage is the most attractive feature of cloud computing in handling the ever increasing biological data. As data increases in size, many research organizations start to experience the lack of computing power, which becomes a major hurdle in achieving research goals. In this paper, we review the features of publically available bio and health cloud systems in terms of graphical user interface, external data integration, security and extensibility of features. We then discuss about issues and limitations of current cloud systems and conclude with suggestion of a biological cloud environment concept, which can be defined as a total workbench environment assembling computational tools and databases for analyzing bio/medical big data in particular application domains.

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.

PLOS Collections: Article collections published by the Public Library of

Science.gov Websites

Collections Propose a Special Collection Finances for Special Collections Browse Biology & Life Sciences Advertise Media Inquiries Publications PLOS Biology PLOS Medicine PLOS Computational Biology PLOS Currents

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.

Crossing Over…Markov Meets Mendel

PubMed Central

Mneimneh, Saad

2012-01-01

Chromosomal crossover is a biological mechanism to combine parental traits. It is perhaps the first mechanism ever taught in any introductory biology class. The formulation of crossover, and resulting recombination, came about 100 years after Mendel's famous experiments. To a great extent, this formulation is consistent with the basic genetic findings of Mendel. More importantly, it provides a mathematical insight for his two laws (and corrects them). From a mathematical perspective, and while it retains similarities, genetic recombination guarantees diversity so that we do not rapidly converge to the same being. It is this diversity that made the study of biology possible. In particular, the problem of genetic mapping and linkage—one of the first efforts towards a computational approach to biology—relies heavily on the mathematical foundation of crossover and recombination. Nevertheless, as students we often overlook the mathematics of these phenomena. Emphasizing the mathematical aspect of Mendel's laws through crossover and recombination will prepare the students to make an early realization that biology, in addition to being experimental, IS a computational science. This can serve as a first step towards a broader curricular transformation in teaching biological sciences. I will show that a simple and modern treatment of Mendel's laws using a Markov chain will make this step possible, and it will only require basic college-level probability and calculus. My personal teaching experience confirms that students WANT to know Markov chains because they hear about them from bioinformaticists all the time. This entire exposition is based on three homework problems that I designed for a course in computational biology. A typical reader is, therefore, an instructional staff member or a student in a computational field (e.g., computer science, mathematics, statistics, computational biology, bioinformatics). However, other students may easily follow by omitting the mathematically more elaborate parts. I kept those as separate sections in the exposition. PMID:22629235

Development of Interactive Computer Programs To Help Students Transfer Basic Skills to College Level Science and Behavioral Science Courses.

ERIC Educational Resources Information Center

Mikulecky, Larry

Interactive computer programs, developed at Indiana University's Learning Skills Center, were designed to model effective strategies for reading biology and psychology textbooks. For each subject area, computer programs and textbook passages were used to instruct and model for students how to identify key concepts, compare and contrast concepts,…

Why are some STEM fields more gender balanced than others?

PubMed

Cheryan, Sapna; Ziegler, Sianna A; Montoya, Amanda K; Jiang, Lily

2017-01-01

Women obtain more than half of U.S. undergraduate degrees in biology, chemistry, and mathematics, yet they earn less than 20% of computer science, engineering, and physics undergraduate degrees (National Science Foundation, 2014a). Gender differences in interest in computer science, engineering, and physics appear even before college. Why are women represented in some science, technology, engineering, and mathematics (STEM) fields more than others? We conduct a critical review of the most commonly cited factors explaining gender disparities in STEM participation and investigate whether these factors explain differential gender participation across STEM fields. Math performance and discrimination influence who enters STEM, but there is little evidence to date that these factors explain why women's underrepresentation is relatively worse in some STEM fields. We introduce a model with three overarching factors to explain the larger gender gaps in participation in computer science, engineering, and physics than in biology, chemistry, and mathematics: (a) masculine cultures that signal a lower sense of belonging to women than men, (b) a lack of sufficient early experience with computer science, engineering, and physics, and (c) gender gaps in self-efficacy. Efforts to increase women's participation in computer science, engineering, and physics may benefit from changing masculine cultures and providing students with early experiences that signal equally to both girls and boys that they belong and can succeed in these fields. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Using the Principles of BIO2010 to Develop an Introductory, Interdisciplinary Course for Biology Students

PubMed Central

Adams, Peter; Goos, Merrilyn

2010-01-01

Modern biological sciences require practitioners to have increasing levels of knowledge, competence, and skills in mathematics and programming. A recent review of the science curriculum at the University of Queensland, a large, research-intensive institution in Australia, resulted in the development of a more quantitatively rigorous undergraduate program. Inspired by the National Research Council's BIO2010 report, a new interdisciplinary first-year course (SCIE1000) was created, incorporating mathematics and computer programming in the context of modern science. In this study, the perceptions of biological science students enrolled in SCIE1000 in 2008 and 2009 are measured. Analysis indicates that, as a result of taking SCIE1000, biological science students gained a positive appreciation of the importance of mathematics in their discipline. However, the data revealed that SCIE1000 did not contribute positively to gains in appreciation for computing and only slightly influenced students' motivation to enroll in upper-level quantitative-based courses. Further comparisons between 2008 and 2009 demonstrated the positive effect of using genuine, real-world contexts to enhance student perceptions toward the relevance of mathematics. The results support the recommendation from BIO2010 that mathematics should be introduced to biology students in first-year courses using real-world examples, while challenging the benefits of introducing programming in first-year courses. PMID:20810961

Bioinformatics for Exploration

NASA Technical Reports Server (NTRS)

Johnson, Kathy A.

2006-01-01

For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

Energy and technology review

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

Quirk, W.J.; Canada, J.; de Vore, L.

1994-04-01

This issue highlights the Lawrence Livermore National Laboratory`s 1993 accomplishments in our mission areas and core programs: economic competitiveness, national security, energy, the environment, lasers, biology and biotechnology, engineering, physics, chemistry, materials science, computers and computing, and science and math education. Secondary topics include: nonproliferation, arms control, international security, environmental remediation, and waste management.

Computer Programs in Marine Science: Key to Oceanographic Records Documentation No. 5.

ERIC Educational Resources Information Center

Firestone, Mary A.

Presented are abstracts of 700 computer programs in marine science. The programs listed are categorized under a wide range of headings which include physical oceanography, chemistry, coastal and estuarine processes, biology, pollution, air-sea interaction and heat budget, navigation and charting, curve fitting, and applied mathematics. The…

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

ERIC Educational Resources Information Center

Cutter, Mary Ann G.; Drexler, Edward; Gottesman, Kay S.; Goulding, Philip G.; McCullough, Laurence B.; McInerney, Joseph D.; Micikas, Lynda B.; Mural, Richard J.; Murray, Jeffrey C.; Zola, John

This module, for high school teachers, is the second of two modules about the Human Genome Project (HGP) produced by the Biological Sciences Curriculum Study (BSCS). The first section of this module provides background information for teachers about the structure and objectives of the HGP, aspects of the science and technology that underlie the…

Making Science Work.

ERIC Educational Resources Information Center

Thomas, Lewis

1981-01-01

Presents a viewpoint concerning the impact of recent scientific advances on society. Discusses biological discoveries, space exploration, computer technology, development of new astronomical theories, the behavioral sciences, and basic research. Challenges to keeping science current with technological advancement are also discussed. (DS)

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

Mann, Reinhold C.

This is the first formal progress report issued by the ORNL Life Sciences Division. It covers the period from February 1997 through December 1998, which has been critical in the formation of our new division. The legacy of 50 years of excellence in biological research at ORNL has been an important driver for everyone in the division to do their part so that this new research division can realize the potential it has to make seminal contributions to the life sciences for years to come. This reporting period is characterized by intense assessment and planning efforts. They included thorough scrutinymore » of our strengths and weaknesses, analyses of our situation with respect to comparative research organizations, and identification of major thrust areas leading to core research efforts that take advantage of our special facilities and expertise. Our goal is to develop significant research and development (R&D) programs in selected important areas to which we can make significant contributions by combining our distinctive expertise and resources in the biological sciences with those in the physical, engineering, and computational sciences. Significant facilities in mouse genomics, mass spectrometry, neutron science, bioanalytical technologies, and high performance computing are critical to the success of our programs. Research and development efforts in the division are organized in six sections. These cluster into two broad areas of R&D: systems biology and technology applications. The systems biology part of the division encompasses our core biological research programs. It includes the Mammalian Genetics and Development Section, the Biochemistry and Biophysics Section, and the Computational Biosciences Section. The technology applications part of the division encompasses the Assessment Technology Section, the Environmental Technology Section, and the Toxicology and Risk Analysis Section. These sections are the stewards of the division's core competencies. The common mission of the division is to advance science and technology to understand complex biological systems and their relationship with human health and the environment.« less

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1985

1985-01-01

Presents biology, chemistry, physics, and health activities, experiments, demonstrations, and computer programs. Includes mechanism of stomatal opening, using aquatic plants to help demonstrate chemical buffering, microbial activity/contamination in milk samples, computer computation of fitness scores, reservoir project, complexes of transition…

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.

Associations and Committees of or for Women in Science, Engineering, Mathematics and Medicine.

ERIC Educational Resources Information Center

Aldrich, Michele, Comp.; Leach, Alicia, Comp.

Provided is a list of associations and committees of or for women in science, engineering, mathematics, and medicine. The list is organized by discipline, with cross-referencing to cognate specialties. The disciplines include: anthropology; astronomy; atmospheric sciences; biology; chemistry; computer sciences; earth sciences; energy; engineering;…

Reach for Reference. Science Online

ERIC Educational Resources Information Center

Safford, Barbara Ripp

2004-01-01

This brief article describes the database, Science Online, from Facts on File. Science is defined broadly in this database to include archeology, computer technology, medicine, inventions, and mathematics, as well as biology, chemistry, earth sciences, and astronomy. Content also is divided into format categories for browsing purposes:…

Science News of the Year.

ERIC Educational Resources Information Center

Science News, 1987

1987-01-01

Provides a review of science news stories reported in "Science News" during 1987. References each item to the volume and page number in which the subject was addressed. Contains references on astronomy, behavior, biology, biomedicine, chemistry, earth sciences, environment, mathematics and computers, paleontology and anthropology, physics, science…

High School Students Gear Up for Battle of the Brains

Science.gov Websites

tournament, which focuses on physics, math, biology, astronomy, chemistry, computers and the earth sciences competition. DOE began the National Science Bowl 11 years ago to help stimulate interest in science and math

Students from Grand Junction High School Triumph in Colorado Science Bowl

Science.gov Websites

-fire questions about physics, math, biology, astronomy, chemistry, computers and the earth sciences years ago to help stimulate interest in science and math. The competition has evolved into one of the

High School Students Gear Up for Battle of the Brains

Science.gov Websites

focuses on physics, math, biology, astronomy, chemistry, computers and the earth sciences. Each team is Science Bowl a decade ago to help stimulate interest in science and math. The competition has evolved into

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.

78 FR 9689 - Notification of a Public Meeting of the Chartered Science Advisory Board

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-11

... advances in molecular biology, chemistry and innovative computer science to more effectively and... Science Advisory Board AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: The Environmental Protection Agency (EPA) Science Advisory Board (SAB) Staff Office announces a public meeting of...

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 Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine.

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 Austin), Dr. Aidong Zhang (Buffalo) and Dr. Zhi-Hua Zhou (Nanjing) for their significant contributions to the field of intelligent biological medicine. PMID:21143775

Computational immunology--from bench to virtual reality.

PubMed

Chan, Cliburn; Kepler, Thomas B

2007-02-01

Drinking from a fire-hose is an old cliché for the experience of learning basic and clinical sciences in medical school, and the pipe has been growing fatter at an alarming rate. Of course, it does not stop when one graduates; if anything, both the researcher and clinician are flooded with even more information. Slightly embarrassingly, while modern science is very good at generating new information, our ability to weave multiple strands of data into a useful and coherent story lags quite far behind. Bioinformatics, systems biology and computational medicine have arisen in recent years to address just this challenge. This essay is an introduction to the problem of data synthesis and integration in biology and medicine, and how the relatively new art of biological simulation can provide a new kind of map for understanding physiology and pathology. The nascent field of computational immunology will be used for illustration, but similar trends are occurring broadly across all of biology and medicine.

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

PubMed Central

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

2011-01-01

Computer science has become ubiquitous in many areas of biological research, yet most high school and even college students are unaware of this. As a result, many college biology majors graduate without adequate computational skills for contemporary fields of biology. The absence of a computational element in secondary school biology classrooms is of growing concern to the computational biology community and biology teachers who would like to acquaint their students with updated approaches in the discipline. We present a first attempt to correct this absence by introducing a computational biology element to teach genetic evolution into advanced biology classes in two local high schools. Our primary goal was to show students how computation is used in biology and why a basic understanding of computation is necessary for research in many fields of biology. This curriculum is intended to be taught by a computational biologist who has worked with a high school advanced biology teacher to adapt the unit for his/her classroom, but a motivated high school teacher comfortable with mathematics and computing may be able to teach this alone. In this paper, we present our curriculum, which takes into consideration the constraints of the required curriculum, and discuss our experiences teaching it. We describe the successes and challenges we encountered while bringing this unit to high school students, discuss how we addressed these challenges, and make suggestions for future versions of this curriculum.We believe that our curriculum can be a valuable seed for further development of computational activities aimed at high school biology students. Further, our experiences may be of value to others teaching computational biology at this level. Our curriculum can be obtained at http://ecsite.cs.colorado.edu/?page_id=149#biology or by contacting the authors. PMID:22046118

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

PubMed

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

2011-10-01

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

Opportunities for Computational Discovery in Basic Energy Sciences

NASA Astrophysics Data System (ADS)

Pederson, Mark

2011-03-01

An overview of the broad-ranging support of computational physics and computational science within the Department of Energy Office of Science will be provided. Computation as the third branch of physics is supported by all six offices (Advanced Scientific Computing, Basic Energy, Biological and Environmental, Fusion Energy, High-Energy Physics, and Nuclear Physics). Support focuses on hardware, software and applications. Most opportunities within the fields of~condensed-matter physics, chemical-physics and materials sciences are supported by the Officeof Basic Energy Science (BES) or through partnerships between BES and the Office for Advanced Scientific Computing. Activities include radiation sciences, catalysis, combustion, materials in extreme environments, energy-storage materials, light-harvesting and photovoltaics, solid-state lighting and superconductivity.~ A summary of two recent reports by the computational materials and chemical communities on the role of computation during the next decade will be provided. ~In addition to materials and chemistry challenges specific to energy sciences, issues identified~include a focus on the role of the domain scientist in integrating, expanding and sustaining applications-oriented capabilities on evolving high-performance computing platforms and on the role of computation in accelerating the development of innovative technologies. ~~

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.

Online citizen science games: Opportunities for the biological sciences.

PubMed

Curtis, Vickie

2014-12-01

Recent developments in digital technologies and the rise of the Internet have created new opportunities for citizen science. One of these has been the development of online citizen science games where complex research problems have been re-imagined as online multiplayer computer games. Some of the most successful examples of these can be found within the biological sciences, for example, Foldit, Phylo and EteRNA. These games offer scientists the opportunity to crowdsource research problems, and to engage with those outside the research community. Games also enable those without a background in science to make a valid contribution to research, and may also offer opportunities for informal science learning.

Exposure Science and the US EPA National Center for Computational Toxicology

EPA Science Inventory

The emerging field of computational toxicology applies mathematical and computer models and molecular biological and chemical approaches to explore both qualitative and quantitative relationships between sources of environmental pollutant exposure and adverse health outcomes. The...

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Art in Science Competition invites artworks to the annual exhibition on ISMB 2018 in Chicago.

PubMed

Welch, Lonnie; Gaeta, Bruno; Kovats, Diane E; Frenkel Morgenstern, Milana

2018-01-01

The International Society of Computational Biology and Bioinformatics (ISCB) brings together scientists from a wide range of disciplines, including biology, medicine, computer science, mathematics and statistics. Practitioners in these fields are constantly dealing with information in visual form: from microscope images and photographs of gels to scatter plots, network graphs and phylogenetic trees, structural formulae and protein models to flow diagrams, visual aids for problem-solving are omnipresent. The ISCB Art in Science Competition 2017 at the ISCB/ECCB 2017 conference in Prague offered a way to show the beauty of science in art form. Past artworks in this annual exhibition at ISMB combined outstanding beauty and aesthetics with deep insight that perfectly validated the exhibit's approach or went beyond the problem's solution. Others were surprising and inspiring through the transition from science to art, opening eyes and minds to reflect on the work being undertaken.

Only One Science: Twelfth Annual Report of the National Science Board.

ERIC Educational Resources Information Center

National Science Foundation, Washington, DC. National Science Board.

Departing markedly from previous reports to Congress by the National Science Board, this document presents in an informal, narrative style six stories depicting scientific discoveries and their effects on society. Drawn from the physical, biological, medical, and social sciences, topics discussed include: (1) computers and semiconductors; (2)…

BioSIGHT: Interactive Visualization Modules for Science Education

NASA Technical Reports Server (NTRS)

Wong, Wee Ling

1998-01-01

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high- speed network capabilities. The BioSIGHT project at IMSC is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches towards the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science, Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students. Our collaborators include TERC, a research and education organization with extensive k-12 math and science curricula development from Cambridge, MA.; SRI International of Menlo Park, CA.; teachers and students from local area high schools (Newbury Park High School, USC's Family of Five schools, Chadwick School, and Pasadena Polytechnic High School).

Journal of Undergraduate Research, Volume VIII, 2008

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

Stiner, K. S.; Graham, S.; Khan, M.

Th e Journal of Undergraduate Research (JUR) provides undergraduate interns the opportunity to publish their scientific innovation and to share their passion for education and research with fellow students and scientists. Fields in which these students worked include: Biology; Chemistry; Computer Science; Engineering; Environmental Science; General Sciences; Materials Sciences; Medical and Health Sciences; Nuclear Sciences; Physics; Science Policy; and Waste Management.

International Conference on Intelligent Systems for Molecular Biology (ISMB)

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

Goldberg, Debra; Hibbs, Matthew; Kall, Lukas

The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 13 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on "intelligent systems" and actual biological data makes ISMB a unique and highly important meeting, and 13 years of experience in holding the conference hasmore » resulted in a consistently well organized, well attended, and highly respected annual conference. The ISMB 2005 meeting was held June 25-29, 2005 at the Renaissance Center in Detroit, Michigan. The meeting attracted over 1,730 attendees. The science presented was exceptional, and in the course of the five-day meeting, 56 scientific papers, 710 posters, 47 Oral Abstracts, 76 Software demonstrations, and 14 tutorials were presented. The attendees represented a broad spectrum of backgrounds with 7% from commercial companies, over 28% qualifying for student registration, and 41 countries were represented at the conference, emphasizing its important international aspect. The ISMB conference is especially important because the cultures of computer science and biology are so disparate. ISMB, as a full-scale technical conference with refereed proceedings that have been indexed by both MEDLINE and Current Contents since 1996, bridges this cultural gap.« less

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…

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

None, None

The Second SIAM Conference on Computational Science and Engineering was held in San Diego from February 10-12, 2003. Total conference attendance was 553. This is a 23% increase in attendance over the first conference. The focus of this conference was to draw attention to the tremendous range of major computational efforts on large problems in science and engineering, to promote the interdisciplinary culture required to meet these large-scale challenges, and to encourage the training of the next generation of computational scientists. Computational Science & Engineering (CS&E) is now widely accepted, along with theory and experiment, as a crucial third modemore » of scientific investigation and engineering design. Aerospace, automotive, biological, chemical, semiconductor, and other industrial sectors now rely on simulation for technical decision support. For federal agencies also, CS&E has become an essential support for decisions on resources, transportation, and defense. CS&E is, by nature, interdisciplinary. It grows out of physical applications and it depends on computer architecture, but at its heart are powerful numerical algorithms and sophisticated computer science techniques. From an applied mathematics perspective, much of CS&E has involved analysis, but the future surely includes optimization and design, especially in the presence of uncertainty. Another mathematical frontier is the assimilation of very large data sets through such techniques as adaptive multi-resolution, automated feature search, and low-dimensional parameterization. The themes of the 2003 conference included, but were not limited to: Advanced Discretization Methods; Computational Biology and Bioinformatics; Computational Chemistry and Chemical Engineering; Computational Earth and Atmospheric Sciences; Computational Electromagnetics; Computational Fluid Dynamics; Computational Medicine and Bioengineering; Computational Physics and Astrophysics; Computational Solid Mechanics and Materials; CS&E Education; Meshing and Adaptivity; Multiscale and Multiphysics Problems; Numerical Algorithms for CS&E; Discrete and Combinatorial Algorithms for CS&E; Inverse Problems; Optimal Design, Optimal Control, and Inverse Problems; Parallel and Distributed Computing; Problem-Solving Environments; Software and Wddleware Systems; Uncertainty Estimation and Sensitivity Analysis; and Visualization and Computer Graphics.« less

Investigating Impact Metrics for Performance for the US EPA National Center for Computational Toxicology (ACS Fall meeting)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data drive...

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

Life sciences and environmental sciences

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

Not Available

1992-02-01

The DOE laboratories play a unique role in bringing multidisciplinary talents -- in biology, physics, chemistry, computer sciences, and engineering -- to bear on major problems in the life and environmental sciences. Specifically, the laboratories utilize these talents to fulfill OHER's mission of exploring and mitigating the health and environmental effects of energy use, and of developing health and medical applications of nuclear energy-related phenomena. At Lawrence Berkeley Laboratory (LBL) support of this mission is evident across the spectrum of OHER-sponsored research, especially in the broad areas of genomics, structural biology, basic cell and molecular biology, carcinogenesis, energy and environment,more » applications to biotechnology, and molecular, nuclear and radiation medicine. These research areas are briefly described.« less

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1985

1985-01-01

Presents 23 experiments, activities, field projects and computer programs in the biological and physical sciences. Instructional procedures, experimental designs, materials, and background information are suggested. Topics include fluid mechanics, electricity, crystals, arthropods, limpets, acid neutralization, and software evaluation. (ML)

Multiscale Computation. Needs and Opportunities for BER Science

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

Scheibe, Timothy D.; Smith, Jeremy C.

2015-01-01

The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSLmore » decisions regarding future computational (hardware and software) architectures.« less

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

Reviews: Software.

ERIC Educational Resources Information Center

Mackenzie, Norma N.; And Others

1988-01-01

Reviews four computer software packages including: "The Physical Science Series: Sound" which demonstrates making waves, speed of sound, doppler effect, and human hearing; "Andromeda" depicting celestial motions in any direction; "Biology Quiz: Humans" covering chemistry, cells, viruses, and human biology; and…

Delivering an Informational Hub for Data at the National Center for Computational Toxicology (ACS Spring Meeting) 7 of 7

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data drive...

Journal of Undergraduate Research, Volume VI, 2006

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

Faletra, P.; Schuetz, A.; Cherkerzian, D.

Students who conducted research at DOE National Laboratories during 2005 were invited to include their research abstracts, and for a select few, their completed research papers in this Journal. This Journal is direct evidence of students collaborating with their mentors. Fields in which these students worked include: Biology; Chemistry; Computer Science; Engineering; Environmental Science; General Sciences; Materials Sciences; Medical and Health Sciences; Nuclear Sciences; Physics; and Science Policy.

77 FR 25479 - Notification of a Public Meeting of the Science Advisory Board (SAB); Exposure and Human Health...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-30

... biology, chemistry and innovative computer science to more effectively and efficiently rank chemicals... ENVIRONMENTAL PROTECTION AGENCY [FRL-9667-1] Notification of a Public Meeting of the Science...). ACTION: Notice. SUMMARY: The EPA Science Advisory Board (SAB) Staff Office announces a public meeting of...

Colorado Students Head to National Science Competition

Science.gov Websites

question and answer tournament that focuses on physics, math, biology, astronomy, chemistry, computers and nine years ago to help stimulate interest in science and math. The competition has evolved into one of

Students From Highlands Ranch Triumph in Colorado Science Bowl

Science.gov Websites

final round of rapid-fire questions about physics, math, biology, astronomy, chemistry, computers and interest in science and math. The competition has evolved into one of the Energy Department's premier

Computer Science (CS) Education in Indian Schools: Situation Analysis Using Darmstadt Model

ERIC Educational Resources Information Center

Raman, Raghu; Venkatasubramanian, Smrithi; Achuthan, Krishnashree; Nedungadi, Prema

2015-01-01

Computer science (CS) and its enabling technologies are at the heart of this information age, yet its adoption as a core subject by senior secondary students in Indian schools is low and has not reached critical mass. Though there have been efforts to create core curriculum standards for subjects like Physics, Chemistry, Biology, and Math, CS…

A Bioinformatics Module for Use in an Introductory Biology Laboratory

ERIC Educational Resources Information Center

Alaie, Adrienne; Teller, Virginia; Qiu, Wei-gang

2012-01-01

Since biomedical science has become increasingly data-intensive, acquisition of computational and quantitative skills by science students has become more important. For non-science students, an introduction to biomedical databases and their applications promotes the development of a scientifically literate population. Because typical college…

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

Restoration of neurological functions by neuroprosthetic technologies: future prospects and trends towards micro-, nano-, and biohybrid systems.

PubMed

Stieglitz, T

2007-01-01

Today applications of neural prostheses that successfully help patients to increase their activities of daily living and participate in social life again are quite simple implants that yield definite tissue response and are well recognized as foreign body. Latest developments in genetic engineering, nanotechnologies and materials sciences have paved the way to new scenarios towards highly complex systems to interface the human nervous system. Combinations of neural cells with microimplants promise stable biohybrid interfaces. Nanotechnology opens the door to macromolecular landscapes on implants that mimic the biologic topology and surface interaction of biologic cells. Computer sciences dream of technical cognitive systems that act and react due to knowledge-based conclusion mechanisms to a changing or adaptive environment. Different sciences start to interact and discuss the synergies when methods and paradigms from biology, computer sciences and engineering, neurosciences, psychology will be combined. They envision the era of "converging technologies" to completely change the understanding of science and postulate a new vision of humans. In this chapter, these research lines will be discussed on some examples as well as the societal implications and ethical questions that arise from these new opportunities.

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…

The EPA CompTox Chemistry Dashboard - an online resource for environmental chemists (ACS Spring Meeting)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data drive...

The EPA Comptox Chemistry Dashboard: A Web-Based Data Integration Hub for Toxicology Data (SOT)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data drive...

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

NASA Astrophysics Data System (ADS)

Honing, Henkjan; Zuidema, Willem

2014-09-01

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

Laboratory Directed Research and Development Annual Report for 2011

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

Hughes, Pamela J.

2012-04-09

This report documents progress made on all LDRD-funded projects during fiscal year 2011. The following topics are discussed: (1) Advanced sensors and instrumentation; (2) Biological Sciences; (3) Chemistry; (4) Earth and space sciences; (5) Energy supply and use; (6) Engineering and manufacturing processes; (7) Materials science and technology; (8) Mathematics and computing sciences; (9) Nuclear science and engineering; and (10) Physics.

Current Developments in Machine Learning Techniques in Biological Data Mining.

PubMed

Dumancas, Gerard G; Adrianto, Indra; Bello, Ghalib; Dozmorov, Mikhail

2017-01-01

This supplement is intended to focus on the use of machine learning techniques to generate meaningful information on biological data. This supplement under Bioinformatics and Biology Insights aims to provide scientists and researchers working in this rapid and evolving field with online, open-access articles authored by leading international experts in this field. Advances in the field of biology have generated massive opportunities to allow the implementation of modern computational and statistical techniques. Machine learning methods in particular, a subfield of computer science, have evolved as an indispensable tool applied to a wide spectrum of bioinformatics applications. Thus, it is broadly used to investigate the underlying mechanisms leading to a specific disease, as well as the biomarker discovery process. With a growth in this specific area of science comes the need to access up-to-date, high-quality scholarly articles that will leverage the knowledge of scientists and researchers in the various applications of machine learning techniques in mining biological data.

Enhancing Student Engagement to Positively Impact Mathematics Anxiety, Confidence and Achievement for Interdisciplinary Science Subjects

ERIC Educational Resources Information Center

Everingham, Yvette L.; Gyuris, Emma; Connolly, Sean R.

2017-01-01

Contemporary science educators must equip their students with the knowledge and practical know-how to connect multiple disciplines like mathematics, computing and the natural sciences to gain a richer and deeper understanding of a scientific problem. However, many biology and earth science students are prejudiced against mathematics due to…

Interdisciplinary Introductory Course in Bioinformatics

ERIC Educational Resources Information Center

Kortsarts, Yana; Morris, Robert W.; Utell, Janine M.

2010-01-01

Bioinformatics is a relatively new interdisciplinary field that integrates computer science, mathematics, biology, and information technology to manage, analyze, and understand biological, biochemical and biophysical information. We present our experience in teaching an interdisciplinary course, Introduction to Bioinformatics, which was developed…

Molecular Mechanics and Dynamics Characterization of an "in silico" Mutated Protein: A Stand-Alone Lab Module or Support Activity for "in vivo" and "in vitro" Analyses of Targeted Proteins

ERIC Educational Resources Information Center

Chiang, Harry; Robinson, Lucy C.; Brame, Cynthia J.; Messina, Troy C.

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems.…

Meta-analysis of the effectiveness of computer-based laboratory versus traditional hands-on laboratory in college and pre-college science instructions

NASA Astrophysics Data System (ADS)

Onuoha, Cajetan O.

The purpose of this research study was to determine the overall effectiveness of computer-based laboratory compared with the traditional hands-on laboratory for improving students' science academic achievement and attitudes towards science subjects at the college and pre-college levels of education in the United States. Meta-analysis was used to synthesis the findings from 38 primary research studies conducted and/or reported in the United States between 1996 and 2006 that compared the effectiveness of computer-based laboratory with the traditional hands-on laboratory on measures related to science academic achievements and attitudes towards science subjects. The 38 primary research studies, with total subjects of 3,824 generated a total of 67 weighted individual effect sizes that were used in this meta-analysis. The study found that computer-based laboratory had small positive effect sizes over the traditional hands-on laboratory (ES = +0.26) on measures related to students' science academic achievements and attitudes towards science subjects (ES = +0.22). It was also found that computer-based laboratory produced more significant effects on physical science subjects compared to biological sciences (ES = +0.34, +0.17).

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

Protein Engineering: Development of a Metal Ion Dependent Switch

DTIC Science & Technology

2017-05-22

Society of Chemistry Royal Society of Chemistry Biochemistry PNAS Escherichia coli Journal of Biotechnology Biochemistry Nature Protocols Journal of...Molecular Biology Biochemistry Royal Society of Chemistry Proteins: Structure, Function, and Bioinformatics Journal of Molecular Biology Biophysical...Biophysical Journal Protein Science Journal of Computational Chemistry Current Opinion in Chemical Biology Royal Society of Chemistry

Interdisciplinarity: The Right "People", a Supportive "Place", and a "Program" Emerges

ERIC Educational Resources Information Center

Van Wylen, David G. L.; Abdella, Beth R. J.; Dickinson, Shelly D.; Engbrecht, Jason J.; Vandiver, Rebecca

2013-01-01

Twenty-first-century biology is inherently interdisciplinary. Every aspect of biology, from molecules to organisms to ecosystems, is richly informed by the physical, mathematical, and computational sciences. It is both an exciting and daunting time for biology educators--exciting because of the vast opportunity for important new discoveries that…

Comptox Chemistry Dashboard: Web-Based Data Integration Hub for Environmental Chemistry and Toxicology Data (ACS Fall meeting 4 of 12)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrate advances in biology, chemistry, exposure and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and da...

New developments in delivering public access to data from the National Center for Computational Toxicology at the EPA

EPA Science Inventory

Researchers at 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 goal of this researc...

Marc Snir | Argonne National Laboratory

Science.gov Websites

Molecular biology Proteomics Environmental science & technology Air quality Atmospheric & climate , H.S., Jr., Demonstrating the scalability of a molecular dynamics application on a Petaflop computer Transformations IGSBInstitute for Genomics and Systems Biology IMEInstitute for Molecular Engineering JCESRJoint

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.

3D Object Recognition: Symmetry and Virtual Views

DTIC Science & Technology

1992-12-01

NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATIONI Artificial Intelligence Laboratory REPORT NUMBER 545 Technology Square AIM 1409 Cambridge... ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING A.I. Memo No. 1409 December 1992 C.B.C.L. Paper No. 76 3D Object...research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences, and at the Artificial

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1985

1985-01-01

Presents 23 experiments, demonstrations, activities, and computer programs in biology, chemistry, and physics. Topics include lead in petrol, production of organic chemicals, reduction of water, enthalpy, X-ray diffraction model, nuclear magnetic resonance spectroscopy, computer simulation for additive mixing of colors, Archimedes Principle, and…

ISMB Conference Funding to Support Attendance of Early Researchers and Students

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

Gaasterland, Terry

ISMB Conference Funding for Students and Young Scientists Historical Description The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 22 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on “intelligent systems” and actual biological data makes ISMB a unique and highly important meeting.more » 21 years of experience in holding the conference has resulted in a consistently well-organized, well attended, and highly respected annual conference. "Intelligent systems" include any software which goes beyond straightforward, closed-form algorithms or standard database technologies, and encompasses those that view data in a symbolic fashion, learn from examples, consolidate multiple levels of abstraction, or synthesize results to be cognitively tractable to a human, including the development and application of advanced computational methods for biological problems. Relevant computational techniques include, but are not limited to: machine learning, pattern recognition, knowledge representation, databases, combinatorics, stochastic modeling, string and graph algorithms, linguistic methods, robotics, constraint satisfaction, and parallel computation. Biological areas of interest include molecular structure, genomics, molecular sequence analysis, evolution and phylogenetics, molecular interactions, metabolic pathways, regulatory networks, developmental control, and molecular biology generally. Emphasis is placed on the validation of methods using real data sets, on practical applications in the biological sciences, and on development of novel computational techniques. The ISMB conferences are distinguished from many other conferences in computational biology or artificial intelligence by an insistence that the researchers work with real molecular biology data, not theoretical or toy examples; and from many other biological conferences by providing a forum for technical advances as they occur, which otherwise may be shunned until a firm experimental result is published. The resulting intellectual richness and cross-disciplinary diversity provides an important opportunity for both students and senior researchers. ISMB has become the premier conference series in this field with refereed, published proceedings, establishing an infrastructure to promote the growing body of research.« less

2017 ISCB Accomplishment by a Senior Scientist Award: Pavel Pevzner

PubMed Central

Fogg, Christiana N.; Kovats, Diane E.; Berger, Bonnie

2017-01-01

The International Society for Computational Biology ( ISCB) recognizes an established scientist each year with the Accomplishment by a Senior Scientist Award for significant contributions he or she has made to the field. This award honors scientists who have contributed to the advancement of computational biology and bioinformatics through their research, service, and education work. Pavel Pevzner, PhD, Ronald R. Taylor Professor of Computer Science and Director of the NIH Center for Computational Mass Spectrometry at University of California, San Diego, has been selected as the winner of the 2017 Accomplishment by a Senior Scientist Award. The ISCB awards committee, chaired by Dr. Bonnie Berger of the Massachusetts Institute of Technology, selected Pevzner as the 2017 winner. Pevzner will receive his award and deliver a keynote address at the 2017 Intelligent Systems for Molecular Biology-European Conference on Computational Biology joint meeting ( ISMB/ECCB 2017) held in Prague, Czech Republic from July 21-July 25, 2017. ISMB/ECCB is a biennial joint meeting that brings together leading scientists in computational biology and bioinformatics from around the globe. PMID:28713548

Index to College Television Courseware. A Comprehensive Directory of Credit Courses and Concept Modules Distributed on Video Tape and Film.

ERIC Educational Resources Information Center

Prange, W. Werner; Bellinghausen, Carol R.

A directory of college television courseware lists offerings in curriculum areas such as: social sciences, biology, black studies, business, mathematics, sciences, computer science, consumer protection, creative arts, drug education, ecology, engineering, humanities, physics, nursing, nutrition, religion, and vocational education, etc. Each course…

The Mix of Military and Civilian Faculty at the United States Air Force Academy: Finding a Sustainable Balance for Enduring Success

DTIC Science & Technology

2013-01-01

academic departments are as follows: The Basic Sciences Division includes the Departments of Biology, Chemistry, Computer Science, Mathematical Sciences...percent). This factor is based on actuarial estimates for the costs of the government- paid portion of health insurance under the Federal Employees

Bringing computational science to the public.

PubMed

McDonagh, James L; Barker, Daniel; Alderson, Rosanna G

2016-01-01

The increasing use of computers in science allows for the scientific analyses of large datasets at an increasing pace. We provided examples and interactive demonstrations at Dundee Science Centre as part of the 2015 Women in Science festival, to present aspects of computational science to the general public. We used low-cost Raspberry Pi computers to provide hands on experience in computer programming and demonstrated the application of computers to biology. Computer games were used as a means to introduce computers to younger visitors. The success of the event was evaluated by voluntary feedback forms completed by visitors, in conjunction with our own self-evaluation. This work builds on the original work of the 4273π bioinformatics education program of Barker et al. (2013, BMC Bioinform. 14:243). 4273π provides open source education materials in bioinformatics. This work looks at the potential to adapt similar materials for public engagement events. It appears, at least in our small sample of visitors (n = 13), that basic computational science can be conveyed to people of all ages by means of interactive demonstrations. Children as young as five were able to successfully edit simple computer programs with supervision. This was, in many cases, their first experience of computer programming. The feedback is predominantly positive, showing strong support for improving computational science education, but also included suggestions for improvement. Our conclusions are necessarily preliminary. However, feedback forms suggest methods were generally well received among the participants; "Easy to follow. Clear explanation" and "Very easy. Demonstrators were very informative." Our event, held at a local Science Centre in Dundee, demonstrates that computer games and programming activities suitable for young children can be performed alongside a more specialised and applied introduction to computational science for older visitors.

A Clinical Evaluation Of Cone Beam Computed Tomography

DTIC Science & Technology

2016-06-01

A CLINICAL EVALUATION OF CONE BEAM COMPUTED TOMOGRAPHY by Bryan James Behm, D.D.S. Lieutenant, Dental Corps United States Navy A thesis...submitted to the Faculty of the Endodontic Graduate Program Naval Postgraduate Dental School Uniformed Services University of the Health Sciences in...partial fulfillment of the requirements for the degree of Master of Science in Oral Biology June 2016 Naval Postgraduate Dental School Unif01med

Biology Needs Evolutionary Software Tools: Let’s Build Them Right

PubMed Central

Team, Galaxy; Goecks, Jeremy; Taylor, James

2018-01-01

Abstract Research in population genetics and evolutionary biology has always provided a computational backbone for life sciences as a whole. Today evolutionary and population biology reasoning are essential for interpretation of large complex datasets that are characteristic of all domains of today’s life sciences ranging from cancer biology to microbial ecology. This situation makes algorithms and software tools developed by our community more important than ever before. This means that we, developers of software tool for molecular evolutionary analyses, now have a shared responsibility to make these tools accessible using modern technological developments as well as provide adequate documentation and training. PMID:29688462

Cognitive science as an interface between rational and mechanistic explanation.

PubMed

Chater, Nick

2014-04-01

Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). The discipline is thus at the interface between two very different styles of explanation--as the papers in the current special issue well illustrate, it explores the interplay of rational and mechanistic forces. Copyright © 2014 Cognitive Science Society, Inc.

Anesthesiologist Assistant

MedlinePlus

... requirements are met), majors typically are biology, chemistry, physics, mathematics, computer science, or one of the allied health professions, such as respiratory therapy, medical technology, or ...

48 CFR 22.1102 - Definition.

Code of Federal Regulations, 2010 CFR

2010-10-01

... through prolonged study. Examples of these professions include accountancy, actuarial computation, architecture, dentistry, engineering, law, medicine, nursing, pharmacy, the sciences (such as biology...

ExpoCast: Exposure Science for Prioritization and Toxicity Testing (T)

EPA Science Inventory

The US EPA National Center for Computational Toxicology (NCCT) has a mission to integrate modern computing and information technology with molecular biology to improve Agency prioritization of data requirements and risk assessment of chemicals. Recognizing the critical need for ...

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

Biologically Relevant Exposure Science for 21st Century Toxicity Testing

EPA Science Inventory

High visibility efforts in toxicity testing and computational toxicology including the recent NRC report, Toxicity Testing in the 21st Century: a Vision and Strategy (NRC, 2007), raise important research questions and opportunities for the field of exposure science. The authors ...

Twenty Years of Symbiosis Between Art and Science

ERIC Educational Resources Information Center

Reichardt, Jasia

1974-01-01

During the past two decades advances in biology, nuclear physics, computer and material sciences, and audiovisual engineering have brought a radically new dimension to most art forms and have stimulated the artist and his innovations to breath-taking levels of achievement. (Editor/JR)

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 neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.

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 neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology. Copyright © 2014. Published by Elsevier B.V.

The Benefits of Making Data from the EPA National Center for Computational Toxicology available for reuse (ACS Fall meeting 3 of 12)

EPA Science Inventory

Researchers at EPA’s National Center for Computational Toxicology (NCCT) integrate advances in biology, chemistry, exposure and computer science to help prioritize chemicals for further research based on potential human health risks. The goal of this research is to quickly evalua...

[Computational chemistry in structure-based drug design].

PubMed

Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu

2013-07-01

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.

A new parallel DNA algorithm to solve the task scheduling problem based on inspired computational model.

PubMed

Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei

2017-12-01

As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.

2017 ISCB Overton Prize: Christoph Bock

PubMed Central

Fogg, Christiana N.; Kovats, Diane E.; Berger, Bonnie

2017-01-01

The International Society for Computational Biology (ISCB) each year recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, an admired computational biologist and founding ISCB Board member. Winners of the Overton Prize are independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching, and service. ISCB is pleased to recognize Dr. Christoph Bock, Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, Austria, as the 2017 winner of the Overton Prize. Bock will be presenting a keynote presentation at the 2017 International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Prague, Czech Republic being held during July 21-25, 2017. PMID:28713546

2017 ISCB Overton Prize: Christoph Bock.

PubMed

Fogg, Christiana N; Kovats, Diane E; Berger, Bonnie

2017-01-01

The International Society for Computational Biology (ISCB) each year recognizes the achievements of an early to mid-career scientist with the Overton Prize. This prize honors the untimely death of Dr. G. Christian Overton, an admired computational biologist and founding ISCB Board member. Winners of the Overton Prize are independent investigators who are in the early to middle phases of their careers and are selected because of their significant contributions to computational biology through research, teaching, and service. ISCB is pleased to recognize Dr. Christoph Bock, Principal Investigator at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, Austria, as the 2017 winner of the Overton Prize. Bock will be presenting a keynote presentation at the 2017 International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology (ISMB/ECCB) in Prague, Czech Republic being held during July 21-25, 2017.

TEACHING "MATH-LITE" CONSERVATION (BOOK REVIEW OF CONSERVATION BIOLOGY WITH RAMAS ECOLAB)

EPA Science Inventory

This book is designed to serve as a laboratory workbook for an undergraduate course in conservation biology, environmental science, or natural resource management. By integrating with RAMAS EcoLab software, the book provides instructors with hands-on computer exercises that can ...

Abstracts of Research, July 1975-June 1976.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in computer and information science are given for 62 papers in the areas of information storage and retrieval; computer facilities; information analysis; linguistics analysis; artificial intelligence; information processes in physical, biological, and social systems; mathematical technigues; systems programming;…

It's All in Your Head

ERIC Educational Resources Information Center

Ennis, Lisa A.

2007-01-01

The dynamic and rapidly expanding field of neuroscience traditionally has involved the study of the nervous system from a biological/medical standpoint. In recent years, however, the science has become multidisciplinary, attracting researchers from computer science, psychology, sociology, philosophy, and even the humanities. For public and college…

Laboratory directed research and development program FY 1997

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

NONE

1998-03-01

This report compiles the annual reports of Laboratory Directed Research and Development projects supported by the Berkeley Lab. Projects are arranged under the following topical sections: (1) Accelerator and fusion research division; (2) Chemical sciences division; (3) Computing Sciences; (4) Earth sciences division; (5) Environmental energy technologies division; (6) life sciences division; (7) Materials sciences division; (8) Nuclear science division; (9) Physics division; (10) Structural biology division; and (11) Cross-divisional. A total of 66 projects are summarized.

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…

Representations, approximations, and limitations within a computational framework for cognitive science. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by W. Tecumseh Fitch

NASA Astrophysics Data System (ADS)

Perfors, Amy

2014-09-01

There is much to approve of in this provocative and interesting paper. I strongly agree in many parts, especially the point that dichotomies like nature/nurture are actively detrimental to the field. I also appreciate the idea that cognitive scientists should take the "biological wetware" of the cell (rather than the network) more seriously.

Whales and Hermit Crabs: Integrated Programming and Science.

ERIC Educational Resources Information Center

Kataoka, Joy C.; Lock, Robin

1995-01-01

This article describes an integrated program in marine biology. The program was implemented in a nongraded inclusive setting with second- to fourth-grade students whose abilities ranged from gifted to learning disabled. The program integrated science, art, music, language arts, and research and computer skills. (DB)

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.

Bacteria as computers making computers

PubMed Central

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments. PMID:19016882

Bacteria as computers making computers.

PubMed

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments.

Mother, Earth, Father Sky Symposium

NASA Technical Reports Server (NTRS)

Bowman, B.

1977-01-01

A conference was held in which minority aerospace scientists and engineers interacted with the minority community, particularly at the junior high, high school, and college levels. There were two presentations in the biological sciences, two in the physical and environmental sciences, seven in engineering and computer sciences, and nine in aerospace science and engineering. Aerospace technology careers and aerospace activities were discussed as to how they are relevant to minorities and women.

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

Meta!Blast computer game: a pipeline from science to 3D art to education

NASA Astrophysics Data System (ADS)

Schneller, William; Campbell, P. J.; Bassham, Diane; Wurtele, Eve Syrkin

2012-03-01

Meta!Blast (http://www.metablast.org) is designed to address the challenges students often encounter in understanding cell and metabolic biology. Developed by faculty and students in biology, biochemistry, computer science, game design, pedagogy, art and story, Meta!Blast is being created using Maya (http://usa.autodesk.com/maya/) and the Unity 3D (http://unity3d.com/) game engine, for Macs and PCs in classrooms; it has also been exhibited in an immersive environment. Here, we describe the pipeline from protein structural data and holographic information to art to the threedimensional (3D) environment to the game engine, by which we provide a publicly-available interactive 3D cellular world that mimics a photosynthetic plant cell.

Machine learning for Big Data analytics in plants.

PubMed

Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

2014-12-01

Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

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),

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

ERIC Educational Resources Information Center

Tataw, Oben Moses

2013-01-01

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

Oak Ridge National Laboratory Core Competencies

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

Roberto, J.B.; Anderson, T.D.; Berven, B.A.

1994-12-01

A core competency is a distinguishing integration of capabilities which enables an organization to deliver mission results. Core competencies represent the collective learning of an organization and provide the capacity to perform present and future missions. Core competencies are distinguishing characteristics which offer comparative advantage and are difficult to reproduce. They exhibit customer focus, mission relevance, and vertical integration from research through applications. They are demonstrable by metrics such as level of investment, uniqueness of facilities and expertise, and national impact. The Oak Ridge National Laboratory (ORNL) has identified four core competencies which satisfy the above criteria. Each core competencymore » represents an annual investment of at least $100M and is characterized by an integration of Laboratory technical foundations in physical, chemical, and materials sciences; biological, environmental, and social sciences; engineering sciences; and computational sciences and informatics. The ability to integrate broad technical foundations to develop and sustain core competencies in support of national R&D goals is a distinguishing strength of the national laboratories. The ORNL core competencies are: 9 Energy Production and End-Use Technologies o Biological and Environmental Sciences and Technology o Advanced Materials Synthesis, Processing, and Characterization & Neutron-Based Science and Technology. The distinguishing characteristics of each ORNL core competency are described. In addition, written material is provided for two emerging competencies: Manufacturing Technologies and Computational Science and Advanced Computing. Distinguishing institutional competencies in the Development and Operation of National Research Facilities, R&D Integration and Partnerships, Technology Transfer, and Science Education are also described. Finally, financial data for the ORNL core competencies are summarized in the appendices.« less

Project Solo; Newsletter Number Seven.

ERIC Educational Resources Information Center

Pittsburgh Univ., PA. Project Solo.

The current curriculum modules under development at Project Solo are listed. The modules are grouped under the subject matter that they are designed to teach--algebra II, biology, calculus, chemistry, computer science, 12th grade math, physics, social science. Special programs written for use on the Hewlett-Packard Plotter are listed that may be…

Spinning a Web Around Forensic Science and Senior Biology.

ERIC Educational Resources Information Center

Harrison, Colin R.

1999-01-01

Discusses a project that was established to integrate computer technology, especially the Internet, into the science classroom. Argues for the importance of providing students with a program of study that exposes them to the widest possible range of ways of gathering information for problem solving. (Author/WRM)

Education through the prism of computation

NASA Astrophysics Data System (ADS)

Kaurov, Vitaliy

2014-03-01

With the rapid development of technology, computation claims its irrevocable place among research components of modern science. Thus to foster a successful future scientist, engineer or educator we need to add computation to the foundations of scientific education. We will discuss what type of paradigm shifts it brings to these foundations on the example of Wolfram Science Summer School. It is one of the most advanced computational outreach programs run by Wolfram Foundation, welcoming participants of almost all ages and backgrounds. Centered on complexity science and physics, it also covers numerous adjacent and interdisciplinary fields such as finance, biology, medicine and even music. We will talk about educational and research experiences in this program during the 12 years of its existence. We will review statistics and outputs the program has produced. Among these are interactive electronic publications at the Wolfram Demonstrations Project and contributions to the computational knowledge engine Wolfram|Alpa.

Applications of large-scale density functional theory in biology

NASA Astrophysics Data System (ADS)

Cole, Daniel J.; Hine, Nicholas D. M.

2016-10-01

Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

Evaluation of an Educational Computer Programme as a Change Agent in Science Classrooms

NASA Astrophysics Data System (ADS)

Muwanga-Zake, Johnnie Wycliffe Frank

2007-12-01

I report on benefits from 26 teacher-participant evaluators of a computer game designed to motivate learning and to ease conceptual understanding of biology in South Africa. Using a developmental, social constructivist and interpretative model, the recommendation is to include the value systems and needs of end-users (through social dialogue); curriculum issues (learning theories in the ECP and those the education authorities recommend, as well as ECP-curriculum integration); the nature of the subject the ECP presents (e.g., Nature of Science); and the compatibility of the ECP with school computers.

Women's decision to major in STEM fields

NASA Astrophysics Data System (ADS)

Conklin, Stephanie

This paper explores the lived experiences of high school female students who choose to enter into STEM fields, and describes the influencing factors which steered these women towards majors in computer science, engineering and biology. Utilizing phenomenological methodology, this study seeks to understand the essence of women's decisions to enter into STEM fields and further describe how the decision-making process varies for women in high female enrollment fields, like biology, as compared with low enrollment fields like, computer science and engineering. Using Bloom's 3-Stage Theory, this study analyzes how relationships, experiences and barriers influenced women towards, and possibly away, from STEM fields. An analysis of women's experiences highlight that support of family, sustained experience in a STEM program during high school as well as the presence of an influential teacher were all salient factors in steering women towards STEM fields. Participants explained that influential teacher worked individually with them, modified and extended assignments and also steered participants towards coursework and experiences. This study also identifies factors, like guidance counselors as well as personal challenges, which inhibited participant's path to STEM fields. Further, through analyzing all six participants' experiences, it is clear that a linear model, like Bloom's 3-Stage Model, with limited ability to include potential barriers inhibited the ability to capture the essence of each participant's decision-making process. Therefore, a revised model with no linear progression which allows for emerging factors, like personal challenges, has been proposed; this model focuses on how interest in STEM fields begins to develop and is honed and then mastered. This study also sought to identify key differences in the paths of female students pursuing different majors. The findings of this study suggest that the path to computer science and engineering is limited. Computer science majors faced few, if any, challenges, hoped to use computers as a tool to innovate and also participated in the same computer science program. For female engineering students, the essence of their experience focused on interaction at a young age with an expert in an engineering-related field as well as a strong desire to help solve world problems using engineering. These participants were able to articulate clearly future careers. In contrast, biology majors, faced more challenges and were undecided about their future career goals. These results suggest that a longitudinal study focused on women pursuing engineering and computer science fields is warranted; this will hopefully allow these findings to be substantiated and also for refinement of the revised theoretical model.

Micro-separation toward systems biology.

PubMed

Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

2006-02-17

Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

A Qualitative Study of Students' Computational Thinking Skills in a Data-Driven Computing Class

ERIC Educational Resources Information Center

Yuen, Timothy T.; Robbins, Kay A.

2014-01-01

Critical thinking, problem solving, the use of tools, and the ability to consume and analyze information are important skills for the 21st century workforce. This article presents a qualitative case study that follows five undergraduate biology majors in a computer science course (CS0). This CS0 course teaches programming within a data-driven…

NeXT Application Development Workshop. [Use and Design of Instructional Applications on the NeXT Computer.

ERIC Educational Resources Information Center

Kiel, Don; And Others

Instructional applications for NeXT computers were developed by nine faculty members from the biology, mathematics and computer science, fine arts, chemistry, physics and astronomy, and geology departments as part of a grant awarded to the California State University at Los Angeles. These notes provide a schedule of events and reports from a 2-day…

Building machines that adapt and compute like brains.

PubMed

Kriegeskorte, Nikolaus; Mok, Robert M

2017-01-01

Building machines that learn and think like humans is essential not only for cognitive science, but also for computational neuroscience, whose ultimate goal is to understand how cognition is implemented in biological brains. A new cognitive computational neuroscience should build cognitive-level and neural-level models, understand their relationships, and test both types of models with both brain and behavioral data.

Final Report: A Broad Research Project on the Sciences of Complexity, September 15, 1994 - November 15, 1999

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

None

2000-02-01

DOE support for a broad research program in the sciences of complexity permitted the Santa Fe Institute to initiate new collaborative research within its integrative core activities as well as to host visitors to participate in research on specific topics that serve as motivation and testing ground for the study of the general principles of complex systems. Results are presented on computational biology, biodiversity and ecosystem research, and advanced computing and simulation.

The 1984 NASA/ASEE summer faculty fellowship program

NASA Technical Reports Server (NTRS)

Mcinnis, B. C.; Duke, M. B.; Crow, B.

1984-01-01

An overview is given of the program management and activities. Participants and research advisors are listed. Abstracts give describe and present results of research assignments performed by 31 fellows either at the Johnson Space Center, at the White Sands test Facility, or at the California Space Institute in La Jolla. Disciplines studied include engineering; biology/life sciences; Earth sciences; chemistry; mathematics/statistics/computer sciences; and physics/astronomy.

Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.

PubMed

Spirov, Alexander; Holloway, David

2013-07-15

This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.

A Project-Based Biologically-Inspired Robotics Module

ERIC Educational Resources Information Center

Crowder, R. M.; Zauner, K.-P.

2013-01-01

The design of any robotic system requires input from engineers from a variety of technical fields. This paper describes a project-based module, "Biologically-Inspired Robotics," that is offered to Electronics and Computer Science students at the University of Southampton, U.K. The overall objective of the module is for student groups to…

Biomimetic robots using EAP as artificial muscles - progress and challenges

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph

2004-01-01

Biology offers a great model for emulation in areas ranging from tools, computational algorithms, materials science, mechanisms and information technology. In recent years, the field of biomimetics, namely mimicking biology, has blossomed with significant advances enabling the reverse engineering of many animals' functions and implementation of some of these capabilities.

77 FR 57569 - Science Advisory Board to the National Center for Toxicological Research; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-18

... overview of research activities from the NCTR Division of Bioinformatics and Computational Biology and the Division of Systems Biology. The SAB will also receive and update from the subcommittee on Immunotoxicology... advisory committee meetings and will make every effort to accommodate persons with physical disabilities or...

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).

Meeting Report: Incorporating Genomics Research into Undergraduate Curricula

ERIC Educational Resources Information Center

Dyer, Betsey Dexter; LeBlanc, Mark D.

2002-01-01

In the first of two National Science Foundation (NSF)-funded workshops, 30 professors of biology and computer science from 18 institutions met at Wheaton College in Norton, Massachusetts, on June 6-7, 2002, to share ideas on how to incorporate genomics research into undergraduate curricula. The participants included nine pairs or trios of…

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

Virtual fetal pig dissection as an agent of knowledge acquisition and attitudinal change in female high school biology students

NASA Astrophysics Data System (ADS)

Maloney, Rebecca Scudari

One way to determine if all students can learn through the use of computers is to introduce a lesson taught completely via computers and compare the results with those gained when the same lesson is taught in a traditional manner. This study attempted to determine if a virtual fetal pig dissection can be used as a viable alternative for an actual dissection for females enrolled in high school biology classes by comparing the knowledge acquisition and attitudinal change between the experimental (virtual dissection) and control (actual dissection) groups. Two hundred and twenty-four students enrolled in biology classes in a suburban all-girl parochial high school participated in this study. Female students in an all-girl high school were chosen because research shows differences in science competency and computer usage between the genders that may mask the performance of females on computer-based tasks in a science laboratory exercise. Students who completed the virtual dissection scored significantly higher on practical test and objective tests that were used to measure knowledge acquisition. Attitudinal change was measured by examining the students' attitudes toward dissections, computer usage in the classroom, and toward biology both before and after the dissections using pre and post surveys. Significant results in positive gain scores were found in the virtual dissection group's attitude toward dissections, and their negative gain score toward virtual dissections. Attitudinal changes toward computers and biology were not significant. A purposefully selected sample of the students were interviewed, in addition to gathering a sample of the students' daily dissection journals, as data highlighting their thoughts and feelings about their dissection experience. Further research is suggested to determine if a virtual laboratory experience can be a substitute for actual dissections, or may serve as an enhancement to an actual dissection.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

A Seminar in Mathematical Model-Building.

ERIC Educational Resources Information Center

Smith, David A.

1979-01-01

A course in mathematical model-building is described. Suggested modeling projects include: urban problems, biology and ecology, economics, psychology, games and gaming, cosmology, medicine, history, computer science, energy, and music. (MK)

An Undergraduate Research Experience Studying Ras and Ras Mutants

ERIC Educational Resources Information Center

Griffeth, Nancy; Batista, Naralys; Grosso, Terri; Arianna, Gianluca; Bhatia, Ravnit; Boukerche, Faiza; Crispi, Nicholas; Fuller, Neno; Gauza, Piotr; Kingsbury, Lyle; Krynski, Kamil; Levine, Alina; Ma, Rui Yan; Nam, Jennifer; Pearl, Eitan; Rosa, Alessandro; Salarbux, Stephanie; Sun, Dylan

2016-01-01

Each January from 2010 to 2014, an undergraduate workshop on modeling biological systems was held at Lehman College of the City University of New York. The workshops were funded by a National Science Foundation (NSF) Expedition in Computing, "Computational Modeling and Analysis of Complex Systems (CMACS)." The primary goal was to…

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

Is there room for ethics within bioinformatics education?

PubMed

Taneri, Bahar

2011-07-01

When bioinformatics education is considered, several issues are addressed. At the undergraduate level, the main issue revolves around conveying information from two main and different fields: biology and computer science. At the graduate level, the main issue is bridging the gap between biology students and computer science students. However, there is an educational component that is rarely addressed within the context of bioinformatics education: the ethics component. Here, a different perspective is provided on bioinformatics education, and the current status of ethics is analyzed within the existing bioinformatics programs. Analysis of the existing undergraduate and graduate programs, in both Europe and the United States, reveals the minimal attention given to ethics within bioinformatics education. Given that bioinformaticians speedily and effectively shape the biomedical sciences and hence their implications for society, here redesigning of the bioinformatics curricula is suggested in order to integrate the necessary ethics education. Unique ethical problems awaiting bioinformaticians and bioinformatics ethics as a separate field of study are discussed. In addition, a template for an "Ethics in Bioinformatics" course is provided.

Underlying Principles of Natural Selection in Network Evolution: Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Wu, Wei-Sheng

2007-01-01

Systems biology is a rapidly expanding field that integrates diverse areas of science such as physics, engineering, computer science, mathematics, and biology toward the goal of elucidating the underlying principles of hierarchical metabolic and regulatory systems in the cell, and ultimately leading to predictive understanding of cellular response to perturbations. Because post-genomics research is taking place throughout the tree of life, comparative approaches offer a way for combining data from many organisms to shed light on the evolution and function of biological networks from the gene to the organismal level. Therefore, systems biology can build on decades of theoretical work in evolutionary biology, and at the same time evolutionary biology can use the systems biology approach to go in new uncharted directions. In this study, we present a review of how the post-genomics era is adopting comparative approaches and dynamic system methods to understand the underlying design principles of network evolution and to shape the nascent field of evolutionary systems biology. Finally, the application of evolutionary systems biology to robust biological network designs is also discussed from the synthetic biology perspective. PMID:19468310

Complex network problems in physics, computer science and biology

NASA Astrophysics Data System (ADS)

Cojocaru, Radu Ionut

There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe lattice at zero temperature and then we apply this formalism to the K-SAT problem defined in Chapter 1. The phase transition which physicists study often corresponds to a change in the computational complexity of the corresponding computer science problem. Chapter 3 presents phase transitions which are specific to the problems discussed in Chapter 1 and also known results for the K-SAT problem. We discuss the replica method and experimental evidences of replica symmetry breaking. The physics approach to hard problems is based on replica methods which are difficult to understand. In Chapter 4 we develop novel methods for studying hard problems using methods similar to the message passing techniques that were discussed in Chapter 2. Although we concentrated on the symmetric case, cavity methods show promise for generalizing our methods to the un-symmetric case. As has been highlighted by John Hopfield, several key features of biological systems are not shared by physical systems. Although living entities follow the laws of physics and chemistry, the fact that organisms adapt and reproduce introduces an essential ingredient that is missing in the physical sciences. In order to extract information from networks many algorithm have been developed. In Chapter 5 we apply polynomial algorithms like minimum spanning tree in order to study and construct gene regulatory networks from experimental data. As future work we propose the use of algorithms like min-cut/max-flow and Dijkstra for understanding key properties of these networks.

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.

Understanding Life : The Evolutionary Dynamics of Complexity and Semiosis

NASA Astrophysics Data System (ADS)

Loeckenhoff, Helmut K.

2010-11-01

Post-Renaissance sciences created different cultures. To establish an epistemological base, Physics were separated from the Mental domain. Consciousness was excluded from science. Life Sciences were left in between e.g. LaMettrie's `man—machine' (1748) and 'vitalism' [e.g. Bergson 4]. Causative thinking versus intuitive arguing limited strictly comprehensive concepts. First ethology established a potential shared base for science, proclaiming the `biology paradigm' in the middle of the 20th century. Initially procured by Cybernetics and Systems sciences, `constructivist' models prepared a new view on human perception and thus also of scientific `objectivity when introducing the `observer'. In sequel Computer sciences triggered the ICT revolution. In turn ICT helped to develop Chaos and Complexity sciences, Non-linear Mathematics and its spin-offs in the formal sciences [Spencer-Brown 49] as e.g. (proto-)logics. Models of life systems, as e.g. Anticipatory Systems, integrated epistemology with mathematics and Anticipatory Computing [Dubois 11, 12, 13, 14] connecting them with Semiotics. Seminal ideas laid in the turn of the 19th to the 20th century [J. v. Uexküll 53] detected the co-action and co-evolvement of environments and life systems. Bio-Semiotics ascribed purpose, intent and meaning as essential qualities of life. The concepts of Systems Biology and Qualitative Research enriched and develop also anthropologies and humanities. Brain research added models of (higher) consciousness. An avant-garde is contemplating a science including consciousness as one additional base. New insights from the extended qualitative approach led to re-conciliation of basic assumptions of scientific inquiry, creating the `epistemological turn'. Paradigmatically, resting on macro- micro- and recently on nano-biology, evolution biology sired fresh scripts of evolution [W. Wieser 60,61]. Its results tie to hypotheses describing the emergence of language, of the human mind and of culture [e.g. R. Logan 34]. The different but related approaches are yet but loosely connected. Recent efforts search for a shared foundation e.g. in a set of Transdisciplinary base models [Loeckenhoff 30, 31]. The domain of pure mental constructions as ideologies/religions and spiritual phenomena will be implied.

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.

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.

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

NASA Astrophysics Data System (ADS)

Takano, Yu; Kobayashi, Nobuhiko; Morikawa, Yoshitada

2018-06-01

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

Data Integration and Mining for Synthetic Biology Design.

PubMed

Mısırlı, Göksel; Hallinan, Jennifer; Pocock, Matthew; Lord, Phillip; McLaughlin, James Alastair; Sauro, Herbert; Wipat, Anil

2016-10-21

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

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

PubMed Central

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

2014-01-01

This editorial provides insights into how informatics can attract highly trained students by involving them in science, technology, engineering, and math (STEM) training at the high school level and continuing to provide mentorship and research opportunities through the formative years of their education. Our central premise is that the trajectory necessary to be expert in the emergent fields in front of them requires acceleration at an early time point. Both pathology (and biomedical) informatics are new disciplines which would benefit from involvement by students at an early stage of their education. In 2009, Michael T Lotze MD, Kirsten Livesey (then a medical student, now a medical resident at University of Pittsburgh Medical Center (UPMC)), Richard Hersheberger, PhD (Currently, Dean at Roswell Park), and Megan Seippel, MS (the administrator) launched the University of Pittsburgh Cancer Institute (UPCI) Summer Academy to bring high school students for an 8 week summer academy focused on Cancer Biology. Initially, pathology and biomedical informatics were involved only in the classroom component of the UPCI Summer Academy. In 2011, due to popular interest, an informatics track called Computer Science, Biology and Biomedical Informatics (CoSBBI) was launched. CoSBBI currently acts as a feeder program for the undergraduate degree program in bioinformatics at the University of Pittsburgh, which is a joint degree offered by the Departments of Biology and Computer Science. We believe training in bioinformatics is the best foundation for students interested in future careers in pathology informatics or biomedical informatics. We describe our approach to the recruitment, training and research mentoring of high school students to create a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics. We emphasize here how mentoring of high school students in pathology informatics and biomedical informatics will be critical to assuring their success as leaders in the era of big data and personalized medicine. PMID:24860688

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

PubMed

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

2014-01-01

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

Can a Tablet Device Alter Undergraduate Science Students' Study Behavior and Use of Technology?

ERIC Educational Resources Information Center

Morris, Neil P.; Ramsay, Luke; Chauhan, Vikesh

2012-01-01

This article reports findings from a study investigating undergraduate biological sciences students' use of technology and computer devices for learning and the effect of providing students with a tablet device. A controlled study was conducted to collect quantitative and qualitative data on the impact of a tablet device on students' use of…

Thinking Through Computational Exposure as an Evolving Paradign Shift for Exposure Science: Development and Application of Predictive Models from Big Data

EPA Science Inventory

Symposium Abstract: Exposure science has evolved from a time when the primary focus was on measurements of environmental and biological media and the development of enabling field and laboratory methods. The Total Exposure Assessment Method (TEAM) studies of the 1980s were class...

arXiv.org and Physics Education

ERIC Educational Resources Information Center

Ramlo, Susan

2007-01-01

The website arXiv.org (pronounced "archive") is a free online resource for full-text articles in the fields of physics, mathematics, computer science, nonlinear science, and quantitative biology that has existed for about 15 years. Available directly at http://www.arXiv.org, this e-print archive is searchable. As of Jan. 3, 2007, arXiv had open…

Innovations in Science Teaching. The Forum for Liberal Education, Volume II, Number 4, February, 1980.

ERIC Educational Resources Information Center

Mohrman, Kathryn, Ed.

Curricular development in undergraduate programs in the biological, physical, and mathematical sciences at a number of colleges and universities are described. One common theme is the continuing interest in computers in higher education. As the student bodies of many campuses become more heterogeneous with increasing enrollments of minorities and…

Record Number of Summer Students Work at Ames in 2014

NASA Image and Video Library

2014-09-16

NASA's Ames Research Center concluded the 2014 summer student program session that featured a record number of participants from around the globe. More than 1,100 students with high school- to graduate-level education took part in a wide variety of science activities. Some of the activities included robotics, aeronautics, biology, computer science, engineering and astrophysics.

Report of the Defense Science Board Task Force on University Responsiveness to National Security Requirements.

DTIC Science & Technology

1982-01-01

R.ugustine Chairman iv OFFICE OF THE SECRETARY OF DEFENSE WASHINGTON, D.C. 20301 27 January 1982 DEFENSE SCIENCIE BOARD Mr. Norman R. Augustine Chai rman...Institute of Technology Dr. Norman Hackerman President Rice University Dr. Richard L. Haley Assistant Deputy Science and Technology USA Material ...Biological and Medical Sciences 51.8 67.8 22% Materials 53.2 65.1 13% Chemistry 47.8 60.1 17% Math and Computer Sciences 44.2 53.6 12% Oceanography 43.2

Students from Aurora Triumph in Competition of the Mind

Science.gov Websites

fast-paced questions about physics, math, biology, astronomy, chemistry, computers and the earth educational programs to help stimulate young people's interest in science and math. NR-00797

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1984

1984-01-01

Presents 28 activities, games, demonstrations, experiments, and computer programs for biology, chemistry, physics, and conservation education. Background information, laboratory procedures, equipment lists, and instructional strategies are included. Topics include nature conservation, chickens in school, human anatomy, nitrogen cycle, mechanism…

Evaluation of an Educational Computer Programme as a Change Agent in Science Classrooms

ERIC Educational Resources Information Center

Muwanga-Zake, Johnnie Wycliffe Frank

2007-01-01

I report on benefits from 26 teacher-participant evaluators of a computer game designed to motivate learning and to ease conceptual understanding of biology in South Africa. Using a developmental, social constructivist and interpretative model, the recommendation is to include the value systems and needs of end-users (through social dialogue);…

Computer-Based Learning Packages Have a Role, but Care Needs to Be Given as to When They Are Delivered

ERIC Educational Resources Information Center

Quinn, Joseph G.; King, Karen; Roberts, David; Carey, Linda; Mousley, Angela

2009-01-01

It is compulsory for first year biological science students at Queens University Belfast to complete a range of assessed, laboratory-based practicals in various scientific procedures including dissection. This study investigates student performance and attitudes when they have to complete a traditional dissection and a computer based learning…

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets.

PubMed

McKinney, Bill; Meyer, Peter A; Crosas, Mercè; Sliz, Piotr

2017-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension-functionality supporting preservation of file system structure within Dataverse-which is essential for both in-place computation and supporting non-HTTP data transfers. © 2016 New York Academy of Sciences.

Effectiveness of a Computer-Mediated Simulations Program in School Biology on Pupils' Learning Outcomes in Cell Theory

ERIC Educational Resources Information Center

Kiboss, Joel K.; Ndirangu, Mwangi; Wekesa, Eric W.

2004-01-01

Biology knowledge and understanding is important not only for the conversion of the loftiest dreams into reality for a better life of individuals but also for preparing secondary pupils for such fields as agriculture, medicine, biotechnology, and genetic engineering. But a recent study has revealed that many aspects of school science (biology…

University-Level Practical Activities in Bioinformatics Benefit Voluntary Groups of Pupils in the Last 2 Years of School

ERIC Educational Resources Information Center

Barker, Daniel; Alderson, Rosanna G.; McDonagh, James L.; Plaisier, Heleen; Comrie, Muriel M.; Duncan, Leigh; Muirhead, Gavin T. P.; Sweeney, Stuart D.

2015-01-01

Background: Bioinformatics--the use of computers in biology--is of major and increasing importance to biological sciences and medicine. We conducted a preliminary investigation of the value of bringing practical, university-level bioinformatics education to the school level. We conducted voluntary activities for pupils at two schools in Scotland…

The Effectiveness of a Virtual Field Trip (VFT) Module in Learning Biology

ERIC Educational Resources Information Center

Haris, Norbaizura; Osman, Kamisah

2015-01-01

Virtual Field Trip is a computer aided module of science developed to study the Colonisation and Succession in Mangrove Swamps, as an alternative to the real field trip in Form for Biology. This study is to identify the effectiveness of the Virtual Field Trip (VFT) module towards the level of achievement in the formative test for this topic. This…

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Colorado Students Contend in Competition of the Mind

Science.gov Websites

-paced match of questions about physics, math, biology, astronomy, chemistry, computers and the earth one of its premier educational programs to help stimulate young people's interest in science and math

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1984

1984-01-01

Presents 26 activities, experiments, demonstrations, games, and computer programs for biology, chemistry, and physics. Background information, laboratory procedures, equipment lists, and instructional strategies are given. Topics include eye measurements, nutrition, soil test tube rack, population dynamics, angular momentum, transition metals,…

Varieties of noise: analogical reasoning in synthetic biology.

PubMed

Knuuttila, Tarja; Loettgers, Andrea

2014-12-01

The picture of synthetic biology as a kind of engineering science has largely created the public understanding of this novel field, covering both its promises and risks. In this paper, we will argue that the actual situation is more nuanced and complex. Synthetic biology is a highly interdisciplinary field of research located at the interface of physics, chemistry, biology, and computational science. All of these fields provide concepts, metaphors, mathematical tools, and models, which are typically utilized by synthetic biologists by drawing analogies between the different fields of inquiry. We will study analogical reasoning in synthetic biology through the emergence of the functional meaning of noise, which marks an important shift in how engineering concepts are employed in this field. The notion of noise serves also to highlight the differences between the two branches of synthetic biology: the basic science-oriented branch and the engineering-oriented branch, which differ from each other in the way they draw analogies to various other fields of study. Moreover, we show that fixing the mapping between a source domain and the target domain seems not to be the goal of analogical reasoning in actual scientific practice.

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

Mathematics and statistics research progress report, period ending June 30, 1983

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

Beauchamp, J. J.; Denson, M. V.; Heath, M. T.

1983-08-01

This report is the twenty-sixth in the series of progress reports of Mathematics and Statistics Research of the Computer Sciences organization, Union Carbide Corporation Nuclear Division. Part A records research progress in analysis of large data sets, applied analysis, biometrics research, computational statistics, materials science applications, numerical linear algebra, and risk analysis. Collaboration and consulting with others throughout the Oak Ridge Department of Energy complex are recorded in Part B. Included are sections on biological sciences, energy, engineering, environmental sciences, health and safety, and safeguards. Part C summarizes the various educational activities in which the staff was engaged. Part Dmore » lists the presentations of research results, and Part E records the staff's other professional activities during the report period.« less

Addressing the Digital Divide in Contemporary Biology: Lessons from Teaching UNIX.

PubMed

Mangul, Serghei; Martin, Lana S; Hoffmann, Alexander; Pellegrini, Matteo; Eskin, Eleazar

2017-10-01

Life and medical science researchers increasingly rely on applications that lack a graphical interface. Scientists who are not trained in computer science face an enormous challenge analyzing high-throughput data. We present a training model for use of command-line tools when the learner has little to no prior knowledge of UNIX. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optic Glomeruli: Biological Circuits that Compute Target Identity

DTIC Science & Technology

2013-11-01

vitripennis. Insect Mol. Biol. Suppl. 1:121-36. Strausfeld NJ. 2012. Arthropod Brains. Evolution , Functional Elegance and Historical Significance. Harvard...Neuroscience and Center for Insect Science University of Arizona Tucson, AZ 85721 Contract No. FA8651-10-1-0001 November 2013 FINAL REPORT...PERFORMING ORGANIZATION REPORT NUMBER Department of Neuroscience and Center for Insect Science University of Arizona Tucson, AZ 85721

75 FR 10491 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-08

...: Computational Biology, Image Processing, and Data Mining. Date: March 18, 2010. Time: 8 a.m. to 6 p.m. Agenda... Science. Date: March 24, 2010. Time: 12 p.m. to 3:30 p.m. Agenda: To review and evaluate grant...; Fellowship: Biophysical and Biochemical Sciences. Date: March 25-26, 2010. Time: 8 a.m. to 5 p.m. Agenda: To...

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

PubMed

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

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

Why Machine-Information Metaphors are Bad for Science and Science Education

NASA Astrophysics Data System (ADS)

Pigliucci, Massimo; Boudry, Maarten

2011-05-01

Genes are often described by biologists using metaphors derived from computational science: they are thought of as carriers of information, as being the equivalent of "blueprints" for the construction of organisms. Likewise, cells are often characterized as "factories" and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Importantly, modern proponents of Intelligent Design, the latest version of creationism, have exploited biologists' use of the language of information and blueprints to make their spurious case, based on pseudoscientific concepts such as "irreducible complexity" and on flawed analogies between living cells and mechanical factories. However, the living organism = machine analogy was criticized already by David Hume in his Dialogues Concerning Natural Religion. In line with Hume's criticism, over the past several years a more nuanced and accurate understanding of what genes are and how they operate has emerged, ironically in part from the work of computational scientists who take biology, and in particular developmental biology, more seriously than some biologists seem to do. In this article we connect Hume's original criticism of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. Thus, we argue that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public.

Cultural stereotypes as gatekeepers: increasing girls' interest in computer science and engineering by diversifying stereotypes.

PubMed

Cheryan, Sapna; Master, Allison; Meltzoff, Andrew N

2015-01-01

Despite having made significant inroads into many traditionally male-dominated fields (e.g., biology, chemistry), women continue to be underrepresented in computer science and engineering. We propose that students' stereotypes about the culture of these fields-including the kind of people, the work involved, and the values of the field-steer girls away from choosing to enter them. Computer science and engineering are stereotyped in modern American culture as male-oriented fields that involve social isolation, an intense focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities that are typically more valued in men than women in American culture. As a result, when computer science and engineering stereotypes are salient, girls report less interest in these fields than their male peers. However, altering these stereotypes-by broadening the representation of the people who do this work, the work itself, and the environments in which it occurs-significantly increases girls' sense of belonging and interest in the field. Academic stereotypes thus serve as gatekeepers, driving girls away from certain fields and constraining their learning opportunities and career aspirations.

Cultural stereotypes as gatekeepers: increasing girls’ interest in computer science and engineering by diversifying stereotypes

PubMed Central

Cheryan, Sapna; Master, Allison; Meltzoff, Andrew N.

2015-01-01

Despite having made significant inroads into many traditionally male-dominated fields (e.g., biology, chemistry), women continue to be underrepresented in computer science and engineering. We propose that students’ stereotypes about the culture of these fields—including the kind of people, the work involved, and the values of the field—steer girls away from choosing to enter them. Computer science and engineering are stereotyped in modern American culture as male-oriented fields that involve social isolation, an intense focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities that are typically more valued in men than women in American culture. As a result, when computer science and engineering stereotypes are salient, girls report less interest in these fields than their male peers. However, altering these stereotypes—by broadening the representation of the people who do this work, the work itself, and the environments in which it occurs—significantly increases girls’ sense of belonging and interest in the field. Academic stereotypes thus serve as gatekeepers, driving girls away from certain fields and constraining their learning opportunities and career aspirations. PMID:25717308

Artificial-life researchers try to create social reality.

PubMed

Flam, F

1994-08-12

Some scientists, among them cosmologist Stephen Hawking, argue that computer viruses are alive. A better case might be made for many of the self-replicating silicon-based creatures featured at the fourth Conference on Artificial Life, held on 5 to 8 July in Boston. Researchers from computer science, biology, and other disciplines presented computer programs that, among other things, evolved cooperative strategies in a selfish world and recreated themselves in ever more complex forms.

From biological and social network metaphors to coupled bio-social wireless networks

PubMed Central

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

Report of the matrix of biological knowledge workshop

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

Morowitz, H.J.; Smith, T.

1987-10-30

Current understanding of biology involves complex relationships rooted in enormous amounts of data. These data include entries from biochemistry, ecology, genetics, human and veterinary medicine, molecular structure studies, agriculture, embryology, systematics, and many other disciplines. The present wealth of biological data goes beyond past accumulations now include new understandings from molecular biology. Several important biological databases are currently being supported, and more are planned; however, major problems of interdatabase communication and management efficiency abound. Few scientists are currently capable of keeping up with this ever-increasing wealth of knowledge, let alone searching it efficiently for new or unsuspected links and importantmore » analogies. Yet this is what is required if the continued rapid generation of such data is to lead most effectively to the major conceptual, medical, and agricultural advances anticipated over the coming decades in the United States. The opportunity exists to combine the potential of modern computer science, database management, and artificial intelligence in a major effort to organize the vast wealth of biological and clinical data. The time is right because the amount of data is still manageable even in its current highly-fragmented form; important hardware and computer science tools have been greatly improved; and there have been recent fundamental advances in our comprehension of biology. This latter is particularly true at the molecular level where the information for nearly all higher structure and function is encoded. The organization of all biological experimental data coordinately within a structure incorporating our current understanding - the Matrix of Biological Knowledge - will provide the data and structure for the major advances foreseen in the years ahead.« less

Journal news

USGS Publications Warehouse

Conroy, M.J.; Samuel, M.D.; White, Joanne C.

1995-01-01

Statistical power (and conversely, Type II error) is often ignored by biologists. Power is important to consider in the design of studies, to ensure that sufficient resources are allocated to address a hypothesis under examination. Deter- mining appropriate sample size when designing experiments or calculating power for a statistical test requires an investigator to consider the importance of making incorrect conclusions about the experimental hypothesis and the biological importance of the alternative hypothesis (or the biological effect size researchers are attempting to measure). Poorly designed studies frequently provide results that are at best equivocal, and do little to advance science or assist in decision making. Completed studies that fail to reject Ho should consider power and the related probability of a Type II error in the interpretation of results, particularly when implicit or explicit acceptance of Ho is used to support a biological hypothesis or management decision. Investigators must consider the biological question they wish to answer (Tacha et al. 1982) and assess power on the basis of biologically significant differences (Taylor and Gerrodette 1993). Power calculations are somewhat subjective, because the author must specify either f or the minimum difference that is biologically important. Biologists may have different ideas about what values are appropriate. While determining biological significance is of central importance in power analysis, it is also an issue of importance in wildlife science. Procedures, references, and computer software to compute power are accessible; therefore, authors should consider power. We welcome comments or suggestions on this subject.

Hierarchy, determinism, and specificity in theories of development and evolution.

PubMed

Deichmann, Ute

2017-10-16

The concepts of hierarchical organization, genetic determinism and biological specificity (for example of species, biologically relevant macromolecules, or genes) have played a crucial role in biology as a modern experimental science since its beginnings in the nineteenth century. The idea of genetic information (specificity) and genetic determination was at the basis of molecular biology that developed in the 1940s with macromolecules, viruses and prokaryotes as major objects of research often labelled "reductionist". However, the concepts have been marginalized or rejected in some of the research that in the late 1960s began to focus additionally on the molecularization of complex biological structures and functions using systems approaches. This paper challenges the view that 'molecular reductionism' has been successfully replaced by holism and a focus on the collective behaviour of cellular entities. It argues instead that there are more fertile replacements for molecular 'reductionism', in which genomics, embryology, biochemistry, and computer science intertwine and result in research that is as exact and causally predictive as earlier molecular biology.

High School Students Gear Up for Battle of the Brains

Science.gov Websites

answer tournament, which focuses on physics, math, biology, astronomy, chemistry, computers and the earth to help stimulate interest in science and math. The competition has evolved into one of the Energy

For the Love of Statistics: Appreciating and Learning to Apply Experimental Analysis and Statistics through Computer Programming Activities

ERIC Educational Resources Information Center

Mascaró, Maite; Sacristán, Ana Isabel; Rufino, Marta M.

2016-01-01

For the past 4 years, we have been involved in a project that aims to enhance the teaching and learning of experimental analysis and statistics, of environmental and biological sciences students, through computational programming activities (using R code). In this project, through an iterative design, we have developed sequences of R-code-based…

Applications of artificial neural networks in medical science.

PubMed

Patel, Jigneshkumar L; Goyal, Ramesh K

2007-09-01

Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

Biological X-ray absorption spectroscopy (BioXAS): a valuable tool for the study of trace elements in the life sciences.

PubMed

Strange, Richard W; Feiters, Martin C

2008-10-01

Using X-ray absorption spectroscopy (XAS) the binding modes (type and number of ligands, distances and geometry) and oxidation states of metals and other trace elements in crystalline as well as non-crystalline samples can be revealed. The method may be applied to biological systems as a 'stand-alone' technique, but it is particularly powerful when used alongside other X-ray and spectroscopic techniques and computational approaches. In this review, we highlight how biological XAS is being used in concert with crystallography, spectroscopy and computational chemistry to study metalloproteins in crystals, and report recent applications on relatively rare trace elements utilised by living organisms and metals involved in neurodegenerative diseases.

Text-mining and information-retrieval services for molecular biology

PubMed Central

Krallinger, Martin; Valencia, Alfonso

2005-01-01

Text-mining in molecular biology - defined as the automatic extraction of information about genes, proteins and their functional relationships from text documents - has emerged as a hybrid discipline on the edges of the fields of information science, bioinformatics and computational linguistics. A range of text-mining applications have been developed recently that will improve access to knowledge for biologists and database annotators. PMID:15998455

Fiji: an open-source platform for biological-image analysis.

PubMed

Schindelin, Johannes; Arganda-Carreras, Ignacio; Frise, Erwin; Kaynig, Verena; Longair, Mark; Pietzsch, Tobias; Preibisch, Stephan; Rueden, Curtis; Saalfeld, Stephan; Schmid, Benjamin; Tinevez, Jean-Yves; White, Daniel James; Hartenstein, Volker; Eliceiri, Kevin; Tomancak, Pavel; Cardona, Albert

2012-06-28

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity

PubMed Central

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand “complex behavior” and complexity theory, and from which important biological insight can be gained. PMID:24999297

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity.

PubMed

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand "complex behavior" and complexity theory, and from which important biological insight can be gained.

Peculiarities of organization of project and research activity of students in computer science, physics and technology

NASA Astrophysics Data System (ADS)

Stolyarov, I. V.

2017-01-01

The author of this article manages a project and research activity of students in the areas of computer science, physics, engineering and biology, basing on the acquired experience in these fields. Pupils constantly become winners of competitions and conferences of different levels, for example, three of the finalists of Intel ISEF in 2013 in Phoenix (Arizona, USA) and in 2014 in Los Angeles (California, USA). In 2013 A. Makarychev received the "Small Nobel prize" in Computer Science section and special award sponsors - the company's CAST. Scientific themes and methods suggested by the author and developed in joint publications of students from Russia, Germany and Austria are the patents for invention and certificates for registration in the ROSPATENT. The article presents the results of the implementation of specific software and hardware systems in physics, engineering and medicine.

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

Finite Dimensional Approximations for Continuum Multiscale Problems

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

Berlyand, Leonid

2017-01-24

The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less

Exploratory Research and Development Fund, FY 1990

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

Not Available

1992-05-01

The Lawrence Berkeley Laboratory Exploratory R D Fund FY 1990 report is compiled from annual reports submitted by principal investigators following the close of the fiscal year. This report describes the projects supported and summarizes their accomplishments. It constitutes a part of an Exploratory R D Fund (ERF) planning and documentation process that includes an annual planning cycle, projection selection, implementation, and review. The research areas covered in this report are: Accelerator and fusion research; applied science; cell and molecular biology; chemical biodynamics; chemical sciences; earth sciences; engineering; information and computing sciences; materials sciences; nuclear science; physics and research medicinemore » and radiation biophysics.« less

Towards systemic theories in biological psychiatry.

PubMed

Bender, W; Albus, M; Möller, H-J; Tretter, F

2006-02-01

Although still rather controversial, empirical data on the neurobiology of schizophrenia have reached a degree of complexity that makes it hard to obtain a coherent picture of the malfunctions of the brain in schizophrenia. Theoretical neuropsychiatry should therefore use the tools of theoretical sciences like cybernetics, informatics, computational neuroscience or systems science. The methodology of systems science permits the modeling of complex dynamic nonlinear systems. Such procedures might help us to understand brain functions and the disorders and actions of psychiatric drugs better.

What is bioinformatics? A proposed definition and overview of the field.

PubMed

Luscombe, N M; Greenbaum, D; Gerstein, M

2001-01-01

The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

Mathematics and Statistics Research Department progress report, period ending June 30, 1982

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

Denson, M.V.; Funderlic, R.E.; Gosslee, D.G.

1982-08-01

This report is the twenty-fifth in the series of progress reports of the Mathematics and Statistics Research Department of the Computer Sciences Division, Union Carbide Corporation Nuclear Division (UCC-ND). Part A records research progress in analysis of large data sets, biometrics research, computational statistics, materials science applications, moving boundary problems, numerical linear algebra, and risk analysis. Collaboration and consulting with others throughout the UCC-ND complex are recorded in Part B. Included are sections on biology, chemistry, energy, engineering, environmental sciences, health and safety, materials science, safeguards, surveys, and the waste storage program. Part C summarizes the various educational activities inmore » which the staff was engaged. Part D lists the presentations of research results, and Part E records the staff's other professional activities during the report period.« less

Visualization in simulation tools: requirements and a tool specification to support the teaching of dynamic biological processes.

PubMed

Jørgensen, Katarina M; Haddow, Pauline C

2011-08-01

Simulation tools are playing an increasingly important role behind advances in the field of systems biology. However, the current generation of biological science students has either little or no experience with such tools. As such, this educational glitch is limiting both the potential use of such tools as well as the potential for tighter cooperation between the designers and users. Although some simulation tool producers encourage their use in teaching, little attempt has hitherto been made to analyze and discuss their suitability as an educational tool for noncomputing science students. In general, today's simulation tools assume that the user has a stronger mathematical and computing background than that which is found in most biological science curricula, thus making the introduction of such tools a considerable pedagogical challenge. This paper provides an evaluation of the pedagogical attributes of existing simulation tools for cell signal transduction based on Cognitive Load theory. Further, design recommendations for an improved educational simulation tool are provided. The study is based on simulation tools for cell signal transduction. However, the discussions are relevant to a broader biological simulation tool set.

A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm

PubMed Central

Chen, Jui-Le; Yang, Chu-Sing

2013-01-01

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. PMID:23762864

Enlist micros: Training science teachers to use microcomputers

NASA Astrophysics Data System (ADS)

Baird, William E.; Ellis, James D.; Kuerbis, Paul J.

A National Science Foundation grant to the Biological Sciences Curriculum Study (BSCS) at The Colorado College supported the design and production of training materials to encourage literacy of science teachers in the use of microcomputers. ENLIST Micros is based on results of a national needs assessment that identified 22 compentencies needed by K-12 science teachers to use microcomputers for instruction. A writing team developed the 16-hour training program in the summer of 1985, and field-test coordinators tested it with 18 preservice or in-service groups during the 1985-86 academic year at 15 sites within the United States. The training materials consist of video programs, interactive computer disks for the Apple II series microcomputer, a training manual for participants, and a guide for the group leader. The experimental materials address major areas of educational computing: awareness, applications, implementation, evaluation, and resources. Each chapter contains activities developed for this program, such as viewing video segments of science teachers who are using computers effectively and running commercial science and training courseware. Role playing and small-group interaction help the teachers overcome their reluctance to use computers and plan for effective implementation of microcomputers in the school. This study examines the implementation of educational computing among 47 science teachers who completed the ENLIST Micros training at a southern university. We present results of formative evaluation for that site. Results indicate that both elementary and secondary teachers benefit from the training program and demonstrate gains in attitudes toward computer use. Participating teachers said that the program met its stated objectives and helped them obtain needed skills. Only 33 percent of these teachers, however, reported using computers one year after the training. In June 1986, the BSCS initiated a follow up to the ENLIST Micros curriculum to develop, evaluate, and disseminate a complete model of teacher enhancement for educational computing in the sciences. In that project, we use the ENLIST Micros curriculum as the first step in a training process. The project includes seminars that introduce additional skills: It contains provisions for sharing among participants, monitors use of computers in participants' classrooms, provides structured coaching of participants' use of computers in their classrooms, and offers planned observations of peers using computers in their science teaching.

Remediation of Groundwater Contaminated by Nuclear Waste

NASA Astrophysics Data System (ADS)

Parker, Jack; Palumbo, Anthony

2008-07-01

A Workshop on Accelerating Development of Practical Field-Scale Bioremediation Models; An Online Meeting, 23 January to 20 February 2008; A Web-based workshop sponsored by the U.S. Department of Energy Environmental Remediation Sciences Program (DOE/ERSP) was organized in early 2008 to assess the state of the science and knowledge gaps associated with the use of computer models to facilitate remediation of groundwater contaminated by wastes from Cold War era nuclear weapons development and production. Microbially mediated biological reactions offer a potentially efficient means to treat these sites, but considerable uncertainty exists in the coupled biological, chemical, and physical processes and their mathematical representation.

Training in Methods in Computational Neuroscience

DTIC Science & Technology

1989-11-14

inferior colliculus served as inputs to a sheet of 100 cells within the medial geniculate body where combination sensitivity is first observed. Inputs from...course is for advanced graduate students and postdoctoral fellows in neurobiology , physics, electrical engineering, computer science and psychology...Research Code 1142BI 800 N. Quincy St Arlington, VA 22217-5000 Paul Adams Department of Neurobiology SUNY, Stony Brook Graduate Biology Building 576

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.

Theoretical computer science and the natural sciences

NASA Astrophysics Data System (ADS)

Marchal, Bruno

2005-12-01

I present some fundamental theorems in computer science and illustrate their relevance in Biology and Physics. I do not assume prerequisites in mathematics or computer science beyond the set N of natural numbers, functions from N to N, the use of some notational conveniences to describe functions, and at some point, a minimal amount of linear algebra and logic. I start with Cantor's transcendental proof by diagonalization of the non enumerability of the collection of functions from natural numbers to the natural numbers. I explain why this proof is not entirely convincing and show how, by restricting the notion of function in terms of discrete well defined processes, we are led to the non algorithmic enumerability of the computable functions, but also-through Church's thesis-to the algorithmic enumerability of partial computable functions. Such a notion of function constitutes, with respect to our purpose, a crucial generalization of that concept. This will make easy to justify deep and astonishing (counter-intuitive) incompleteness results about computers and similar machines. The modified Cantor diagonalization will provide a theory of concrete self-reference and I illustrate it by pointing toward an elementary theory of self-reproduction-in the Amoeba's way-and cellular self-regeneration-in the flatworm Planaria's way. To make it easier, I introduce a very simple and powerful formal system known as the Schoenfinkel-Curry combinators. I will use the combinators to illustrate in a more concrete way the notion introduced above. The combinators, thanks to their low-level fine grained design, will also make it possible to make a rough but hopefully illuminating description of the main lessons gained by the careful observation of nature, and to describe some new relations, which should exist between computer science, the science of life and the science of inert matter, once some philosophical, if not theological, hypotheses are made in the cognitive sciences. In the last section, I come back to self-reference and I give an exposition of its modal logics. This is used to show that theoretical computer science makes those “philosophical hypotheses” in theoretical cognitive science experimentally and mathematically testable.

77 FR 57571 - Center For Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-18

...: Genes, Genomes, and Genetics Integrated Review Group; Genomics, Computational Biology and Technology... Reproductive Sciences Integrated Review Group; Cellular, Molecular and Integrative Reproduction Study Section...: Immunology Integrated Review Group; Cellular and Molecular Immunology--B Study Section. [[Page 57572

Abstracts of Research. July 1974-June 1975.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in computer and information science are given for 68 papers in the areas of information storage and retrieval; human information processing; information analysis; linguistic analysis; artificial intelligence; information processes in physical, biological, and social systems; mathematical techniques; systems…

Science Notes.

ERIC Educational Resources Information Center

School Science Review, 1987

1987-01-01

Contains 21 articles ranging from instructional experiments to topical information. Deals with investigation of plant rust diseases, using computers to teach biology, plant roots, a biotechnology curriculum, the corrosion of oxides, electrochemical simulations, the Reimer-Tiemann reaction, the oxidation of aldehydes, and the extraction of iodine…

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.

Partly cloudy with a chance of migration: Weather, radars, and aeroecology

USGS Publications Warehouse

Chilson, Phillip B.; Frick, Winifred F.; Kelly, Jeffrey F.; Howard, Kenneth W.; Larkin, Ronald P.; Diehl, Robert H.; Westbrook, John K.; Kelly, T. Adam; Kunz, Thomas H.

2012-01-01

Aeroecology is an emerging scientific discipline that integrates atmospheric science, Earth science, geography, ecology, computer science, computational biology, and engineering to further the understanding of biological patterns and processes. The unifying concept underlying this new transdisciplinary field of study is a focus on the planetary boundary layer and lower free atmosphere (i.e., the aerosphere), and the diversity of airborne organisms that inhabit and depend on the aerosphere for their existence. Here, we focus on the role of radars and radar networks in aeroecological studies. Radar systems scanning the atmosphere are primarily used to monitor weather conditions and track the location and movements of aircraft. However, radar echoes regularly contain signals from other sources, such as airborne birds, bats, and arthropods. We briefly discuss how radar observations can be and have been used to study a variety of airborne organisms and examine some of the many potential benefits likely to arise from radar aeroecology for meteorological and biological research over a wide range of spatial and temporal scales. Radar systems are becoming increasingly sophisticated with the advent of innovative signal processing and dual-polarimetric capabilities. These capabilities should be better harnessed to promote both meteorological and aeroecological research and to explore the interface between these two broad disciplines. We strongly encourage close collaboration among meteorologists, radar scientists, biologists, and others toward developing radar products that will contribute to a better understanding of airborne fauna.

Brookhaven highlights. Report on research, October 1, 1992--September 30, 1993

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

Rowe, M.S.; Belford, M.; Cohen, A.

This report highlights the research activities of Brookhaven National Laboratory during the period dating from October 1, 1992 through September 30, 1993. There are contributions to the report from different programs and departments within the laboratory. These include technology transfer, RHIC, Alternating Gradient Synchrotron, physics, biology, national synchrotron light source, applied science, medical science, advanced technology, chemistry, reactor physics, safety and environmental protection, instrumentation, and computing and communications.

Comparing Lanes in the Pulsed-Field Gel Electrophoresis (PFGE) Images

DTIC Science & Technology

2001-10-25

Department of Computer and Information Science, National Chiao Tung University, Hsin Chu Taiwan 2 Department of Biological Science and Technology, National...Chiao Tung University Hsin Chu Taiwan Performing Organization Report Number Sponsoring/Monitoring Agency Name(s) and Address(es) US Army Research...image contains several lanes. And each lane consists of bands. Two lanes are identical if the relative positions of bands are the same. We present a

New Frontiers in Language Evolution and Development.

PubMed

Oller, D Kimbrough; Dale, Rick; Griebel, Ulrike

2016-04-01

This article introduces the Special Issue and its focus on research in language evolution with emphasis on theory as well as computational and robotic modeling. A key theme is based on the growth of evolutionary developmental biology or evo-devo. The Special Issue consists of 13 articles organized in two sections: A) Theoretical foundations and B) Modeling and simulation studies. All the papers are interdisciplinary in nature, encompassing work in biological and linguistic foundations for the study of language evolution as well as a variety of computational and robotic modeling efforts shedding light on how language may be developed and may have evolved. Copyright © 2016 Cognitive Science Society, Inc.

Research approaches to mass casualty incidents response: development from routine perspectives to complexity science.

PubMed

Shen, Weifeng; Jiang, Libing; Zhang, Mao; Ma, Yuefeng; Jiang, Guanyu; He, Xiaojun

2014-01-01

To review the research methods of mass casualty incident (MCI) systematically and introduce the concept and characteristics of complexity science and artificial system, computational experiments and parallel execution (ACP) method. We searched PubMed, Web of Knowledge, China Wanfang and China Biology Medicine (CBM) databases for relevant studies. Searches were performed without year or language restrictions and used the combinations of the following key words: "mass casualty incident", "MCI", "research method", "complexity science", "ACP", "approach", "science", "model", "system" and "response". Articles were searched using the above keywords and only those involving the research methods of mass casualty incident (MCI) were enrolled. Research methods of MCI have increased markedly over the past few decades. For now, dominating research methods of MCI are theory-based approach, empirical approach, evidence-based science, mathematical modeling and computer simulation, simulation experiment, experimental methods, scenario approach and complexity science. This article provides an overview of the development of research methodology for MCI. The progresses of routine research approaches and complexity science are briefly presented in this paper. Furthermore, the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems. And the only feasible alternative is complexity science. Finally, this summary is followed by a review that ACP method combining artificial systems, computational experiments and parallel execution provides a new idea to address researches for complex MCI.

Neurobiomimetic constructs for intelligent unmanned systems and robotics

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Shah, Danelle C.; DeAngelus, Marianne A.

2014-06-01

This paper discusses a paradigm we refer to as neurobiomimetic, which involves emulations of brain neuroanatomy and neurobiology aspects and processes. Neurobiomimetic constructs include rudimentary and down-scaled computational representations of brain regions, sub-regions, and synaptic connectivity. Many different instances of neurobiomimetic constructs are possible, depending on various aspects such as the initial conditions of synaptic connectivity, number of neuron elements in regions, connectivity specifics, and more, and we refer to these instances as `animats'. While downscaled for computational feasibility, the animats are very large constructs; the animats implemented in this work contain over 47,000 neuron elements and over 720,000 synaptic connections. The paper outlines aspects of the animats implemented, spatial memory and learning cognitive task, the virtual-reality environment constructed to study the animat performing that task, and discussion of results. In a broad sense, we argue that the neurobiomimetic paradigm pursued in this work constitutes a particularly promising path to artificial cognition and intelligent unmanned systems. Biological brains readily cope with challenges of real-life tasks that consistently prove beyond even the most sophisticated algorithmic approaches known. At the cross-over point of neuroscience, cognitive science and computer science, paradigms such as the one pursued in this work aim to mimic the mechanisms of biological brains and as such, we argue, may lead to machines with abilities closer to those of biological species.

High Throughput Screening of Toxicity Pathways Perturbed by Environmental Chemicals

EPA Science Inventory

Toxicology, a field largely unchanged over the past several decades, is undergoing a significant transformation driven by a number of forces – the increasing number of chemicals needing assessment, changing legal requirements, advances in biology and computer science, and concern...

Home - Virginia Department of Forensic Science

Science.gov Websites

Procedure Manuals Training Manuals Digital & Multimedia Evidence Computer Analysis Video Analysis Procedure Manual Training Manual FAQ Updates Firearms & Toolmarks Procedure Manuals Training Manuals Forensic Biology Procedure Manuals Training Manuals Familial Searches Post-Conviction DNA Issues FAQ

An information technology emphasis in biomedical informatics education.

PubMed

Kane, Michael D; Brewer, Jeffrey L

2007-02-01

Unprecedented growth in the interdisciplinary domain of biomedical informatics reflects the recent advancements in genomic sequence availability, high-content biotechnology screening systems, as well as the expectations of computational biology to command a leading role in drug discovery and disease characterization. These forces have moved much of life sciences research almost completely into the computational domain. Importantly, educational training in biomedical informatics has been limited to students enrolled in the life sciences curricula, yet much of the skills needed to succeed in biomedical informatics involve or augment training in information technology curricula. This manuscript describes the methods and rationale for training students enrolled in information technology curricula in the field of biomedical informatics, which augments the existing information technology curriculum and provides training on specific subjects in Biomedical Informatics not emphasized in bioinformatics courses offered in life science programs, and does not require prerequisite courses in the life sciences.

Exploratory Research and Development Fund, FY 1990. Report on Lawrence Berkeley Laboratory

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

Not Available

1992-05-01

The Lawrence Berkeley Laboratory Exploratory R&D Fund FY 1990 report is compiled from annual reports submitted by principal investigators following the close of the fiscal year. This report describes the projects supported and summarizes their accomplishments. It constitutes a part of an Exploratory R&D Fund (ERF) planning and documentation process that includes an annual planning cycle, projection selection, implementation, and review. The research areas covered in this report are: Accelerator and fusion research; applied science; cell and molecular biology; chemical biodynamics; chemical sciences; earth sciences; engineering; information and computing sciences; materials sciences; nuclear science; physics and research medicine and radiationmore » biophysics.« less

The EPA Comptox Chemistry Dashboard: A Web-Based Data ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data driven approaches that integrate chemistry, exposure and biological data. As an outcome of these efforts the National Center for Computational Toxicology (NCCT) has measured, assembled and delivered an enormous quantity and diversity of data for the environmental sciences including high-throughput in vitro screening data, in vivo and functional use data, exposure models and chemical databases with associated properties. A series of software applications and databases have been produced over the past decade to deliver these data but recent developments have focused on the development of a new software architecture that assembles the resources into a single platform. A new web application, the CompTox Chemistry Dashboard provides access to data associated with ~720,000 chemical substances. These data include experimental and predicted physicochemical property data, bioassay screening data associated with the ToxCast program, product and functional use information and a myriad of related data of value to environmental scientists. The dashboard provides chemical-based searching based on chemical names, synonyms and CAS Registry Numbers. Flexible search capabilities allow for chemical identificati

Biomedical informatics training at the University of Wisconsin-Madison.

PubMed

Severtson, D J; Pape, L; Page, C D; Shavlik, J W; Phillips, G N; Flatley Brennan, P

2007-01-01

The purpose of this paper is to describe biomedical informatics training at the University of Wisconsin-Madison (UW-Madison). We reviewed biomedical informatics training, research, and faculty/trainee participation at UW-Madison. There are three primary approaches to training 1) The Computation & Informatics in Biology & Medicine Training Program, 2) formal biomedical informatics offered by various campus departments, and 3) individualized programs. Training at UW-Madison embodies the features of effective biomedical informatics training recommended by the American College of Medical Informatics that were delineated as: 1) curricula that integrate experiences among computational sciences and application domains, 2) individualized and interdisciplinary cross-training among a diverse cadre of trainees to develop key competencies that he or she does not initially possess, 3) participation in research and development activities, and 4) exposure to a range of basic informational and computational sciences. The three biomedical informatics training approaches immerse students in multidisciplinary training and education that is supported by faculty trainers who participate in collaborative research across departments. Training is provided across a range of disciplines and available at different training stages. Biomedical informatics training at UW-Madison illustrates how a large research University, with multiple departments across biological, computational and health fields, can provide effective and productive biomedical informatics training via multiple bioinformatics training approaches.

The EPA CompTox Chemistry Dashboard - an online resource ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data driven approaches that integrate chemistry, exposure and biological data. As an outcome of these efforts the National Center for Computational Toxicology (NCCT) has measured, assembled and delivered an enormous quantity and diversity of data for the environmental sciences including high-throughput in vitro screening data, in vivo and functional use data, exposure models and chemical databases with associated properties. A series of software applications and databases have been produced over the past decade to deliver these data. Recent work has focused on the development of a new architecture that assembles the resources into a single platform. With a focus on delivering access to Open Data streams, web service integration accessibility and a user-friendly web application the CompTox Dashboard provides access to data associated with ~720,000 chemical substances. These data include research data in the form of bioassay screening data associated with the ToxCast program, experimental and predicted physicochemical properties, product and functional use information and related data of value to environmental scientists. This presentation will provide an overview of the CompTox Dashboard and its va

OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

NASA Astrophysics Data System (ADS)

Strayer, Michael

2005-01-01

Good morning. Welcome to SciDAC 2005 and San Francisco. SciDAC is all about computational science and scientific discovery. In a large sense, computational science characterizes SciDAC and its intent is change. It transforms both our approach and our understanding of science. It opens new doors and crosses traditional boundaries while seeking discovery. In terms of twentieth century methodologies, computational science may be said to be transformational. There are a number of examples to this point. First are the sciences that encompass climate modeling. The application of computational science has in essence created the field of climate modeling. This community is now international in scope and has provided precision results that are challenging our understanding of our environment. A second example is that of lattice quantum chromodynamics. Lattice QCD, while adding precision and insight to our fundamental understanding of strong interaction dynamics, has transformed our approach to particle and nuclear science. The individual investigator approach has evolved to teams of scientists from different disciplines working side-by-side towards a common goal. SciDAC is also undergoing a transformation. This meeting is a prime example. Last year it was a small programmatic meeting tracking progress in SciDAC. This year, we have a major computational science meeting with a variety of disciplines and enabling technologies represented. SciDAC 2005 should position itself as a new corner stone for Computational Science and its impact on science. As we look to the immediate future, FY2006 will bring a new cycle to SciDAC. Most of the program elements of SciDAC will be re-competed in FY2006. The re-competition will involve new instruments for computational science, new approaches for collaboration, as well as new disciplines. There will be new opportunities for virtual experiments in carbon sequestration, fusion, and nuclear power and nuclear waste, as well as collaborations with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds immense promise. In this environment, I believe it is necessary to institute a system of science based performance metrics to help quantify our progress towards science goals and scientific computing. As a final comment I would like to reaffirm that the shifting landscapes of science will force changes to our computational sciences, and leave you with the quote from Richard Hamming, 'The purpose of computing is insight, not numbers'.

Connecting Theory and Applications Across Complex Systems

DTIC Science & Technology

2004-01-01

applications in biology and computer science. Fernando Pacanini received his Ingeniero Electricista and Licenciado en Matematica degrees from the...Carlson (pdf) (Pd ) breaks 3:30-4:00 10:30-11:00 3:30-4:00 10:30-11:00 El -Samad / Biology Arkin (ndf) Savageau (ndf) Mitra (tdf) Khammash (Pdf...including the Internet and forest ecology. Hana El -Samad is a PhD candidate at the Mechanical Engineering department of the University of California at

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

The information science of microbial ecology.

PubMed

Hahn, Aria S; Konwar, Kishori M; Louca, Stilianos; Hanson, Niels W; Hallam, Steven J

2016-06-01

A revolution is unfolding in microbial ecology where petabytes of 'multi-omics' data are produced using next generation sequencing and mass spectrometry platforms. This cornucopia of biological information has enormous potential to reveal the hidden metabolic powers of microbial communities in natural and engineered ecosystems. However, to realize this potential, the development of new technologies and interpretative frameworks grounded in ecological design principles are needed to overcome computational and analytical bottlenecks. Here we explore the relationship between microbial ecology and information science in the era of cloud-based computation. We consider microorganisms as individual information processing units implementing a distributed metabolic algorithm and describe developments in ecoinformatics and ubiquitous computing with the potential to eliminate bottlenecks and empower knowledge creation and translation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Nanotechnology and dentistry

PubMed Central

Ozak, Sule Tugba; Ozkan, Pelin

2013-01-01

Nanotechnology deals with the physical, chemical, and biological properties of structures and their components at nanoscale dimensions. Nanotechnology is based on the concept of creating functional structures by controlling atoms and molecules on a one-by-one basis. The use of this technology will allow many developments in the health sciences as well as in materials science, bio-technology, electronic and computer technology, aviation, and space exploration. With developments in materials science and biotechnology, nanotechnology is especially anticipated to provide advances in dentistry and innovations in oral health-related diagnostic and therapeutic methods. PMID:23408486

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

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

Gerber, Richard; Hack, James; Riley, Katherine

The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, andmore » deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain scientists, experts in computer science and applied mathematics, ASCR facility staff, and DOE program managers in ASCR and the respective program offices. The purpose of these reviews was to identify mission-critical scientific problems within the DOE Office of Science (including experimental facilities) and determine the requirements for the exascale ecosystem that would be needed to address those challenges. The exascale ecosystem includes exascale computing systems, high-end data capabilities, efficient software at scale, libraries, tools, and other capabilities. This effort will contribute to the development of a strategic roadmap for ASCR compute and data facility investments and will help the ASCR Facility Division establish partnerships with Office of Science stakeholders. It will also inform the Office of Science research needs and agenda. The results of the six reviews have been published in reports available on the web at http://exascaleage.org/. This report presents a summary of the individual reports and of common and crosscutting findings, and it identifies opportunities for productive collaborations among the DOE SC program offices.« less

Science and technology camp for girls. Final report

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

Not Available

1993-12-31

This document reports on the success of Pacific University`s camp held during the summers of 1992 and 1993; ultimate goal of this summer day camp was to increase the number of women in technical and scientific fields. Some experimentation was done with the age groups (7th and 8th grade girls). The curriculum was biology, chemistry, physics, and mathematics/computer science. Laboratory work and field trips were emphasized, along with socialization.

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

Adverse Outcome Pathways: A Conceptual Framework to Support Ecotoxicology Research and Risk Assessment

EPA Science Inventory

Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences are being developed to generate mechanistic informatio...

Adverse Outcome Pathways: A Conceptual Framework to Support Ecotoxicology Research and Risk Assessment

EPA Science Inventory

Ecological risk assessors face increasing demands to assess more chemicals, with greater speed and accuracy, and to do so using fewer resources and experimental animals. New approaches in biological and computational sciences may be able to generate mechanistic information that ...

Scientific conferences: A big hello to halogen bonding

NASA Astrophysics Data System (ADS)

Erdelyi, Mate

2014-09-01

Halogen bonding connects a wide range of subjects -- from materials science to structural biology, from computation to crystal engineering, and from synthesis to spectroscopy. The 1st International Symposium on Halogen Bonding explored the state of the art in this fast-growing field of research.

Laboratory Experiences in an Introduction to Natural Science Course.

ERIC Educational Resources Information Center

Barnard, Sister Marquita

1984-01-01

Describes a two-semester course designed to meet the needs of future elementary teachers, home economists, and occupational therapists. Laboratory work includes homemade calorimeters, inclined planes, and computing. Content areas of the course include measurement, physics, chemistry, astronomy, biology, geology, and meteorology. (JN)

Journal of Undergraduate Research, Volume IX, 2009

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

Stiner, K. S.; Graham, S.; Khan, M.

Each year more than 600 undergraduate students are awarded paid internships at the Department of Energy’s (DOE) National Laboratories. Th ese interns are paired with research scientists who serve as mentors in authentic research projects. All participants write a research abstract and present at a poster session and/or complete a fulllength research paper. Abstracts and selected papers from our 2007–2008 interns that represent the breadth and depth of undergraduate research performed each year at our National Laboratories are published here in the Journal of Undergraduate Research. The fields in which these students worked included: Biology; Chemistry; Computer Science; Engineering; Environmentalmore » Science; General Science; Materials Science; Medical and Health Sciences; Nuclear Science; Physics; Science Policy; and Waste Management.« less

Biologically inspired intelligent robots

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph; Breazeal, Cynthia

2003-07-01

Humans throughout history have always sought to mimic the appearance, mobility, functionality, intelligent operation, and thinking process of biological creatures. This field of biologically inspired technology, having the moniker biomimetics, has evolved from making static copies of human and animals in the form of statues to the emergence of robots that operate with realistic behavior. Imagine a person walking towards you where suddenly you notice something weird about him--he is not real but rather he is a robot. Your reaction would probably be "I can't believe it but this robot looks very real" just as you would react to an artificial flower that is a good imitation. You may even proceed and touch the robot to check if your assessment is correct but, as oppose to the flower case, the robot may be programmed to respond physical and verbally. This science fiction scenario could become a reality as the current trend continues in developing biologically inspired technologies. Technology evolution led to such fields as artificial muscles, artificial intelligence, and artificial vision as well as biomimetic capabilities in materials science, mechanics, electronics, computing science, information technology and many others. This paper will review the state of the art and challenges to biologically-inspired technologies and the role that EAP is expected to play as the technology evolves.

The GI Project: a prototype electronic textbook for high school biology.

PubMed

Calhoun, P S; Fishman, E K

1997-01-01

A prototype electronic science textbook for secondary education was developed to help bridge the gap between state-of-the-art medical technology and the basic science classroom. The prototype combines the latest in radiologic imaging techniques with a user-friendly multimedia computer program to teach the anatomy, physiology, and diseases of the gastrointestinal (GI) tract. The program includes original text, illustrations, photographs, animations, images from upper GI studies, plain radiographs, computed tomographic images, and three-dimensional reconstructions. These features are intended to create a stimulus-rich environment in which the high school science student can enjoy a variety of interactive experiences that will facilitate the learning process. The computer-based book is a new educational tool that promises to play a prominent role in the coming years. Current research suggests that computer-based books are valuable as an alternative educational medium. Although it is not yet clear what form textbooks will take in the future, computer-based books are already proving valuable as an alternative educational medium. For beginning students, they reinforce the material found in traditional textbooks and class presentations; for advanced students, they provide motivation to learn outside the traditional classroom.

A novel medical image data-based multi-physics simulation platform for computational life sciences.

PubMed

Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels

2013-04-06

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

Can a tablet device alter undergraduate science students' study behavior and use of technology?

PubMed

Morris, Neil P; Ramsay, Luke; Chauhan, Vikesh

2012-06-01

This article reports findings from a study investigating undergraduate biological sciences students' use of technology and computer devices for learning and the effect of providing students with a tablet device. A controlled study was conducted to collect quantitative and qualitative data on the impact of a tablet device on students' use of devices and technology for learning. Overall, we found that students made extensive use of the tablet device for learning, using it in preference to laptop computers to retrieve information, record lectures, and access learning resources. In line with other studies, we found that undergraduate students only use familiar Web 2.0 technologies and that the tablet device did not alter this behavior for the majority of tools. We conclude that undergraduate science students can make extensive use of a tablet device to enhance their learning opportunities without institutions changing their teaching methods or computer systems, but that institutional intervention may be needed to drive changes in student behavior toward the use of novel Web 2.0 technologies.

The Human Genome Project: big science transforms biology and medicine.

PubMed

Hood, Leroy; Rowen, Lee

2013-01-01

The Human Genome Project has transformed biology through its integrated big science approach to deciphering a reference human genome sequence along with the complete sequences of key model organisms. The project exemplifies the power, necessity and success of large, integrated, cross-disciplinary efforts - so-called 'big science' - directed towards complex major objectives. In this article, we discuss the ways in which this ambitious endeavor led to the development of novel technologies and analytical tools, and how it brought the expertise of engineers, computer scientists and mathematicians together with biologists. It established an open approach to data sharing and open-source software, thereby making the data resulting from the project accessible to all. The genome sequences of microbes, plants and animals have revolutionized many fields of science, including microbiology, virology, infectious disease and plant biology. Moreover, deeper knowledge of human sequence variation has begun to alter the practice of medicine. The Human Genome Project has inspired subsequent large-scale data acquisition initiatives such as the International HapMap Project, 1000 Genomes, and The Cancer Genome Atlas, as well as the recently announced Human Brain Project and the emerging Human Proteome Project.

Terahertz Radiation: A Non-contact Tool for the Selective Stimulation of Biological Responses in Human Cells

DTIC Science & Technology

2014-01-01

computational and empirical dosimetric tools [31]. For the computational dosimetry, we employed finite-dif- ference time- domain (FDTD) modeling techniques to...temperature-time data collected for a well exposed to THz radiation using finite-difference time- domain (FDTD) modeling techniques and thermocouples... like )). Alter- ation in the expression of such genes underscores the signif- 62 IEEE TRANSACTIONS ON TERAHERTZ SCIENCE AND TECHNOLOGY, VOL. 6, NO. 1

Online Bioinformatics Tutorials | Office of Cancer Genomics

Cancer.gov

Bioinformatics is a scientific discipline that applies computer science and information technology to help understand biological processes. The NIH provides a list of free online bioinformatics tutorials, either generated by the NIH Library or other institutes, which includes introductory lectures and "how to" videos on using various tools.

Language Networks as Complex Systems

ERIC Educational Resources Information Center

Lee, Max Kueiming; Ou, Sheue-Jen

2008-01-01

Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

Linguistic Extensions of Topic Models

ERIC Educational Resources Information Center

Boyd-Graber, Jordan

2010-01-01

Topic models like latent Dirichlet allocation (LDA) provide a framework for analyzing large datasets where observations are collected into groups. Although topic modeling has been fruitfully applied to problems social science, biology, and computer vision, it has been most widely used to model datasets where documents are modeled as exchangeable…

Test and Evaluation of Architecture-Aware Compiler Environment

DTIC Science & Technology

2011-11-01

biology, medicine, social sciences , and security applications. Challenges include extremely large graphs (the Facebook friend network has over...Operations with Temporal Binning ....................................................................... 32 4.12 Memory behavior and Energy per...five challenge problems empirically, exploring their scaling properties, computation and datatype needs, memory behavior , and temporal behavior

[Opinions of a group of university students about science and technology].

PubMed

Lisker, Rubén; Carnevale, Alessandra; Pérez Vera, Patricia; Betancourt, Miguel

2002-01-01

To learn the opinions of university students of four different areas on the impact of science and technology on society. One Hundred and sixty three close to graduate students of the Universidad Autonoma Metropolitana campus Iztapalapa, distributed as follows: Administration 59, Biology 50, Social Sciences 36 and Engineering 18. For the survey we translated into spanish part of a questionnaire employed in several countries to explore ideas on the impact of science and technology on society of several groups. It contained general questions such as. Do you believe that science and technology are equally good or bad to society, or degree of knowledge of several technologies such as computation or in vitro fertilization. It includes also more specific questions, such as would your have problems with the use of genetically modified vegetables? The results suggested that Administration and Social Sciences students had less interest in Science and Technology than the other, and that in general, the knowledge of all students is rather limited including biotechnology, genetic enginering and gene therapy. We compared the results with those obtained previously in a group of Mexican Physicians and Biology students from India, Thailand and Singapor.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Molecular dynamics simulations through GPU video games technologies

PubMed Central

Loukatou, Styliani; Papageorgiou, Louis; Fakourelis, Paraskevas; Filntisi, Arianna; Polychronidou, Eleftheria; Bassis, Ioannis; Megalooikonomou, Vasileios; Makałowski, Wojciech; Vlachakis, Dimitrios; Kossida, Sophia

2016-01-01

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations. PMID:27525251

System biology of gene regulation.

PubMed

Baitaluk, Michael

2009-01-01

A famous joke story that exhibits the traditionally awkward alliance between theory and experiment and showing the differences between experimental biologists and theoretical modelers is when a University sends a biologist, a mathematician, a physicist, and a computer scientist to a walking trip in an attempt to stimulate interdisciplinary research. During a break, they watch a cow in a field nearby and the leader of the group asks, "I wonder how one could decide on the size of a cow?" Since a cow is a biological object, the biologist responded first: "I have seen many cows in this area and know it is a big cow." The mathematician argued, "The true volume is determined by integrating the mathematical function that describes the outer surface of the cow's body." The physicist suggested: "Let's assume the cow is a sphere...." Finally the computer scientist became nervous and said that he didn't bring his computer because there is no Internet connection up there on the hill. In this humorous but explanatory story suggestions proposed by theorists can be taken to reflect the view of many experimental biologists that computer scientists and theorists are too far removed from biological reality and therefore their theories and approaches are not of much immediate usefulness. Conversely, the statement of the biologist mirrors the view of many traditional theoretical and computational scientists that biological experiments are for the most part simply descriptive, lack rigor, and that much of the resulting biological data are of questionable functional relevance. One of the goals of current biology as a multidisciplinary science is to bring people from different scientific areas together on the same "hill" and teach them to speak the same "language." In fact, of course, when presenting their data, most experimentalist biologists do provide an interpretation and explanation for the results, and many theorists/computer scientists aim to answer (or at least to fully describe) questions of biological relevance. Thus systems biology could be treated as such a socioscientific phenomenon and a new approach to both experiments and theory that is defined by the strategy of pursuing integration of complex data about the interactions in biological systems from diverse experimental sources using interdisciplinary tools and personnel.

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

Applying differential dynamic logic to reconfigurable biological networks.

PubMed

Figueiredo, Daniel; Martins, Manuel A; Chaves, Madalena

2017-09-01

Qualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used. Copyright © 2017 Elsevier Inc. All rights reserved.

Connections Matter: Social Networks and Lifespan Health in Primate Translational Models

PubMed Central

McCowan, Brenda; Beisner, Brianne; Bliss-Moreau, Eliza; Vandeleest, Jessica; Jin, Jian; Hannibal, Darcy; Hsieh, Fushing

2016-01-01

Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health. PMID:27148103

An Introduction to Programming for Bioscientists: A Python-Based Primer

PubMed Central

Mura, Cameron

2016-01-01

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language’s usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a “variable,” the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences. PMID:27271528

An Introduction to Programming for Bioscientists: A Python-Based Primer.

PubMed

Ekmekci, Berk; McAnany, Charles E; Mura, Cameron

2016-06-01

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a "variable," the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.

Computational Systems Biology and Dose Response Modeling Workshop, September 22-26, 2008

EPA Science Inventory

The recently published National Academy of Sciences (NAS) report “Toxicity Testing in the 21st Century” recommends a new approach to toxicity testing, based on evaluating cellular responses in a suite of toxicity pathway assays in human cells or cells lines in vitro. Such a parad...

Usage of Computers and Calculators and Students' Achievement: Results from TIMSS 2003

ERIC Educational Resources Information Center

Antonijevic, Radovan

2007-01-01

The paper deals with the facts obtained from TIMSS 2003 (Trends in International Mathematics and Science Study). This international comparative study, which includes 47 participant countries worldwide, explores dependence between eighth grade students' achievement in the areas of mathematics, physics, chemistry, biology and geography, and basic…

Hidden in the Middle: Culture, Value and Reward in Bioinformatics

ERIC Educational Resources Information Center

Lewis, Jamie; Bartlett, Andrew; Atkinson, Paul

2016-01-01

Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised…

Using a Business Framework to Teach Technical Writing to Nonscientists

ERIC Educational Resources Information Center

Devet, Bonnie

2005-01-01

Today, students other than biology, computer science, or physics majors are enrolling in technical writing. English and communication students, seeking lucrative careers as professional writers or editors, are increasingly signing up for the course. Lacking extensive scientific backgrounds, these students may have a difficult time writing about…

Agent-Based Models in Empirical Social Research

ERIC Educational Resources Information Center

Bruch, Elizabeth; Atwell, Jon

2015-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first…

Computer Simulations for Lab Experiences in Secondary Physics

ERIC Educational Resources Information Center

Murphy, David Shannon

2012-01-01

Physical science instruction often involves modeling natural systems, such as electricity that possess particles which are invisible to the unaided eye. The effect of these particles' motion is observable, but the particles are not directly observable to humans. Simulations have been developed in physics, chemistry and biology that, under certain…

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

Life on the borders

NASA Astrophysics Data System (ADS)

Barry, Edward

2010-02-01

Interdisciplinary science has been a hot topic for more than a decade, with increasing numbers of researchers working on projects that do not fit into neat departmental boxes like "physics" or "biology". Yet despite this increased activity, the structures in place to support these interdisciplinary scientists - including research grants and training for PhD students - have sometimes lagged behind. One programme that aims to help fill this gap for students of biomedical, physical and computational sciences is the Interfaces Initiative, a joint project of the Howard Hughes Medical Institute and the US National Institute of Biomedical Imaging and Bioengineering. Physics World talked to a current Interfaces participant, Edward Barry, who is finishing his PhD in biology-related condensed-matter physics at Brandeis University in Massachusetts.

Looking back: forward looking

PubMed Central

2017-01-01

Abstract GigaScience is now 5 years old, having been launched at the 2012 Intelligent Systems for Molecular Biology conference. Anyone who has attended what is the largest computational biology conference since then has had the opportunity to join us for each birthday celebration—and receive 1 of our fun T-shirts as a party prize. Since launching, we have pushed our agenda of openness, transparency, reproducibility, and reusability. Here, we look back at our first 5 years and what we have done to forward our open science goals in scientific publishing. Our mainstay has been to create a process that allows the availability and publication of as many “research objects” as possible to create a more complete way of communicating how the research process is done. PMID:28938718

The 159th national meeting of the American Association for the advancement of science

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

Not Available

This volume is the program/abstracts for the 1993 national meeting of the American Association for the Advancement of Science. The meeting was held in Boston from 11-16 February 1993. Symposia dealt with works on the following topics; perspectives on human genetics; confronting AIDS; biology, cells bugs; medical research society; social psychology neuroscience; future chemistry, from carbon to silicon; measuring the matter energy of the universe; earth's ever-changing atmosphere; causing coping with environmental change; agricultural biotechnology, plant protection production; science corporate enterprise; examining reforming the economic system; science, ethics the law; communicating science to the public; information technology the changing facemore » of science; mathematics, concepts computations; international cooperation human survival; science for everyone; science religion, examining both; anthropology, dynamics of human history; international science issues; improving formal science education; and science education reform in America. Separate abstracts have been prepared for articles from this volume.« less

Molecular mechanics and dynamics characterization of an in silico mutated protein: a stand-alone lab module or support activity for in vivo and in vitro analyses of targeted proteins.

PubMed

Chiang, Harry; Robinson, Lucy C; Brame, Cynthia J; Messina, Troy C

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems. Computer simulations of molecular events can now be accomplished quickly and with standard computer technology. Also, simulation software is freely available for most computing platforms, and online support for the novice user is ample. We have therefore created a molecular dynamics laboratory module to enhance undergraduate student understanding of molecular events underlying organismal phenotype. This module builds on a previously described project in which students use site-directed mutagenesis to investigate functions of conserved sequence features in members of a eukaryotic protein kinase family. In this report, we detail the laboratory activities of a MD module that provide a complement to phenotypic outcomes by providing a hypothesis-driven and quantifiable measure of predicted structural changes caused by targeted mutations. We also present examples of analyses students may perform. These laboratory activities can be integrated with genetics or biochemistry experiments as described, but could also be used independently in any course that would benefit from a quantitative approach to protein structure-function relationships. Copyright © 2013 Wiley Periodicals, Inc.

Quantitative and Qualitative Evaluation of The Structural Designing of Medical Informatics Dynamic Encyclopedia.

PubMed

Safdari, Reza; Shahmoradi, Leila; Hosseini-Beheshti, Molouk-Sadat; Nejad, Ahmadreza Farzaneh; Hosseiniravandi, Mohammad

2015-10-01

Encyclopedias and their compilation have become so prevalent as a valid cultural medium in the world. The daily development of computer industry and the expansion of various sciences have made indispensable the compilation of electronic, specialized encyclopedias, especially the web-based ones. This is an applied-developmental study conducted in 2014. First, the main terms in the field of medical informatics were gathered using MeSH Online 2014 and the supplementary terms of each were determined, and then the tree diagram of the terms was drawn based on their relationship in MeSH. Based on the studies done by the researchers, the tree diagram of the encyclopedia was drawn with respect to the existing areas in this field, and the terms gathered were put in related domains. In MeSH, 75 preferred terms together with 249 supplementary ones were indexed. One of the informatics' sub-branches is biomedical informatics and health which itself consists of three sub-divisions of bioinformatics, clinical informatics, and health informatics. Medical informatics which is a subdivision of clinical informatics has developed from the three fields of medical sciences, management and social sciences, and computational sciences and mathematics. Medical Informatics is created of confluence and fusion and applications of the three major scientific branches include health and biological sciences, social sciences and management sciences, computing and mathematical sciences, and according to that the structure of MeSH is weak for future development of Encyclopedia of Medical Informatics.

PoPLAR: Portal for Petascale Lifescience Applications and Research

PubMed Central

2013-01-01

Background We are focusing specifically on fast data analysis and retrieval in bioinformatics that will have a direct impact on the quality of human health and the environment. The exponential growth of data generated in biology research, from small atoms to big ecosystems, necessitates an increasingly large computational component to perform analyses. Novel DNA sequencing technologies and complementary high-throughput approaches--such as proteomics, genomics, metabolomics, and meta-genomics--drive data-intensive bioinformatics. While individual research centers or universities could once provide for these applications, this is no longer the case. Today, only specialized national centers can deliver the level of computing resources required to meet the challenges posed by rapid data growth and the resulting computational demand. Consequently, we are developing massively parallel applications to analyze the growing flood of biological data and contribute to the rapid discovery of novel knowledge. Methods The efforts of previous National Science Foundation (NSF) projects provided for the generation of parallel modules for widely used bioinformatics applications on the Kraken supercomputer. We have profiled and optimized the code of some of the scientific community's most widely used desktop and small-cluster-based applications, including BLAST from the National Center for Biotechnology Information (NCBI), HMMER, and MUSCLE; scaled them to tens of thousands of cores on high-performance computing (HPC) architectures; made them robust and portable to next-generation architectures; and incorporated these parallel applications in science gateways with a web-based portal. Results This paper will discuss the various developmental stages, challenges, and solutions involved in taking bioinformatics applications from the desktop to petascale with a front-end portal for very-large-scale data analysis in the life sciences. Conclusions This research will help to bridge the gap between the rate of data generation and the speed at which scientists can study this data. The ability to rapidly analyze data at such a large scale is having a significant, direct impact on science achieved by collaborators who are currently using these tools on supercomputers. PMID:23902523

The markup is the model: reasoning about systems biology models in the Semantic Web era.

PubMed

Kell, Douglas B; Mendes, Pedro

2008-06-07

Metabolic control analysis, co-invented by Reinhart Heinrich, is a formalism for the analysis of biochemical networks, and is a highly important intellectual forerunner of modern systems biology. Exchanging ideas and exchanging models are part of the international activities of science and scientists, and the Systems Biology Markup Language (SBML) allows one to perform the latter with great facility. Encoding such models in SBML allows their distributed analysis using loosely coupled workflows, and with the advent of the Internet the various software modules that one might use to analyze biochemical models can reside on entirely different computers and even on different continents. Optimization is at the core of many scientific and biotechnological activities, and Reinhart made many major contributions in this area, stimulating our own activities in the use of the methods of evolutionary computing for optimization.

Laboratory Directed Research and Development FY2010 Annual Report

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

Jackson, K J

2011-03-22

A premier applied-science laboratory, Lawrence Livermore National Laboratory (LLNL) has at its core a primary national security mission - to ensure the safety, security, and reliability of the nation's nuclear weapons stockpile without nuclear testing, and to prevent and counter the spread and use of weapons of mass destruction: nuclear, chemical, and biological. The Laboratory uses the scientific and engineering expertise and facilities developed for its primary mission to pursue advanced technologies to meet other important national security needs - homeland defense, military operations, and missile defense, for example - that evolve in response to emerging threats. For broader nationalmore » needs, LLNL executes programs in energy security, climate change and long-term energy needs, environmental assessment and management, bioscience and technology to improve human health, and for breakthroughs in fundamental science and technology. With this multidisciplinary expertise, the Laboratory serves as a science and technology resource to the U.S. government and as a partner with industry and academia. This annual report discusses the following topics: (1) Advanced Sensors and Instrumentation; (2) Biological Sciences; (3) Chemistry; (4) Earth and Space Sciences; (5) Energy Supply and Use; (6) Engineering and Manufacturing Processes; (7) Materials Science and Technology; Mathematics and Computing Science; (8) Nuclear Science and Engineering; and (9) Physics.« less

Current status and future direction of NASA's Space Life Sciences Program

NASA Technical Reports Server (NTRS)

White, Ronald J.; Lujan, Barbara F.

1989-01-01

The elements of the NASA Life Sciences Program that are related to manned space flight and biological scientific studies in space are reviewed. Projects included in the current program are outlined and the future direction of the program is discussed. Consideration is given to issues such as long-duration spaceflight, medical support in space, readaptation to the gravity field of earth, considerations for the Space Station, radiation hazards, environmental standards for space habitation, and human operator interaction with computers, robots, and telepresence systems.

A Simple but Powerful Heuristic Method for Accelerating k-Means Clustering of Large-Scale Data in Life Science.

PubMed

Ichikawa, Kazuki; Morishita, Shinichi

2014-01-01

K-means clustering has been widely used to gain insight into biological systems from large-scale life science data. To quantify the similarities among biological data sets, Pearson correlation distance and standardized Euclidean distance are used most frequently; however, optimization methods have been largely unexplored. These two distance measurements are equivalent in the sense that they yield the same k-means clustering result for identical sets of k initial centroids. Thus, an efficient algorithm used for one is applicable to the other. Several optimization methods are available for the Euclidean distance and can be used for processing the standardized Euclidean distance; however, they are not customized for this context. We instead approached the problem by studying the properties of the Pearson correlation distance, and we invented a simple but powerful heuristic method for markedly pruning unnecessary computation while retaining the final solution. Tests using real biological data sets with 50-60K vectors of dimensions 10-2001 (~400 MB in size) demonstrated marked reduction in computation time for k = 10-500 in comparison with other state-of-the-art pruning methods such as Elkan's and Hamerly's algorithms. The BoostKCP software is available at http://mlab.cb.k.u-tokyo.ac.jp/~ichikawa/boostKCP/.

Leaks in the pipeline: separating demographic inertia from ongoing gender differences in academia.

PubMed

Shaw, Allison K; Stanton, Daniel E

2012-09-22

Identification of the causes underlying the under-representation of women and minorities in academia is a source of ongoing concern and controversy. This is a critical issue in ensuring the openness and diversity of academia; yet differences in personal experiences and interpretations have mired it in controversy. We construct a simple model of the academic career that can be used to identify general trends, and separate the demographic effects of historical differences from ongoing biological or cultural gender differences. We apply the model to data on academics collected by the National Science Foundation (USA) over the past three decades, across all of science and engineering, and within six disciplines (agricultural and biological sciences, engineering, mathematics and computer sciences, physical sciences, psychology, and social sciences). We show that the hiring and retention of women in academia have been affected by both demographic inertia and gender differences, but that the relative influence of gender differences appears to be dwindling for most disciplines and career transitions. Our model enables us to identify the two key non-structural bottlenecks restricting female participation in academia: choice of undergraduate major and application to faculty positions. These transitions are those in greatest need of detailed study and policy development.

NETTAB 2012 on "Integrated Bio-Search"

PubMed Central

2014-01-01

The NETTAB 2012 workshop, held in Como on November 14-16, 2012, was devoted to "Integrated Bio-Search", that is to technologies, methods, architectures, systems and applications for searching, retrieving, integrating and analyzing data, information, and knowledge with the aim of answering complex bio-medical-molecular questions, i.e. some of the most challenging issues in bioinformatics today. It brought together about 80 researchers working in the field of Bioinformatics, Computational Biology, Biology, Computer Science and Engineering. More than 50 scientific contributions, including keynote and tutorial talks, oral communications, posters and software demonstrations, were presented at the workshop. This preface provides a brief overview of the workshop and shortly introduces the peer-reviewed manuscripts that were accepted for publication in this Supplement. PMID:24564635

An interactive computer lab of the galvanic cell for students in biochemistry.

PubMed

Ahlstrand, Emma; Buetti-Dinh, Antoine; Friedman, Ran

2018-01-01

We describe an interactive module that can be used to teach basic concepts in electrochemistry and thermodynamics to first year natural science students. The module is used together with an experimental laboratory and improves the students' understanding of thermodynamic quantities such as Δ r G, Δ r H, and Δ r S that are calculated but not directly measured in the lab. We also discuss how new technologies can substitute some parts of experimental chemistry courses, and improve accessibility to course material. Cloud computing platforms such as CoCalc facilitate the distribution of computer codes and allow students to access and apply interactive course tools beyond the course's scope. Despite some limitations imposed by cloud computing, the students appreciated the approach and the enhanced opportunities to discuss study questions with their classmates and instructor as facilitated by the interactive tools. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):58-65, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

Computer simulations in the high school: students' cognitive stages, science process skills and academic achievement in microbiology

NASA Astrophysics Data System (ADS)

Huppert, J.; Michal Lomask, S.; Lazarowitz, R.

2002-08-01

Computer-assisted learning, including simulated experiments, has great potential to address the problem solving process which is a complex activity. It requires a highly structured approach in order to understand the use of simulations as an instructional device. This study is based on a computer simulation program, 'The Growth Curve of Microorganisms', which required tenth grade biology students to use problem solving skills whilst simultaneously manipulating three independent variables in one simulated experiment. The aims were to investigate the computer simulation's impact on students' academic achievement and on their mastery of science process skills in relation to their cognitive stages. The results indicate that the concrete and transition operational students in the experimental group achieved significantly higher academic achievement than their counterparts in the control group. The higher the cognitive operational stage, the higher students' achievement was, except in the control group where students in the concrete and transition operational stages did not differ. Girls achieved equally with the boys in the experimental group. Students' academic achievement may indicate the potential impact a computer simulation program can have, enabling students with low reasoning abilities to cope successfully with learning concepts and principles in science which require high cognitive skills.

The OptIPuter microscopy demonstrator: enabling science through a transatlantic lightpath

PubMed Central

Ellisman, M.; Hutton, T.; Kirkland, A.; Lin, A.; Lin, C.; Molina, T.; Peltier, S.; Singh, R.; Tang, K.; Trefethen, A.E.; Wallom, D.C.H.; Xiong, X.

2009-01-01

The OptIPuter microscopy demonstrator project has been designed to enable concurrent and remote usage of world-class electron microscopes located in Oxford and San Diego. The project has constructed a network consisting of microscopes and computational and data resources that are all connected by a dedicated network infrastructure using the UK Lightpath and US Starlight systems. Key science drivers include examples from both materials and biological science. The resulting system is now a permanent link between the Oxford and San Diego microscopy centres. This will form the basis of further projects between the sites and expansion of the types of systems that can be remotely controlled, including optical, as well as electron, microscopy. Other improvements will include the updating of the Microsoft cluster software to the high performance computing (HPC) server 2008, which includes the HPC basic profile implementation that will enable the development of interoperable clients. PMID:19487201

The OptIPuter microscopy demonstrator: enabling science through a transatlantic lightpath.

PubMed

Ellisman, M; Hutton, T; Kirkland, A; Lin, A; Lin, C; Molina, T; Peltier, S; Singh, R; Tang, K; Trefethen, A E; Wallom, D C H; Xiong, X

2009-07-13

The OptIPuter microscopy demonstrator project has been designed to enable concurrent and remote usage of world-class electron microscopes located in Oxford and San Diego. The project has constructed a network consisting of microscopes and computational and data resources that are all connected by a dedicated network infrastructure using the UK Lightpath and US Starlight systems. Key science drivers include examples from both materials and biological science. The resulting system is now a permanent link between the Oxford and San Diego microscopy centres. This will form the basis of further projects between the sites and expansion of the types of systems that can be remotely controlled, including optical, as well as electron, microscopy. Other improvements will include the updating of the Microsoft cluster software to the high performance computing (HPC) server 2008, which includes the HPC basic profile implementation that will enable the development of interoperable clients.

Methods and successes of New York University workshops for science graduate students and post-docs in science writing for general audiences (readers and radio listeners)

NASA Astrophysics Data System (ADS)

Hall, S. S.

2012-12-01

Scientists and science administrators often stress the importance of communication to the general public, but rarely develop educational infrastructures to achieve this goal. Since 2009, the Arthur L. Carter Journalism Institute at New York University has offered a series of basic and advanced writing workshops for graduate students and post-docs in NYU's eight scientific divisions (neuroscience, psychology, physics, biology, chemistry, mathematics, anthropology, and computer science). The basic methodology of the NYU approach will be described, along with successful examples of both written and radio work by students that have been either published or broadcast by general interest journalism outlets.

Mapping the Materials Genome through Combinatorial Informatics

NASA Astrophysics Data System (ADS)

Rajan, Krishna

2012-02-01

The recently announced White House Materials Genome Initiative provides an exciting challenge to the materials science community. To meet that challenge one needs to address a critical question, namely what is the materials genome? Some guide on how to the answer this question can be gained by recognizing that a ``gene'' is a carrier of information. In the biological sciences, discovering how to manipulate these genes has generated exciting discoveries in fundamental molecular biology as well as significant advances in biotechnology. Scaling that up to molecular, cellular length scales and beyond, has spawned from genomics, fields such as proteomics, metabolomics and essentially systems biology. The ``omics'' approach requires that one needs to discover and track these ``carriers of information'' and then correlate that information to predict behavior. A similar challenge lies in materials science, where there is a diverse array of modalities of materials ``discovery'' ranging from new materials chemistries and molecular arrangements with novel properties, to the development and design of new micro- and mesoscale structures. Hence to meaningfully adapt the spirit of ``genomics'' style research in materials science, we need to first identify and map the ``genes'' across different materials science applications On the experimental side, combinatorial experiments have opened a new approach to generate data in a high throughput manner, but without a clear way to link that to models, the full value of that data is not realized. Hence along with experimental and computational materials science, we need to add a ``third leg'' to our toolkit to make the ``Materials Genome'' a reality, the science of Materials Informatics. In this presentation we provide an overview of how information science coupled to materials science can in fact achieve the goal of mapping the ``Materials Genome''.

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

On the role of the plasmodial cytoskeleton in facilitating intelligent behavior in slime mold Physarum polycephalum

PubMed Central

Mayne, Richard; Adamatzky, Andrew; Jones, Jeff

2015-01-01

The plasmodium of slime mold Physarum polycephalum behaves as an amorphous reaction-diffusion computing substrate and is capable of apparently ‘intelligent’ behavior. But how does intelligence emerge in an acellular organism? Through a range of laboratory experiments, we visualize the plasmodial cytoskeleton—a ubiquitous cellular protein scaffold whose functions are manifold and essential to life—and discuss its putative role as a network for transducing, transmitting and structuring data streams within the plasmodium. Through a range of computer modeling techniques, we demonstrate how emergent behavior, and hence computational intelligence, may occur in cytoskeletal communications networks. Specifically, we model the topology of both the actin and tubulin cytoskeletal networks and discuss how computation may occur therein. Furthermore, we present bespoke cellular automata and particle swarm models for the computational process within the cytoskeleton and observe the incidence of emergent patterns in both. Our work grants unique insight into the origins of natural intelligence; the results presented here are therefore readily transferable to the fields of natural computation, cell biology and biomedical science. We conclude by discussing how our results may alter our biological, computational and philosophical understanding of intelligence and consciousness. PMID:26478782

On the role of the plasmodial cytoskeleton in facilitating intelligent behavior in slime mold Physarum polycephalum.

PubMed

Mayne, Richard; Adamatzky, Andrew; Jones, Jeff

2015-01-01

The plasmodium of slime mold Physarum polycephalum behaves as an amorphous reaction-diffusion computing substrate and is capable of apparently 'intelligent' behavior. But how does intelligence emerge in an acellular organism? Through a range of laboratory experiments, we visualize the plasmodial cytoskeleton-a ubiquitous cellular protein scaffold whose functions are manifold and essential to life-and discuss its putative role as a network for transducing, transmitting and structuring data streams within the plasmodium. Through a range of computer modeling techniques, we demonstrate how emergent behavior, and hence computational intelligence, may occur in cytoskeletal communications networks. Specifically, we model the topology of both the actin and tubulin cytoskeletal networks and discuss how computation may occur therein. Furthermore, we present bespoke cellular automata and particle swarm models for the computational process within the cytoskeleton and observe the incidence of emergent patterns in both. Our work grants unique insight into the origins of natural intelligence; the results presented here are therefore readily transferable to the fields of natural computation, cell biology and biomedical science. We conclude by discussing how our results may alter our biological, computational and philosophical understanding of intelligence and consciousness.

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.

Governance strategies for living technologies: bridging the gap between stimulating and regulating technoscience.

PubMed

van Est, Rinie; Stemerding, Dirk

2013-01-01

The life sciences present a politically and ethically sensitive area of technology development. NBIC convergence-the convergence of nanotechnology, biotechnology, and information and cognitive technology-presents an increased interaction between the biological and physical sciences. As a result the bio-debate is no longer dominated by biotechnology, but driven by NBIC convergence. NBIC convergence enables two bioengineering megatrends: "biology becoming technology" and "technology becoming biology." The notion of living technologies captures the latter megatrend. Accordingly, living technology presents a politically and ethically sensitive area. This implies that governments sooner or later are faced with the challenge of both promoting and regulating the development of living technology. This article describes four current political models to deal with innovation promotion and risk regulation. Based on two specific developments in the field of living technologies-(psycho)physiological computing and synthetic biology-we reflect on appropriate governance strategies for living technologies. We conclude that recent pleas for anticipatory and deliberative governance tend to neglect the need for anticipatory regulation as a key factor in guiding the development of the life sciences from a societal perspective. In particular, when it is expected that a certain living technology will radically challenge current regulatory systems, one should opt for just such a more active biopolitical approach.

BioMEMS and Lab-on-a-Chip Course Education at West Virginia University

PubMed Central

Liu, Yuxin

2011-01-01

With the rapid growth of Biological/Biomedical MicroElectroMechanical Systems (BioMEMS) and microfluidic-based lab-on-a-chip (LOC) technology to biological and biomedical research and applications, demands for educated and trained researchers and technicians in these fields are rapidly expanding. Universities are expected to develop educational plans to address these specialized needs in BioMEMS, microfluidic and LOC science and technology. A course entitled BioMEMS and Lab-on-a-Chip was taught recently at the senior undergraduate and graduate levels in the Department of Computer Science and Electrical Engineering at West Virginia University (WVU). The course focused on the basic principles and applications of BioMEMS and LOC technology to the areas of biomedicine, biology, and biotechnology. The course was well received and the enrolled students had diverse backgrounds in electrical engineering, material science, biology, mechanical engineering, and chemistry. Student feedback and a review of the course evaluations indicated that the course was effective in achieving its objectives. Student presentations at the end of the course were a highlight and a valuable experience for all involved. The course proved successful and will continue to be offered regularly. This paper provides an overview of the course as well as some development and future improvements. PMID:25586697

Computational protein design: a review

NASA Astrophysics Data System (ADS)

Coluzza, Ivan

2017-04-01

Proteins are one of the most versatile modular assembling systems in nature. Experimentally, more than 110 000 protein structures have been identified and more are deposited every day in the Protein Data Bank. Such an enormous structural variety is to a first approximation controlled by the sequence of amino acids along the peptide chain of each protein. Understanding how the structural and functional properties of the target can be encoded in this sequence is the main objective of protein design. Unfortunately, rational protein design remains one of the major challenges across the disciplines of biology, physics and chemistry. The implications of solving this problem are enormous and branch into materials science, drug design, evolution and even cryptography. For instance, in the field of drug design an effective computational method to design protein-based ligands for biological targets such as viruses, bacteria or tumour cells, could give a significant boost to the development of new therapies with reduced side effects. In materials science, self-assembly is a highly desired property and soon artificial proteins could represent a new class of designable self-assembling materials. The scope of this review is to describe the state of the art in computational protein design methods and give the reader an outline of what developments could be expected in the near future.

Structural Biology of Tumor Necrosis Factor Demonstrated for Undergraduates Instruction by Computer Simulation

ERIC Educational Resources Information Center

Roy, Urmi

2016-01-01

This work presents a three-dimensional (3D) modeling exercise for undergraduate students in chemistry and health sciences disciplines, focusing on a protein-group linked to immune system regulation. Specifically, the exercise involves molecular modeling and structural analysis of tumor necrosis factor (TNF) proteins, both wild type and mutant. The…

An overview of the biocreative 2012 workshop track III: Interactive text mining task

USDA-ARS?s Scientific Manuscript database

An important question is how to make use of text mining to enhance the biocuration workflow. A number of groups have developed tools for text mining from a computer science/linguistics perspective and there are many initiatives to curate some aspect of biology from the literature. In some cases the ...

Characteristics of Open Access Journals in Six Subject Areas

ERIC Educational Resources Information Center

Walters, William H.; Linvill, Anne C.

2011-01-01

We examine the characteristics of 663 Open Access (OA) journals in biology, computer science, economics, history, medicine, and psychology, then compare the OA journals with impact factors to comparable subscription journals. There is great variation in the size of OA journals; the largest publishes more than 2,700 articles per year, but half…

Statistical Physics in the Era of Big Data

ERIC Educational Resources Information Center

Wang, Dashun

2013-01-01

With the wealth of data provided by a wide range of high-throughout measurement tools and technologies, statistical physics of complex systems is entering a new phase, impacting in a meaningful fashion a wide range of fields, from cell biology to computer science to economics. In this dissertation, by applying tools and techniques developed in…

A Biologically Informed Framework for the Analysis of the PPAR Signaling Pathway using a Bayesian Network

EPA Science Inventory

The US EPA’s ToxCastTM program seeks to combine advances in high-throughput screening technology with methodologies from statistics and computer science to develop high-throughput decision support tools for assessing chemical hazard and risk. To develop new methods of analysis of...

Biological Production in Lakes. Physical Processes in Terrestrial and Aquatic Ecosystems, Ecological Processes.

ERIC Educational Resources Information Center

Walters, R. A.; Carey, G. F.

These materials were designed to be used by life science students for instruction in the application of physical theory to ecosystem operation. Most modules contain computer programs which are built around a particular application of a physical process. Primary production in aquatic ecosystems is carried out by phytoplankton, microscopic plants…

Analysis and logical modeling of biological signaling transduction networks

NASA Astrophysics Data System (ADS)

Sun, Zhongyao

The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

The Computational Science Education Reference Desk: A tool for increasing inquiry based learning in the science classroom

NASA Astrophysics Data System (ADS)

Joiner, D. A.; Stevenson, D. E.; Panoff, R. M.

2000-12-01

The Computational Science Reference Desk is an online tool designed to provide educators in math, physics, astronomy, biology, chemistry, and engineering with information on how to use computational science to enhance inquiry based learning in the undergraduate and pre college classroom. The Reference Desk features a showcase of original content exploration activities, including lesson plans and background materials; a catalog of websites which contain models, lesson plans, software, and instructional resources; and a forum to allow educators to communicate their ideas. Many of the recent advances in astronomy rely on the use of computer simulation, and tools are being developed by CSERD to allow students to experiment with some of the models that have guided scientific discovery. One of these models allows students to study how scientists use spectral information to determine the makeup of the interstellar medium by modeling the interstellar extinction curve using spherical grains of silicate, amorphous carbon, or graphite. Students can directly compare their model to the average interstellar extinction curve, and experiment with how small changes in their model alter the shape of the interstellar extinction curve. A simpler model allows students to visualize spatial relationships between the Earth, Moon, and Sun to understand the cause of the phases of the moon. A report on the usefulness of these models in two classes, the Computational Astrophysics workshop at The Shodor Education Foundation and the Conceptual Astronomy class at the University of North Carolina at Greensboro, will be presented.

Earth System Grid II, Turning Climate Datasets into Community Resources

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

Middleton, Don

2006-08-01

The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects,more » we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.« less

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

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

Teeguarden, Justin G.; Tan, Yu-Mei; Edwards, Stephen W.

Driven by major scientific advances in analytical methods, biomonitoring, and computational exposure assessment, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the computationally enabled “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) conceptmore » in the toxicological sciences. The AEP framework offers an intuitive approach to successful organization of exposure science data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathway and adverse outcome pathways, completing the source to outcome continuum and setting the stage for more efficient integration of exposure science and toxicity testing information. Together these frameworks form and inform a decision making framework with the flexibility for risk-based, hazard-based or exposure-based decisions.« less

SigWin-detector: a Grid-enabled workflow for discovering enriched windows of genomic features related to DNA sequences.

PubMed

Inda, Márcia A; van Batenburg, Marinus F; Roos, Marco; Belloum, Adam S Z; Vasunin, Dmitry; Wibisono, Adianto; van Kampen, Antoine H C; Breit, Timo M

2008-08-08

Chromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential. Here we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic) features in a (DNA) sequence in a fast and reproducible way. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs) in human transcriptome maps. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment. As we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. Thus, SigWin-detector provides the proof-of-principle for the modular e-Science based concept of integrative bioinformatics experimentation.

Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

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

Soundarajan, Sucheta; Wendt, Jeremy D.

2016-06-01

While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to bemore » found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.« less

Synchronization in complex networks

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

Arenas, A.; Diaz-Guilera, A.; Moreno, Y.

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analyticalmore » approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.« less

Looking back: forward looking.

PubMed

Edmunds, Scott C; Nogoy, Nicole A; Zauner, Hans; Li, Peter; Hunter, Christopher I; Zhe, Xiao Si; Goodman, Laurie

2017-09-01

GigaScience is now 5 years old, having been launched at the 2012 Intelligent Systems for Molecular Biology conference. Anyone who has attended what is the largest computational biology conference since then has had the opportunity to join us for each birthday celebration-and receive 1 of our fun T-shirts as a party prize. Since launching, we have pushed our agenda of openness, transparency, reproducibility, and reusability. Here, we look back at our first 5 years and what we have done to forward our open science goals in scientific publishing. Our mainstay has been to create a process that allows the availability and publication of as many "research objects" as possible to create a more complete way of communicating how the research process is done. © The Authors 2017. Published by Oxford University Press.

Quantitative and Qualitative Evaluation of The Structural Designing of Medical Informatics Dynamic Encyclopedia

PubMed Central

Safdari, Reza; Shahmoradi, Leila; Hosseini-beheshti, Molouk-sadat; Nejad, Ahmadreza Farzaneh; Hosseiniravandi, Mohammad

2015-01-01

Introduction: Encyclopedias and their compilation have become so prevalent as a valid cultural medium in the world. The daily development of computer industry and the expansion of various sciences have made indispensable the compilation of electronic, specialized encyclopedias, especially the web-based ones. Materials and Methods: This is an applied-developmental study conducted in 2014. First, the main terms in the field of medical informatics were gathered using MeSH Online 2014 and the supplementary terms of each were determined, and then the tree diagram of the terms was drawn based on their relationship in MeSH. Based on the studies done by the researchers, the tree diagram of the encyclopedia was drawn with respect to the existing areas in this field, and the terms gathered were put in related domains. Findings: In MeSH, 75 preferred terms together with 249 supplementary ones were indexed. One of the informatics’ sub-branches is biomedical informatics and health which itself consists of three sub-divisions of bioinformatics, clinical informatics, and health informatics. Medical informatics which is a subdivision of clinical informatics has developed from the three fields of medical sciences, management and social sciences, and computational sciences and mathematics. Results and Discussion: Medical Informatics is created of confluence and fusion and applications of the three major scientific branches include health and biological sciences, social sciences and management sciences, computing and mathematical sciences, and according to that the structure of MeSH is weak for future development of Encyclopedia of Medical Informatics. PMID:26635440

Artificial neural networks in biology and chemistry: the evolution of a new analytical tool.

PubMed

Cartwright, Hugh M

2008-01-01

Once regarded as an eccentric and unpromising algorithm for the analysis of scientific data, the neural network has been developed in the last decade into a powerful computational tool. Its use now spans all areas of science, from the physical sciences and engineering to the life sciences and allied subjects. Applications range from the assessment of epidemiological data or the deconvolution of spectra to highly practical applications, such as the electronic nose. This introductory chapter considers briefly the growth in the use of neural networks and provides some general background in preparation for the more detailed chapters that follow.

Behavioural science at work for Canada: National Research Council laboratories.

PubMed

Veitch, Jennifer A

2007-03-01

The National Research Council is Canada's principal research and development agency. Its 20 institutes are structured to address interdisciplinary problems for industrial sectors, and to provide the necessary scientific infrastructure, such as the national science library. Behavioural scientists are active in five institutes: Biological Sciences, Biodiagnostics, Aerospace, Information Technology, and Construction. Research topics include basic cellular neuroscience, brain function, human factors in the cockpit, human-computer interaction, emergency evacuation, and indoor environment effects on occupants. Working in collaboration with NRC colleagues and with researchers from universities and industry, NRC behavioural scientists develop knowledge, designs, and applications that put technology to work for people, designed with people in mind.

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.

''After the Genome 5 Conference'' to be held October 6-10, 1999 in Jackson Hole, Wyoming

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

Roger Brent

OAK B139 The postgenomic era is arriving faster than anyone had imagined--sometime during 2000 we'll have a large fraction of the human genome sequence. Heretofore, our understanding of function has come from non-industrial experiments whose conclusions were largely framed in human language. The advent of large amounts of sequence data, and of ''functional genomic'' data types such as mRNA expression data, have changed this picture. These data share the feature that individual observations and measurements are typically relatively low value adding. Such data is now being generated so rapidly that the amount of information contained in it will surpass themore » amount of biological information collected by traditional means. It is tantalizing to envision using genomic information to create a quantitative biology with a very strong data component. Unfortunately, we are very early in our understanding of how to ''compute on'' genomic information so as to extract biological knowledge from i t. In fact, some current efforts to come to grips with genomic information often resemble a computer savvy library science, where the most important issues concern categories, classification schemes, and information retrieval. When exploring new libraries, a measure of cataloging and inventory is surely inevitable. However, at some point we will need to move from library science to scholarship.We would like to achieve a quantitative and predictive understanding of biological function. We realize that making the bridge from knowledge of systems to the sets of abstractions that constitute computable entities is not easy. The After the Genome meetings were started in 1995 to help the biological community think about and prepare for the changes in biological research in the face of the oncoming flow of genomic information. The term ''After the Genome'' refers to a future in which complete inventories of the gene products of entire organisms become available.Since then, many more biologists have become cognizant of the issues raised by this future, and, in response, the organizers intend to distinguish this meeting from other ''postgenomic'' meetings by bringing together intellectuals from subject fields far outside of conventional biology with the expectation that this will help focus thinking beyond the immediate future. To this end, After the Genome 5 will bring together industrial and university researchers, including: (1) Physicists, chemists, and engineers who are devising and using new data gathering techniques, such as microarrays, protein mass spectrometry, and single molecule measurements (2) Computer scientists from fields as diverse as geology and wargames, who have experience moving from broad knowledge of systems to analysis that results in models and simulations (3) Neurobiologists and computer scientists who combine physiological experimentation and computer modeling to understand single cells and small networks of cells (4) Biologists who are trying to model genetic networks (5) All-around visionary thinkers (6) policy makers, to suggest how to convey any good ideas to organizations that can commit resources to them.« less

"After the Genome 5, Conference to be held October 6-10, 1999, Jackson Hole, Wyoming"

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

Brent, Roger

The postgenomic era is arriving faster than anyone had imagined-- sometime during 2000 we'll have a large fraction of the human genome sequence. Heretofore, our understanding of function has come from non-industrial experiments whose conclusions were largely framed in human language. The advent of large amounts of sequence data, and of "functional genomic" data types such as mRNA expression data, have changed this picture. These data share the feature that individual observations and measurements are typically relatively low value adding. Such data is now being generated so rapidly that the amount of information contained in it will surpass the amountmore » of biological information collected by traditional means. It is tantalizing to envision using genomic information to create a quantitative biology with a very strong data component. Unfortunately, we are very early in our understanding of how to "compute on" genomic information so as to extract biological knowledge from it. In fact, some current efforts to come to grips with genomic information often resemble a computer savvy library science, where the most important issues concern categories, classification schemes, and information retrieval. When exploring new libraries, a measure of cataloging and inventory is surely inevitable. However, at some point we will need to move from library science to scholarship. We would like to achieve a quantitative and predictive understanding of biological function. We realize that making the bridge from knowledge of systems to the sets of abstractions that constitute computable entities is not easy. The After the Genome meetings were started in 1995 to help the biological community think about and prepare for the changes in biological research in the face of the oncoming flow of genomic information. The term "After the Genome" refers to a future in which complete inventories of the gene products of entire organisms become available. Since then, many more biologists have become cognizant of the issues raised by this future, and, in response, the organizers intend to distinguish this meeting from other "postgenomic" meetings by bringing together intellectuals from subject fields far outside of conventional biology with the expectation that this will help focus thinking beyond the immediate future. To this end, After the Genome 5 will bring together industrial and university researchers, including: 1) Physicists, chemists, and engineers who are devising and using new data gathering techniques, such as microarrays, protein mass spectrometry, and single molecule measurements 2) Computer scientists from fields as diverse as geology and wargames, who have experience moving from broad knowledge of systems to analysis that results in models and simulations 3) Neurobiologists and computer scientists who combine physiological experimentation and computer modeling to understand single cells and small networks of cells 4) Biologists who are trying to model genetic networks 5) All- around visionary thinkers 7) policy makers, to suggest how to convey any good ideas to organizations that can commit resources to them.« less

Unraveling the Complexities of Life Sciences Data.

PubMed

Higdon, Roger; Haynes, Winston; Stanberry, Larissa; Stewart, Elizabeth; Yandl, Gregory; Howard, Chris; Broomall, William; Kolker, Natali; Kolker, Eugene

2013-03-01

The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (Data-Enabled Life Sciences Alliance, DELSAglobal.org), the Kolker Lab ( kolkerlab.org ) is creating partnerships that identify data challenges and solve community needs. We specialize in solutions to complex biological data challenges, as exemplified by the community resource of MOPED (Model Organism Protein Expression Database, MOPED.proteinspire.org ) and the analysis pipeline of SPIRE (Systematic Protein Investigative Research Environment, PROTEINSPIRE.org ). Our collaborative work extends into the computationally intensive tasks of analysis and visualization of millions of protein sequences through innovative implementations of sequence alignment algorithms and creation of the Protein Sequence Universe tool (PSU). Pushing into the future together with our collaborators, our lab is pursuing integration of multi-omics data and exploration of biological pathways, as well as assigning function to proteins and porting solutions to the cloud. Big data have come to the life sciences; discovering the knowledge in the data will bring breakthroughs and benefits.

The Human Genome Project: big science transforms biology and medicine

PubMed Central

2013-01-01

The Human Genome Project has transformed biology through its integrated big science approach to deciphering a reference human genome sequence along with the complete sequences of key model organisms. The project exemplifies the power, necessity and success of large, integrated, cross-disciplinary efforts - so-called ‘big science’ - directed towards complex major objectives. In this article, we discuss the ways in which this ambitious endeavor led to the development of novel technologies and analytical tools, and how it brought the expertise of engineers, computer scientists and mathematicians together with biologists. It established an open approach to data sharing and open-source software, thereby making the data resulting from the project accessible to all. The genome sequences of microbes, plants and animals have revolutionized many fields of science, including microbiology, virology, infectious disease and plant biology. Moreover, deeper knowledge of human sequence variation has begun to alter the practice of medicine. The Human Genome Project has inspired subsequent large-scale data acquisition initiatives such as the International HapMap Project, 1000 Genomes, and The Cancer Genome Atlas, as well as the recently announced Human Brain Project and the emerging Human Proteome Project. PMID:24040834

Biocatalysis and biomimetics

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

Burrington, J.D.; Clark, D.S.

1989-01-01

This book presents recent advances in catalytic science and biotechnology. The chapters illustrate how many of the key challenges in biotechnology can be addressed by bringing together traditionally separate disciplines within chemistry and biology. The authors focus on emerging enabling technologies at the interfaces of catalysis and biology that will provide new opportunities for the chemicals industries. Key aspects to be presented within this major theme of catalysis and biotechnology are biomimetics and hybrid catalysts, biocatalytic applications of computers and expert systems, enzyme solid-state structure and immobilization, enzyme structure-activity relationships, and the use of enzymes under novel conditions.

Bioinspired principles for large-scale networked sensor systems: an overview.

PubMed

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy.

Remodeling a tissue: subtraction adds insight.

PubMed

Axelrod, Jeffrey D

2012-11-27

Sculpting a body plan requires both patterning of gene expression and translating that pattern into morphogenesis. Developmental biologists have made remarkable strides in understanding gene expression patterning, but despite a long history of fascination with the mechanics of morphogenesis, knowledge of how patterned gene expression drives the emergence of even simple shapes and forms has grown at a slower pace. The successful merging of approaches from cell biology, developmental biology, imaging, engineering, and mathematical and computational sciences is now accelerating progress toward a fuller and better integrated understanding of the forces shaping morphogenesis.

Physics through the 1990s: Scientific interfaces and technological applications

NASA Technical Reports Server (NTRS)

1986-01-01

The volume examines the scientific interfaces and technological applications of physics. Twelve areas are dealt with: biological physics-biophysics, the brain, and theoretical biology; the physics-chemistry interface-instrumentation, surfaces, neutron and synchrotron radiation, polymers, organic electronic materials; materials science; geophysics-tectonics, the atmosphere and oceans, planets, drilling and seismic exploration, and remote sensing; computational physics-complex systems and applications in basic research; mathematics-field theory and chaos; microelectronics-integrated circuits, miniaturization, future trends; optical information technologies-fiber optics and photonics; instrumentation; physics applications to energy needs and the environment; national security-devices, weapons, and arms control; medical physics-radiology, ultrasonics, MNR, and photonics. An executive summary and many chapters contain recommendations regarding funding, education, industry participation, small-group university research and large facility programs, government agency programs, and computer database needs.

Single-molecule protein sequencing through fingerprinting: computational assessment

NASA Astrophysics Data System (ADS)

Yao, Yao; Docter, Margreet; van Ginkel, Jetty; de Ridder, Dick; Joo, Chirlmin

2015-10-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.

Credit by Examination at the University of Texas at Austin, 1985-1986.

ERIC Educational Resources Information Center

Mahoney, Susan S.

The University of Texas (UT) at Austin's credit by examination program is described. In 1985-86, credit by examination was offered in 55 subjects. Details were provided for each of 18 subject areas in which over 20 tests were administered: Biology; Chemistry; Chinese; Computer Science; Economics; Electrical Engineering; English; French; German;…

What Are They Thinking? Automated Analysis of Student Writing about Acid-Base Chemistry in Introductory Biology

ERIC Educational Resources Information Center

Haudek, Kevin C.; Prevost, Luanna B.; Moscarella, Rosa A.; Merrill, John; Urban-Lurain, Mark

2012-01-01

Students' writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an…

A Computer Lab Exploring Evolutionary Aspects of Chromatin Structure and Dynamics for an Undergraduate Chromatin Course

ERIC Educational Resources Information Center

Eirin-Lopez, Jose M.

2013-01-01

The study of chromatin constitutes one of the most active research fields in life sciences, being subject to constant revisions that continuously redefine the state of the art in its knowledge. As every other rapidly changing field, chromatin biology requires clear and straightforward educational strategies able to efficiently translate such a…

Using the Bifocal Modeling Framework to Resolve "Discrepant Events" between Physical Experiments and Virtual Models in Biology

ERIC Educational Resources Information Center

Blikstein, Paulo; Fuhrmann, Tamar; Salehi, Shima

2016-01-01

In this paper, we investigate an approach to supporting students' learning in science through a combination of physical experimentation and virtual modeling. We present a study that utilizes a scientific inquiry framework, which we call "bifocal modeling," to link student-designed experiments and computer models in real time. In this…

Identification of Students' Content Mastery and Cognitive and Affective Percepts of a Bioinformatics Miniunit: A Case Study with Recommendations for Teacher Education

ERIC Educational Resources Information Center

Wefer, Stephen H.; Anderson, O. Roger

2008-01-01

Bioinformatics, merging biological data with computer science, is increasingly incorporated into school curricula at all levels. This case study of 10 secondary school students highlights student individual differences (especially the way they processed information and integrated procedural and analytical thought) and summarizes a variety of…

Thermodynamics of Irreversible Processes. Physical Processes in Terrestrial and Aquatic Ecosystems, Transport Processes.

ERIC Educational Resources Information Center

Levin, Michael; Gallucci, V. F.

These materials were designed to be used by life science students for instruction in the application of physical theory to ecosystem operation. Most modules contain computer programs which are built around a particular application of a physical process. This module describes the application of irreversible thermodynamics to biology. It begins with…

Blinn College Final Grade Distribution Report for Spring 1994 Semester. Student Performance Report. International Research Document No. 012E.

ERIC Educational Resources Information Center

Blinn Coll., Brenham, TX.

Blinn College final course grade distributions are summarized for spring 1990 to 1994 in this four-part report. Section I presents tables of final grade distributions by campus and course in accounting; agriculture; anthropology; biology; business; chemistry; child development; communications; computer science; criminal justice; drama; emergency…

High-throughput Crystallography for Structural Genomics

PubMed Central

Joachimiak, Andrzej

2009-01-01

Protein X-ray crystallography recently celebrated its 50th anniversary. The structures of myoglobin and hemoglobin determined by Kendrew and Perutz provided the first glimpses into the complex protein architecture and chemistry. Since then, the field of structural molecular biology has experienced extraordinary progress and now over 53,000 proteins structures have been deposited into the Protein Data Bank. In the past decade many advances in macromolecular crystallography have been driven by world-wide structural genomics efforts. This was made possible because of third-generation synchrotron sources, structure phasing approaches using anomalous signal and cryo-crystallography. Complementary progress in molecular biology, proteomics, hardware and software for crystallographic data collection, structure determination and refinement, computer science, databases, robotics and automation improved and accelerated many processes. These advancements provide the robust foundation for structural molecular biology and assure strong contribution to science in the future. In this report we focus mainly on reviewing structural genomics high-throughput X-ray crystallography technologies and their impact. PMID:19765976

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets

PubMed Central

McKinney, Bill; Meyer, Peter A.; Crosas, Mercè; Sliz, Piotr

2016-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension—functionality supporting preservation of filesystem structure within Dataverse—which is essential for both in-place computation and supporting non-http data transfers. PMID:27862010

Toward integration of in vivo molecular computing devices: successes and challenges

PubMed Central

Hayat, Sikander; Hinze, Thomas

2008-01-01

The computing power unleashed by biomolecule based massively parallel computational units has been the focus of many interdisciplinary studies that couple state of the art ideas from mathematical logic, theoretical computer science, bioengineering, and nanotechnology to fulfill some computational task. The output can influence, for instance, release of a drug at a specific target, gene expression, cell population, or be a purely mathematical entity. Analysis of the results of several studies has led to the emergence of a general set of rules concerning the implementation and optimization of in vivo computational units. Taking two recent studies on in vivo computing as examples, we discuss the impact of mathematical modeling and simulation in the field of synthetic biology and on in vivo computing. The impact of the emergence of gene regulatory networks and the potential of proteins acting as “circuit wires” on the problem of interconnecting molecular computing device subunits is also highlighted. PMID:19404433

Leaks in the pipeline: separating demographic inertia from ongoing gender differences in academia

PubMed Central

Shaw, Allison K.; Stanton, Daniel E.

2012-01-01

Identification of the causes underlying the under-representation of women and minorities in academia is a source of ongoing concern and controversy. This is a critical issue in ensuring the openness and diversity of academia; yet differences in personal experiences and interpretations have mired it in controversy. We construct a simple model of the academic career that can be used to identify general trends, and separate the demographic effects of historical differences from ongoing biological or cultural gender differences. We apply the model to data on academics collected by the National Science Foundation (USA) over the past three decades, across all of science and engineering, and within six disciplines (agricultural and biological sciences, engineering, mathematics and computer sciences, physical sciences, psychology, and social sciences). We show that the hiring and retention of women in academia have been affected by both demographic inertia and gender differences, but that the relative influence of gender differences appears to be dwindling for most disciplines and career transitions. Our model enables us to identify the two key non-structural bottlenecks restricting female participation in academia: choice of undergraduate major and application to faculty positions. These transitions are those in greatest need of detailed study and policy development. PMID:22719028

Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

PubMed Central

Kearse, Matthew; Moir, Richard; Wilson, Amy; Stones-Havas, Steven; Cheung, Matthew; Sturrock, Shane; Buxton, Simon; Cooper, Alex; Markowitz, Sidney; Duran, Chris; Thierer, Tobias; Ashton, Bruce; Meintjes, Peter; Drummond, Alexei

2012-01-01

Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com PMID:22543367

Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data.

PubMed

Kearse, Matthew; Moir, Richard; Wilson, Amy; Stones-Havas, Steven; Cheung, Matthew; Sturrock, Shane; Buxton, Simon; Cooper, Alex; Markowitz, Sidney; Duran, Chris; Thierer, Tobias; Ashton, Bruce; Meintjes, Peter; Drummond, Alexei

2012-06-15

The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl.

PREFACE: Nanobiology: from physics and engineering to biology

NASA Astrophysics Data System (ADS)

Nussinov, Ruth; Alemán, Carlos

2006-03-01

Biological systems are inherently nano in scale. Unlike nanotechnology, nanobiology is characterized by the interplay between physics, materials science, synthetic organic chemistry, engineering and biology. Nanobiology is a new discipline, with the potential of revolutionizing medicine: it combines the tools, ideas and materials of nanoscience and biology; it addresses biological problems that can be studied and solved by nanotechnology; it devises ways to construct molecular devices using biomacromolecules; and it attempts to build molecular machines utilizing concepts seen in nature. Its ultimate aim is to be able to predictably manipulate these, tailoring them to specified needs. Nanobiology targets biological systems and uses biomacromolecules. Hence, on the one hand, nanobiology is seemingly constrained in its scope as compared to general nanotechnology. Yet the amazing intricacy of biological systems, their complexity, and the richness of the shapes and properties provided by the biological polymers, enrich nanobiology. Targeting biological systems entails comprehension of how they work and the ability to use their components in design. From the physical standpoint, ultimately, if we are to understand biology we need to learn how to apply physical principles to figure out how these systems actually work. The goal of nanobiology is to assist in probing these systems at the appropriate length scale, heralding a new era in the biological, physical and chemical sciences. Biology is increasingly asking quantitative questions. Quantitation is essential if we are to understand how the cell works, and the details of its regulation. The physical sciences provide tools and strategies to obtain accurate measurements and simulate the information to allow comprehension of the processes. Nanobiology is at the interface of the physical and the biological sciences. Biology offers to the physical sciences fascinating problems, sophisticated systems and a rich repertoire of shapes and materials. Inspection of the protein structure databank illustrates the breadth of scaffolds, shapes and properties that protein molecules and their building blocks can provide. Via a shape-guided self-assembly strategy, these can be put together toward a specific function. Further, by inserting synthetic non-natural residues at judiciously selected positions, or synthetic peptide linkers, we may selectively rigidify the construct, or obtain a totally new world of shapes and scaffolds. Such broadening of the chemical space may lead to an almost unlimited range of nanosystems and architectures. Merging computation with experiment will accelerate nanodesign. Computational modeling will enhance the application of nanotechnology to key areas such as drug delivery and biomaterial design. Nanobiology is a field where interdisciplinary collaborations are essential and disciplines converge. Discipline convergence should enable the quantitation, leading to a better understanding of the regulatory networks within cells and between cells of an organism. These networks dictate how a cell responds to external stimuli, which in turn activate signaling cascades. It should allow the addressing of a broad range of questions on the structure and function of the cytoskeleton; the nuclear envelope; signal transduction by membrane embedded receptors; the nanomechanical properties of the extracellular matrix; nuclear transport; and voltage induced channel gating. For successful nanostructure design, we need to figure out and be able to control the intermolecular associations. For a stable functional construct, there are two key elements: first, the conformations of the building blocks in the designed structure should follow their natural tendencies; and second, the associations should be favorable. Molecules interact through their surfaces. Thus, favorable associations derive from shape complementarity and contributions of the various physical components. Nanobiology is in its infancy. Yet, biology provides an enormous range of engaging and stimulating problems with many in vivo examples of intricate, complex, fascinating biological systems. Understanding, mimicking and controlling the devices which target these processes and which are constructed from these molecules is a tremendous challenge to the converging disciplines in nanobiology.

Bioinformatics by Example: From Sequence to Target

NASA Astrophysics Data System (ADS)

Kossida, Sophia; Tahri, Nadia; Daizadeh, Iraj

2002-12-01

With the completion of the human genome, and the imminent completion of other large-scale sequencing and structure-determination projects, computer-assisted bioscience is aimed to become the new paradigm for conducting basic and applied research. The presence of these additional bioinformatics tools stirs great anxiety for experimental researchers (as well as for pedagogues), since they are now faced with a wider and deeper knowledge of differing disciplines (biology, chemistry, physics, mathematics, and computer science). This review targets those individuals who are interested in using computational methods in their teaching or research. By analyzing a real-life, pharmaceutical, multicomponent, target-based example the reader will experience this fascinating new discipline.

U.S, Department of Energy's Bioenergy Research Centers An Overview of the Science

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

None

2009-07-01

Alternative fuels from renewable cellulosic biomass--plant stalks, trunks, stems, and leaves--are expected to significantly reduce U.S. dependence on imported oil while enhancing national energy security and decreasing the environmental impacts of energy use. Ethanol and other advanced biofuels from cellulosic biomass are renewable alternatives that could increase domestic production of transportation fuels, revitalize rural economies, and reduce carbon dioxide and pollutant emissions. According to U.S. Secretary of Energy Steven Chu, 'Developing the next generation of biofuels is key to our effort to end our dependence on foreign oil and address the climate crisis while creating millions of new jobs thatmore » can't be outsourced'. In the United States, the Energy Independence and Security Act (EISA) of 2007 is an important driver for the sustainable development of renewable biofuels. As part of EISA, the Renewable Fuel Standard mandates that 36 billion gallons of biofuels are to be produced annually by 2022, of which 16 billion gallons are expected to come from cellulosic feedstocks. Although cellulosic ethanol production has been demonstrated on a pilot level, developing a cost-effective, commercial-scale cellulosic biofuel industry will require transformational science to significantly streamline current production processes. Woodchips, grasses, cornstalks, and other cellulosic biomass are widely abundant but more difficult to break down into sugars than corn grain--the primary source of U.S. ethanol fuel production today. Biological research is key to accelerating the deconstruction of cellulosic biomass into sugars that can be converted to biofuels. The Department of Energy (DOE) Office of Science continues to play a major role in inspiring, supporting, and guiding the biotechnology revolution over the past 25 years. The DOE Genomic Science Program is advancing a new generation of research focused on achieving whole-systems understanding for biology. This program is bringing together scientists in diverse fields to understand the complex biology underlying solutions to DOE missions in energy production, environmental remediation, and climate change science. New interdisciplinary research communities are emerging, as are knowledgebases and scientific and computational resources critical to advancing large-scale, genome-based biology. To focus the most advanced biotechnology-based resources on the biological challenges of biofuel production, DOE established three Bioenergy Research Centers (BRCs) in September 2007. Each center is pursuing the basic research underlying a range of high-risk, high-return biological solutions for bioenergy applications. Advances resulting from the BRCs will provide the knowledge needed to develop new biobased products, methods, and tools that the emerging biofuel industry can use. The scientific rationale for these centers and for other fundamental genomic research critical to the biofuel industry was established at a DOE workshop involving members of the research community (see sidebar, Biofuel Research Plan, below). The DOE BRCs have developed automated, high-throughput analysis pipelines that will accelerate scientific discovery for biology-based biofuel research. The three centers, which were selected through a scientific peer-review process, are based in geographically diverse locations--the Southeast, the Midwest, and the West Coast--with partners across the nation. DOE's Oak Ridge National Laboratory leads the BioEnergy Science Center (BESC) in Tennessee; the University of Wisconsin-Madison leads the Great Lakes Bioenergy Research Center (GLBRC); and DOE's Lawrence Berkeley National Laboratory leads the DOE Joint BioEnergy Institute (JBEI) in California. Each center represents a multidisciplinary partnership with expertise spanning the physical and biological sciences, including genomics, microbial and plant biology, analytical chemistry, computational biology and bioinformatics, and engineering. Institutional partners include DOE national laboratories, universities, private companies, and nonprofit organizations.« less

Modeling Co-evolution of Speech and Biology.

PubMed

de Boer, Bart

2016-04-01

Two computer simulations are investigated that model interaction of cultural evolution of language and biological evolution of adaptations to language. Both are agent-based models in which a population of agents imitates each other using realistic vowels. The agents evolve under selective pressure for good imitation. In one model, the evolution of the vocal tract is modeled; in the other, a cognitive mechanism for perceiving speech accurately is modeled. In both cases, biological adaptations to using and learning speech evolve, even though the system of speech sounds itself changes at a more rapid time scale than biological evolution. However, the fact that the available acoustic space is used maximally (a self-organized result of cultural evolution) is constant, and therefore biological evolution does have a stable target. This work shows that when cultural and biological traits are continuous, their co-evolution may lead to cognitive adaptations that are strong enough to detect empirically. Copyright © 2016 Cognitive Science Society, Inc.

Learning nucleic acids solving by bioinformatics problems.

PubMed

Nunes, Rhewter; Barbosa de Almeida Júnior, Edivaldo; Pessoa Pinto de Menezes, Ivandilson; Malafaia, Guilherme

2015-01-01

The article describes the development of a new approach to teach molecular biology to undergraduate biology students. The 34 students who participated in this research belonged to the first period of the Biological Sciences teaching course of the Instituto Federal Goiano at Urutaí Campus, Brazil. They were registered in Cell Biology in the first semester of 2013. They received four 55 min-long expository/dialogued lectures that covered the content of "structure and functions of nucleic acids". Later the students were invited to attend four meetings (in a computer laboratory) in which some concepts of Bioinformatics were presented and some problems of the Rosalind platform were solved. The observations we report here are very useful as a broad groundwork to development new research. An interesting possibility is research into the effects of bioinformatics interventions that improve molecular biology learning. © 2015 The International Union of Biochemistry and Molecular Biology.

Extracting biomarkers of commitment to cancer development: potential role of vibrational spectroscopy in systems biology.

PubMed

Theophilou, Georgios; Paraskevaidi, Maria; Lima, Kássio M G; Kyrgiou, Maria; Martin-Hirsch, Pierre L; Martin, Francis L

2015-05-01

The complex processes driving cancer have so far impeded the discovery of dichotomous biomarkers associated with its initiation and progression. Reductionist approaches utilizing 'omics' technologies have met some success in identifying molecular alterations associated with carcinogenesis. Systems biology is an emerging science that combines high-throughput investigation techniques to define the dynamic interplay between regulatory biological systems in response to internal and external cues. Vibrational spectroscopy has the potential to play an integral role within systems biology research approaches. It is capable of examining global models of carcinogenesis by scrutinizing chemical bond alterations within molecules. The application of infrared or Raman spectroscopic approaches coupled with computational analysis under the systems biology umbrella can assist the transition of biomarker research from the molecular level to the system level. The comprehensive representation of carcinogenesis as a multilevel biological process will inevitably revolutionize cancer-related healthcare by personalizing risk prediction and prevention.

Conception and development of the Second Life® Embryo Physics Course.

PubMed

Gordon, Richard

2013-06-01

The study of embryos with the tools and mindset of physics, started by Wilhelm His in the 1880s, has resumed after a hiatus of a century. The Embryo Physics Course convenes online allowing interested researchers and students, who are scattered around the world, to gather weekly in one place, the virtual world of Second Life®. It attracts people from a wide variety of disciplines and walks of life: applied mathematics, artificial life, bioengineering, biophysics, cancer biology, cellular automata, civil engineering, computer science, embryology, electrical engineering, evolution, finite element methods, history of biology, human genetics, mathematics, molecular developmental biology, molecular biology, nanotechnology, philosophy of biology, phycology, physics, self-reproducing systems, stem cells, tensegrity structures, theoretical biology, and tissue engineering. Now in its fifth year, the Embryo Physics Course provides a focus for research on the central question of how an embryo builds itself.

Uses of the Drupal CMS Collaborative Framework in the Woods Hole Scientific Community (Invited)

NASA Astrophysics Data System (ADS)

Maffei, A. R.; Chandler, C. L.; Work, T. T.; Shorthouse, D.; Furfey, J.; Miller, H.

2010-12-01

Organizations that comprise the Woods Hole scientific community (Woods Hole Oceanographic Institution, Marine Biological Laboratory, USGS Woods Hole Coastal and Marine Science Center, Woods Hole Research Center, NOAA NMFS Northeast Fisheries Science Center, SEA Education Association) have a long history of collaborative activity regarding computing, computer network and information technologies that support common, inter-disciplinary science needs. Over the past several years there has been growing interest in the use of the Drupal Content Management System (CMS) playing a variety of roles in support of research projects resident at several of these organizations. Many of these projects are part of science programs that are national and international in scope. Here we survey the current uses of Drupal within the Woods Hole scientific community and examine reasons it has been adopted. The promise of emerging semantic features in the Drupal framework is examined and projections of how pre-existing Drupal-based websites might benefit are made. Closer examination of Drupal software design exposes it as more than simply a content management system. The flexibility of its architecture; the power of its taxonomy module; the care taken in nurturing the open-source developer community that surrounds it (including organized and often well-attended code sprints); the ability to bind emerging software technologies as Drupal modules; the careful selection process used in adopting core functionality; multi-site hosting and cross-site deployment of updates and a recent trend towards development of use-case inspired Drupal distributions casts Drupal as a general-purpose application deployment framework. Recent work in the semantic arena casts Drupal as an emerging RDF framework as well. Examples of roles played by Drupal-based websites within the Woods Hole scientific community that will be discussed include: science data metadata database, organization main website, biological taxonomy development, bibliographic database, physical media data archive inventory manager, disaster-response website development framework, science project task management, science conference planning, and spreadsheet-to-database converter.

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

Dehydration of 1-octadecanol over H-BEA: A combined experimental and computational study

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

Song, Wenji; Liu, Yuanshuai; Barath, Eszter

Liquid phase dehydration of 1-octdecanol, which is intermediately formed during the hydrodeoxygenation of microalgae oil, has been explored in a combined experimental and computational study. The alkyl chain of C18 alcohol interacts with acid sites during diffusion inside the zeolite pores, resulting in an inefficient utilization of the Brønsted acid sites for samples with high acid site concentrations. The parallel intra- and inter- molecular dehydration pathways having different activation energies pass through alternative reaction intermediates. Formation of surface-bound alkoxide species is the rate-limiting step during intramolecular dehydration, whereas intermolecular dehydration proceeds via a bulky dimer intermediate. Octadecene is the primarymore » dehydration product over H-BEA at 533 K. Despite of the main contribution of Brønsted acid sites towards both dehydration pathways, Lewis acid sites are also active in the formation of dioctadecyl ether. The intramolecular dehydration to octadecene and cleavage of the intermediately formed ether, however, require strong BAS. L. Wang, D. Mei and J. A. Lercher, acknowledge the partial support from the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and by the National Energy Research Scientific Computing Center (NERSC). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.« less

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed Central

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics. PMID:29163041

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system's behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities

PubMed Central

Bardhan, Jaydeep P.

2014-01-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics. PMID:25505358

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities.

PubMed

Bardhan, Jaydeep P

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

Gradient models in molecular biophysics: progress, challenges, opportunities

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g., molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding nonlocal dielectric response. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain, and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost 40 years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The review concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

Rosen's (M,R) system as an X-machine.

PubMed

Palmer, Michael L; Williams, Richard A; Gatherer, Derek

2016-11-07

Robert Rosen's (M,R) system is an abstract biological network architecture that is allegedly both irreducible to sub-models of its component states and non-computable on a Turing machine. (M,R) stands as an obstacle to both reductionist and mechanistic presentations of systems biology, principally due to its self-referential structure. If (M,R) has the properties claimed for it, computational systems biology will not be possible, or at best will be a science of approximate simulations rather than accurate models. Several attempts have been made, at both empirical and theoretical levels, to disprove this assertion by instantiating (M,R) in software architectures. So far, these efforts have been inconclusive. In this paper, we attempt to demonstrate why - by showing how both finite state machine and stream X-machine formal architectures fail to capture the self-referential requirements of (M,R). We then show that a solution may be found in communicating X-machines, which remove self-reference using parallel computation, and then synthesise such machine architectures with object-orientation to create a formal basis for future software instantiations of (M,R) systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression

PubMed Central

Zagrijchuk, Elizaveta A.; Sabirov, Marat A.; Holloway, David M.; Spirov, Alexander V.

2014-01-01

Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes. PMID:24712536

A reconfigurable NAND/NOR genetic logic gate

PubMed Central

2012-01-01

Background Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. Results We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. Conclusions We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications. PMID:22989145

A reconfigurable NAND/NOR genetic logic gate.

PubMed

Goñi-Moreno, Angel; Amos, Martyn

2012-09-18

Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.

Computational Toxicology at the US EPA | Science Inventory ...

EPA Pesticide Factsheets

Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in America’s air, water, and hazardous-waste sites. The ORD Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the EPA Science to Achieve Results (STAR) program. Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast™) and exposure (ExpoCast™), and creating virtual liver (v-Liver™) and virtual embryo (v-Embryo™) systems models. The models and underlying data are being made publicly available t

Enhancing student engagement to positively impact mathematics anxiety, confidence and achievement for interdisciplinary science subjects

NASA Astrophysics Data System (ADS)

Everingham, Yvette L.; Gyuris, Emma; Connolly, Sean R.

2017-11-01

Contemporary science educators must equip their students with the knowledge and practical know-how to connect multiple disciplines like mathematics, computing and the natural sciences to gain a richer and deeper understanding of a scientific problem. However, many biology and earth science students are prejudiced against mathematics due to negative emotions like high mathematical anxiety and low mathematical confidence. Here, we present a theoretical framework that investigates linkages between student engagement, mathematical anxiety, mathematical confidence, student achievement and subject mastery. We implement this framework in a large, first-year interdisciplinary science subject and monitor its impact over several years from 2010 to 2015. The implementation of the framework coincided with an easing of anxiety and enhanced confidence, as well as higher student satisfaction, retention and achievement. The framework offers interdisciplinary science educators greater flexibility and confidence in their approach to designing and delivering subjects that rely on mathematical concepts and practices.

Mathematics and statistics research department. Progress report, period ending June 30, 1981

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

Lever, W.E.; Kane, V.E.; Scott, D.S.

1981-09-01

This report is the twenty-fourth in the series of progress reports of the Mathematics and Statistics Research Department of the Computer Sciences Division, Union Carbide Corporation - Nuclear Division (UCC-ND). Part A records research progress in biometrics research, materials science applications, model evaluation, moving boundary problems, multivariate analysis, numerical linear algebra, risk analysis, and complementary areas. Collaboration and consulting with others throughout the UCC-ND complex are recorded in Part B. Included are sections on biology and health sciences, chemistry, energy, engineering, environmental sciences, health and safety research, materials sciences, safeguards, surveys, and uranium resource evaluation. Part C summarizes the variousmore » educational activities in which the staff was engaged. Part D lists the presentations of research results, and Part E records the staff's other professional activities during the report period.« less

A Multidisciplined Teaching Reform of Biomaterials Course for Undergraduate Students

NASA Astrophysics Data System (ADS)

Li, Xiaoming; Zhao, Feng; Pu, Fang; Liu, Haifeng; Niu, Xufeng; Zhou, Gang; Li, Deyu; Fan, Yubo; Feng, Qingling; Cui, Fu-zhai; Watari, Fumio

2015-12-01

The biomaterials science has advanced in a high speed with global science and technology development during the recent decades, which experts predict to be more obvious in the near future with a more significant position for medicine and health care. Although the three traditional subjects, such as medical science, materials science and biology that act as a scaffold to support the structure of biomaterials science, are still essential for the research and education of biomaterials, other subjects, such as mechanical engineering, mechanics, computer science, automatic science, nanotechnology, and Bio-MEMS, are playing more and more important roles in the modern biomaterials science development. Thus, the research and education of modern biomaterials science should require a logical integration of the interdisciplinary science and technology, which not only concerns medical science, materials science and biology, but also includes other subjects that have been stated above. This article focuses on multidisciplinary nature of biomaterials, the awareness of which is currently lacking in the education at undergraduate stage. In order to meet this educational challenge, we presented a multidisciplinary course that referred to not only traditional sciences, but also frontier sciences and lasted for a whole academic year for senior biomaterials undergraduate students with principles of a better understanding of the modern biomaterials science and meeting the requirements of the future development in this area. The course has been shown to gain the recognition of the participants by questionaries and specific "before and after" comments and has also gained high recognition and persistent supports from our university. The idea of this course might be also fit for the education and construction of some other disciplines.

A new approach to the rationale discovery of polymeric biomaterials

PubMed Central

Kohn, Joachim; Welsh, William J.; Knight, Doyle

2007-01-01

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

Virtual Learning in the Biological Sciences: Pitfalls of Simply "Putting Notes on the Web"

ERIC Educational Resources Information Center

Evans, Chris; Gibbons, Nicola J.; Shah, Kavita; Griffin, Darren K.

2004-01-01

Computer-based learning (CBL) is well established and its benefits are widely reported. It has found considerable utility in recent years with the explosion in interest in the use of the Web as a knowledge medium. Many online courses, however, consist merely of a series of textual notes and pictures with little navigational information or choice.…

Examining the Use of Web-Based Tests for Testing Academic Vocabulary in EAP Instruction

ERIC Educational Resources Information Center

Dashtestani, Reza

2015-01-01

Interest in Web-based and computer-assisted language testing is growing in the field of English for academic purposes (EAP). In this study, four groups of undergraduate EAP students (n = 120), each group consisted of 30 students, were randomly selected from four different disciplines, i.e. biology, political sciences, psychology, and law. The four…

77 FR 27470 - Center for Scientific Review Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-10

..., Prevention and Intervention for Addictions Study Section. Date: June 7-8, 2012. Time: 8:00 a.m. to 5:00 p.m...: Bioengineering Sciences & Technologies Integrated Review Group; Nanotechnology Study Section. Date: June 7-8..., Computational Biology and Technology Study Section. Date: June 7-8, 2012. Time: 8:30 a.m. to 6:00 p.m. Agenda...

The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences

PubMed Central

Stefan, Melanie I.; Gutlerner, Johanna L.; Born, Richard T.; Springer, Michael

2015-01-01

The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others. PMID:25880064

The quantitative methods boot camp: teaching quantitative thinking and computing skills to graduate students in the life sciences.

PubMed

Stefan, Melanie I; Gutlerner, Johanna L; Born, Richard T; Springer, Michael

2015-04-01

The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a "boot camp" in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students' engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.

Applications of penetrating radiation for small animal imaging

NASA Astrophysics Data System (ADS)

Hasegawa, Bruce H.; Wu, Max C.; Iwata, Koji; Hwang, Andrew B.; Wong, Kenneth H.; Barber, William C.; Dae, Michael W.; Sakdinawat, Anne E.

2002-11-01

Researchers long have relied on research involving small animals to unravel scientific mysteries in the biological sciences, and to develop new diagnostic and therapeutic techniques in the medical and health sciences. Within the past 2 decades, new techniques have been developed to manipulate the genome of the mouse, allowing the development of transgenic and knockout models of mammalian and human disease, development, and physiology. Traditionally, much biological research involving small animals has relied on the use of invasive methods such as organ harvesting, tissue sampling, and autoradiography during which the animal was sacrificed to perform a single measurement. More recently, imaging techniques have been developed that assess anatomy and physiology in the intact animal, in a way that allows the investigator to follow the progression of disease, or to monitor the response to therapeutic interventions. Imaging techniques that use penetrating radiation at millimeter or submillimeter levels to image small animals include x-ray computed tomography (microCT), single-photon emission computed tomography (microSPECT), and imaging positron emission computed tomography (microPET). MicroCT generates cross-sectional slices which reveal the structure of the object with spatial resolution in the range of 50 to 100 microns. MicroSPECT and microPET are radionuclide imaging techniques in which a radiopharmaceutical is injected into the animal that is accumulated to metabolism, blood flow, bone remodeling, tumor growth, or other biological processes. Both microSPECT and microPET offer spatial resolutions in the range of 1-2 millimeters. However, microPET records annihilation photons produced by a positron-emitting radiopharmaceutical using electronic coincidence, and has a sensitivity approximately two orders of magnitude better than microSPECT, while microSPECT is compatible with gamma-ray emitting radiopharmaceuticals that are less expensive and more readily available than those used with microPET. High-resolution dual-modality imaging systems now are being developed that combine microPET or microSPECT with microCT in a way that facilitates more direct correlation of anatomy and physiology in the same animal. Small animal imaging allows researchers to perform experiments that are not possible with conventional invasive techniques, and thereby are becoming increasingly important tools for discovery of fundamental biological information, and development of new diagnostic and therapeutic techniques in the biomedical sciences.

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), physics (fluid-dynamical and quantum-mechanical calculations; extensive numerical simulations of various condensed-matter systems; the development of stellar constellations, even the early Universe), chemistry (quantum-chemical calculations on the structures of new chemical compounds; chemical reactions and reaction dynamics), and biology (various models, for example, in population dynamics). We succeeded in our effort to assemble several internationally recognized researchers of Computational Science to deliver invited talks on a couple of exceptionally beautiful late-summer days in the modern premises of the Adult Education Center at Lahti. Among the plenary speakers, Per Bak described his highly original work on self-organized criticality. David Ceperley discussed pioneering numerical simulations of superfluid helium in which, for the first time, Feynman's path-integral formulation of quantum mechanics has been implemented on a computer. Jim Gunton presented his comprehensive studies of the Cahn-Hilliard equation for the dynamics of ordering in a condensed-matter system far from equilibrium, while Alex Hansen explained those on nonlinear breakdown in disordered materials. Representing the important field of computational chemistry, Bo Jönsson dealt with attractive forces between polyelectrolytes. Kurt Kremer gave an interesting account on computer-simulation studies of complex polymer systems, while Ole Mouritsen reviewed studies of interfacial fluctuations in lipid membranes. Pekka Pyykkö introduced his pioneering work which has led to predictions of completely novel chemical species. Annette Zippelius gave an expert introduction to the highly active field of neural networks. It is evident from each of these intriguing plenary contributions that, indeed, the computational approach is a frontier field of science, possibly providing the most versatile research method available today. We also arranged a competition for the best Posters presented at the Symposium; the Prizes were some of the newest books on the beauty of fractals. The First Prize was won by Hanna Viertio, the Second Prize by Miguel Zendejas and the Third Prize was shared by Leo Kärkkäinen and Kari Rummukainen. As for the future of Computational Science, we identify two principal avenues: (a) big science - large centers with ultrafast supercomputers, and (b) small science - active groups utilizing personal minisupercomputers or supenvorkstations. At present, it appears that the latter already compete extremely favourably in their performance with the massive supercomputers - at least in their throughput and, especially, in tasks where a broad range of diverse software support is not absolutely necessary. In view of this important emergence of "personal supercomputing", we envisage that the role and the development of large computer centers will have to be reviewed critically and modified accordingly. Furthermore, a promise for some radically new approaches to Computational Science could be provided by massively parallel computers; among them, maybe solutions based on ideas of neural computing could be utilized, especially for restricted applications. Therefore, in order not to overlook any important advances within such a forefront field, one should rather choose the strategy of actively following each and every one of these routes. In perspective of the large variety of simultaneous developments, we want to emphasize the importance of Nordic collaboration in sharing expertise and experience in the rapidly progressing research - it ought to be cultivated and could be expanded. Therefore, we think that it is vitally important to continue with and to further promote the kind of Nordic Symposia that have been held at Lund, Kolle-Kolle, and Lahti. We want to thank most cordially the plenary and invited speakers, contributors, students, and in particular the Conference Secretary, Ms Ulla Ahlfors and Dr Milja Mäkelä, who was responsible for the local arrangements. The work that they did served to make this Symposium a scientific success and a useful and pleasant experience for all the well over 100 participants. We also thank the City of Lahti for kindly arranging a refreshing reception at the Town Hall. We wish to express our gratitude to Nordiska Kulturfonden, NORDITA, the Research Institute for Theoretical Physics at the University of Helsinki, the Finnish Ministry of Education and the Academy of Finland for their financial support. March 1990

Seeing Science through Symmetry

NASA Astrophysics Data System (ADS)

Gould, L. I.

Seeing Through Symmetry is a course that introduces non-science majors to the pervasive influence of symmetry in science. The concept of symmetry is usedboth as a link between subjects (such as physics, biology, mathematics, music, poetry, and art) and as a method within a subject. This is done through the development and use of interactive multimedia learning environments to stimulate learning. Computer-based labs enable the student to further explore the concept by being gently led from the arts to science. This talk is an update that includes some of the latest changes to the course. Explanations are given on methodology and how a variety of interactive multimedia tools contribute to both the lecture and lab portion of the course (created in 1991 and taught almost every semester since then, including one in Sweden).

Sixth International Conference on Systems Biology (ICSB 2005)

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

Professor Andrew Murray

2005-10-22

This grant supported the Sixth International Conference on Systems Biology (ICSB 2005), held in Boston, Massachusetts from October 19th to 22nd, 2005. The ICSB is the only major, annual, international conference focused exclusively on the important emerging field of systems biology. It draws together scientists with expertise in theoretical, computational and experimental approaches to understanding biological systems at many levels. Previous ICSB meetings have been held in Tokyo (2000), at Caltech (2001), at the Karolinska Institute (2002), at Washington University in St. Louis (2003), and in Heidelberg (2004). These conferences have been increasingly successful at bringing together the growing communitymore » of established and junior researchers with interests in this area. Boston is home to several groups that have shown leadership in the field and was therefore an ideal place to hold this conference . The executive committee for the conference comprised Jim Collins (Biomedical Engineering, Boston University), Marc Kirschner (chair of the new Department of Systems Biology at Harvard Medical School), Eric Lander (director of the Broad Institute of MIT and Harvard), Andrew Murray (director of Harvard’s Bauer Center for Genomics Research) and Peter Sorger (director of MIT’s Computational and Systems Biology Initiative). There are almost as many definitions of systems biology as there are systems biologists. We take a broad view of the field, and we succeeded in one of our major aims in organizing a conference that bridges two types of divide. The first is that between traditional academic disciplines: each of our sessions includes speakers from biology and from one or more physical or quantitative sciences. The second type includes those that separate experimental biologists from their colleagues who work on theory or computation. Here again, each session included representatives from at least two of these three categories; indeed, many of the speakers combined at least two of the categories in their own research activities. We define systems biology as a widening of focus in biology from individual genes or proteins to the complex networks of these molecules that allow cells and organisms to function. In the same way that conscious thought cannot be said to reside in any single neuron in the brain, simpler biological functions such as cell division arise from the interactions among many components in a network or ‘functional module’. For us, systems biology is characterized by the recognition that a higher-order description of biological function, accompanied by quantitative methods of analysis — often borrowed from disciplines such as physics, engineering, computer science or mathematics — can lead to the identification of general principles that underlie the structure, behavior, and evolution of cells and organisms. The heart of the conference were sessions on six topics: intracellular dynamics (featuring measurements on single cells, and their interpretation); biology by design (synthetic biology); intracellular networks (signal transduction and transcriptional regulation); multicellular networks (development and pattern formation); mechanics and scale in cellular behavior (featuring work on cytoskeletal mechanics, and on scaling relationships in biology); and evolution in action (including experimental evolution, of both real and artificial life-forms). Each session had four invited speakers; 23 of the 24 invited speakers attended (see below). We have selected these speakers not only for the interest of their research, but for their skills as communicators, thereby giving us the best chance of bridging the divides mentioned above. We also made a point of including women, younger investigators and people from outside the United States among the speakers. In addition to the invited speakers, we allotted time in the program for at least five contributed talks, which were selected from the poster submissions. Our aim in selecting these contributors showcased work that is “hot off the bench” (or computer) at the time of the conference, and also created additional opportunities for younger investigators to present their work. The main conference was preceded by a day of tutorials, and followed by two days of workshops, on a range of topics in quantitative, computational and systems biology.« less

Greek Students' Science-related Interests and Experiences: Gender differences and correlations

NASA Astrophysics Data System (ADS)

Christidou, Vasilia

2006-08-01

This paper explores the science-related interests and out-of-school experiences of 583 ninth-grade Greek students. The instrument of data collection consisted of a questionnaire including items on science-related topics that could be of interest to students and on everyday, out-of-school, science-related experiences. Factor analysis yielded six distinct fields of interest and five types of science-related experiences. Significant gender differences emerge: girls are more interested in topics related to human biology, health, and fitness, and are more familiar with using instruments and devices, seeking information about nature, and doing cuisine and handicraft; while boys are more interested in science, technology, and their social dimension, and the threatening aspects of science and technology, and tend to engage more in manual work and computer use. The results of this study indicate that there is a need for the Greek science curriculum to become more appealing to students, by integrating topics and experiences that are interesting and relevant to them.

Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

PubMed Central

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy. PMID:22163841

Paradoxical Personality and Academic Achievement in College Students From Buenos Aires

PubMed Central

Freiberg Hoffmann, Agustín; Fernández Liporace, María Mercedes

2015-01-01

This paper presents a study on paradoxical personality, defined as a distinctive feature in creative persons, developed with 350 college students from Buenos Aires. Goals aimed at describing and analysing possible significant differences of paradoxical traits in students from diverse majors representing seven different fields of study, and examining the relationship between each bipolar trait and academic achievement. The sample was composed of 7 groups (n = 50 by group) representing fields of study typically offered in public universities, Biology, Computer Science, Engineering, Law, Nutrition, Psychology, and History of Art. Analyses by career provided descriptive information about students of these majors, concerning their paradoxical personality profiles. Correlational studies verified significant associations between academic achievement and most paradoxical traits in majors such as Computer Science, Nutrition and Psychology. Results are discussed regarding practical outcomes and teaching programs. PMID:27247680

U.S. Department of Energy's Bioenergy Research Centers An Overview of the Science

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

None

2010-07-01

Alternative fuels from renewable cellulosic biomass - plant stalks, trunks, stems, and leaves - are expected to significantly reduce U.S. dependence on imported oil while enhancing national energy security and decreasing the environmental impacts of energy use. Ethanol and other advanced biofuels from cellulosic biomass are renewable alternatives that could increase domestic production of transportation fuels, revitalize rural economies, and reduce carbon dioxide and pollutant emissions. According to U.S. Secretary of Energy Steven Chu, 'Developing the next generation of biofuels is key to our effort to end our dependence on foreign oil and address the climate crisis while creating millionsmore » of new jobs that can't be outsourced.' Although cellulosic ethanol production has been demonstrated on a pilot level, developing a cost-effective, commercial-scale cellulosic biofuel industry will require transformational science to significantly streamline current production processes. Woodchips, grasses, cornstalks, and other cellulosic biomass are widely abundant but more difficult to break down into sugars than corn grain - the primary source of U.S. ethanol fuel production today. Biological research is key to accelerating the deconstruction of cellulosic biomass into sugars that can be converted to biofuels. The Department of Energy (DOE) Office of Science continues to play a major role in inspiring, supporting, and guiding the biotechnology revolution over the past 30 years. The DOE Genomic Science program is advancing a new generation of research focused on achieving whole-systems understanding of biology. This program is bringing together scientists in diverse fields to understand the complex biology underlying solutions to DOE missions in energy production, environmental remediation, and climate change science. For more information on the Genomic Science program, see p. 26. To focus the most advanced biotechnology-based resources on the biological challenges of biofuel production, DOE established three Bioenergy Research Centers (BRCs) in September 2007. Each center is pursuing the basic research underlying a range of high-risk, high-return biological solutions for bioenergy applications. Advances resulting from the BRCs are providing the knowledge needed to develop new biobased products, methods, and tools that the emerging biofuel industry can use (see sidebar, Bridging the Gap from Fundamental Biology to Industrial Innovation for Bioenergy, p. 6). The DOE BRCs have developed automated, high-throughput analysis pipelines that will accelerate scientific discovery for biology-based biofuel research. The three centers, which were selected through a scientific peer-review process, are based in geographically diverse locations - the Southeast, the Midwest, and the West Coast - with partners across the nation (see U.S. map, DOE Bioenergy Research Centers and Partners, on back cover). DOE's Lawrence Berkeley National Laboratory leads the DOE Joint BioEnergy Institute (JBEI) in California; DOE's Oak Ridge National Laboratory leads the BioEnergy Science Center (BESC) in Tennessee; and the University of Wisconsin-Madison leads the Great Lakes Bioenergy Research Center (GLBRC). Each center represents a multidisciplinary partnership with expertise spanning the physical and biological sciences, including genomics, microbial and plant biology, analytical chemistry, computational biology and bioinformatics, and engineering. Institutional partners include DOE national laboratories, universities, private companies, and nonprofit organizations.« less

Promoting Systems Thinking through Biology Lessons

NASA Astrophysics Data System (ADS)

Riess, Werner; Mischo, Christoph

2010-04-01

This study's goal was to analyze various teaching approaches within the context of natural science lessons, especially in biology. The main focus of the paper lies on the effectiveness of different teaching methods in promoting systems thinking in the field of Education for Sustainable Development. The following methods were incorporated into the study: special lessons designed to promote systems thinking, a computer-simulated scenario on the topic "ecosystem forest," and a combination of both special lessons and the computer simulation. These groups were then compared to a control group. A questionnaire was used to assess systems thinking skills of 424 sixth-grade students of secondary schools in Germany. The assessment differentiated between a conceptual understanding (measured as achievement score) and a reflexive justification (measured as justification score) of systems thinking. The following control variables were used: logical thinking, grades in school, memory span, and motivational goal orientation. Based on the pretest-posttest control group design, only those students who received both special instruction and worked with the computer simulation showed a significant increase in their achievement scores. The justification score increased in the computer simulation condition as well as in the combination of computer simulation and lesson condition. The possibilities and limits of promoting various forms of systems thinking by using realistic computer simulations are discussed.

Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.

PubMed

Louridas, George E; Lourida, Katerina G

2017-02-21

Systems biology is an important concept that connects molecular biology and genomics with computing science, mathematics and engineering. An endeavor is made in this paper to associate basic conceptual ideas of systems biology with clinical medicine. Complex cardiac diseases are clinical phenotypes generated by integration of genetic, molecular and environmental factors. Basic concepts of systems biology like network construction, modular thinking, biological constraints (downward biological direction) and emergence (upward biological direction) could be applied to clinical medicine. Especially, in the field of cardiology, these concepts can be used to explain complex clinical cardiac phenotypes like chronic heart failure and coronary artery disease. Cardiac diseases are biological complex entities which like other biological phenomena can be explained by a systems biology approach. The above powerful biological tools of systems biology can explain robustness growth and stability during disease process from modulation to phenotype. The purpose of the present review paper is to implement systems biology strategy and incorporate some conceptual issues raised by this approach into the clinical field of complex cardiac diseases. Cardiac disease process and progression can be addressed by the holistic realistic approach of systems biology in order to define in better terms earlier diagnosis and more effective therapy.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.

Geological applications and training in remote sensing

NASA Technical Reports Server (NTRS)

Sabins, F. F., Jr.

1981-01-01

Some of the experiences, methods, and opinions developed during 15 years of teaching an introductory course in remote sensing at several universities in the Southern California area are related. Although the course is offered in Geology departments, every class includes significant numbers of students from other disciplines including geography, computer science, biology, and environmental science. The instructor or teaching assistant provides a few hours of tutorial lectures (outside of regular class time) on basic geology for these nongeologists. This approach is successful because the grade distribution for nongeologists is similar to that for geologists. The schedule for a typical one-semester course is given.

Theodor Bücher Lecture. Metabolomics, modelling and machine learning in systems biology - towards an understanding of the languages of cells. Delivered on 3 July 2005 at the 30th FEBS Congress and the 9th IUBMB conference in Budapest.

PubMed

Kell, Douglas B

2006-03-01

The newly emerging field of systems biology involves a judicious interplay between high-throughput 'wet' experimentation, computational modelling and technology development, coupled to the world of ideas and theory. This interplay involves iterative cycles, such that systems biology is not at all confined to hypothesis-dependent studies, with intelligent, principled, hypothesis-generating studies being of high importance and consequently very far from aimless fishing expeditions. I seek to illustrate each of these facets. Novel technology development in metabolomics can increase substantially the dynamic range and number of metabolites that one can detect, and these can be exploited as disease markers and in the consequent and principled generation of hypotheses that are consistent with the data and achieve this in a value-free manner. Much of classical biochemistry and signalling pathway analysis has concentrated on the analyses of changes in the concentrations of intermediates, with 'local' equations - such as that of Michaelis and Menten v=(Vmax x S)/(S+K m) - that describe individual steps being based solely on the instantaneous values of these concentrations. Recent work using single cells (that are not subject to the intellectually unsupportable averaging of the variable displayed by heterogeneous cells possessing nonlinear kinetics) has led to the recognition that some protein signalling pathways may encode their signals not (just) as concentrations (AM or amplitude-modulated in a radio analogy) but via changes in the dynamics of those concentrations (the signals are FM or frequency-modulated). This contributes in principle to a straightforward solution of the crosstalk problem, leads to a profound reassessment of how to understand the downstream effects of dynamic changes in the concentrations of elements in these pathways, and stresses the role of signal processing (and not merely the intermediates) in biological signalling. It is this signal processing that lies at the heart of understanding the languages of cells. The resolution of many of the modern and postgenomic problems of biochemistry requires the development of a myriad of new technologies (and maybe a new culture), and thus regular input from the physical sciences, engineering, mathematics and computer science. One solution, that we are adopting in the Manchester Interdisciplinary Biocentre (http://www.mib.ac.uk/) and the Manchester Centre for Integrative Systems Biology (http://www.mcisb.org/), is thus to colocate individuals with the necessary combinations of skills. Novel disciplines that require such an integrative approach continue to emerge. These include fields such as chemical genomics, synthetic biology, distributed computational environments for biological data and modelling, single cell diagnostics/bionanotechnology, and computational linguistics/text mining.

78 FR 33115 - Biological Sciences Advisory Committee; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-03

... NATIONAL SCIENCE FOUNDATION Biological Sciences Advisory Committee; Notice of Meeting In... Foundation announces the following meeting: Name: Biological Sciences Advisory Committee ( 1110). Date and... 22230. All visitors should contact the Directorate of Biological Sciences [call 703-292-8400 or send an...

Fundamentals and Recent Developments in Approximate Bayesian Computation

PubMed Central

Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka

2017-01-01

Abstract Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments. [ABC; approximate Bayesian computation; Bayesian inference; likelihood-free inference; phylogenetics; simulator-based models; stochastic simulation models; tree-based models.] PMID:28175922

ISMB/ECCB 2009 Stockholm

PubMed Central

Sagot, Marie-France; McKay, B.J. Morrison; Myers, Gene

2009-01-01

The International Society for Computational Biology (ISCB; http://www.iscb.org) presents the Seventeenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), organized jointly with the Eighth Annual European Conference on Computational Biology (ECCB; http://bioinf.mpi-inf.mpg.de/conferences/eccb/eccb.htm), in Stockholm, Sweden, 27 June to 2 July 2009. The organizers are putting the finishing touches on the year's premier computational biology conference, with an expected attendance of 1400 computer scientists, mathematicians, statisticians, biologists and scientists from other disciplines related to and reliant on this multi-disciplinary science. ISMB/ECCB 2009 (http://www.iscb.org/ismbeccb2009/) follows the framework introduced at the ISMB/ECCB 2007 (http://www.iscb.org/ismbeccb2007/) in Vienna, and further refined at the ISMB 2008 (http://www.iscb.org/ismb2008/) in Toronto; a framework developed to specifically encourage increased participation from often under-represented disciplines at conferences on computational biology. During the main ISMB conference dates of 29 June to 2 July, keynote talks from highly regarded scientists, including ISCB Award winners, are the featured presentations that bring all attendees together twice a day. The remainder of each day offers a carefully balanced selection of parallel sessions to choose from: proceedings papers, special sessions on emerging topics, highlights of the past year's published research, special interest group meetings, technology demonstrations, workshops and several unique sessions of value to the broad audience of students, faculty and industry researchers. Several hundred posters displayed for the duration of the conference has become a standard of the ISMB and ECCB conference series, and an extensive commercial exhibition showcases the latest bioinformatics publications, software, hardware and services available on the market today. The main conference is preceded by 2 days of Special Interest Group (SIG) and Satellite meetings running in parallel to the fifth Student Council Symposium on 27 June, and in parallel to Tutorials on 28 June. All scientific sessions take place at the Stockholmsmässan/Stockholm International Fairs conference and exposition facility. Contact: bj@iscb.org PMID:19447790

A novel paradigm for cell and molecule interaction ontology: from the CMM model to IMGT-ONTOLOGY

PubMed Central

2010-01-01

Background Biology is moving fast toward the virtuous circle of other disciplines: from data to quantitative modeling and back to data. Models are usually developed by mathematicians, physicists, and computer scientists to translate qualitative or semi-quantitative biological knowledge into a quantitative approach. To eliminate semantic confusion between biology and other disciplines, it is necessary to have a list of the most important and frequently used concepts coherently defined. Results We propose a novel paradigm for generating new concepts for an ontology, starting from model rather than developing a database. We apply that approach to generate concepts for cell and molecule interaction starting from an agent based model. This effort provides a solid infrastructure that is useful to overcome the semantic ambiguities that arise between biologists and mathematicians, physicists, and computer scientists, when they interact in a multidisciplinary field. Conclusions This effort represents the first attempt at linking molecule ontology with cell ontology, in IMGT-ONTOLOGY, the well established ontology in immunogenetics and immunoinformatics, and a paradigm for life science biology. With the increasing use of models in biology and medicine, the need to link different levels, from molecules to cells to tissues and organs, is increasingly important. PMID:20167082

4D bioprinting: the next-generation technology for biofabrication enabled by stimuli-responsive materials.

PubMed

Li, Yi-Chen; Zhang, Yu Shrike; Akpek, Ali; Shin, Su Ryon; Khademhosseini, Ali

2016-12-02

Four-dimensional (4D) bioprinting, encompassing a wide range of disciplines including bioengineering, materials science, chemistry, and computer sciences, is emerging as the next-generation biofabrication technology. By utilizing stimuli-responsive materials and advanced three-dimensional (3D) bioprinting strategies, 4D bioprinting aims to create dynamic 3D patterned biological structures that can transform their shapes or behavior under various stimuli. In this review, we highlight the potential use of various stimuli-responsive materials for 4D printing and their extension into biofabrication. We first discuss the state of the art and limitations associated with current 3D printing modalities and their transition into the inclusion of the additional time dimension. We then suggest the potential use of different stimuli-responsive biomaterials as the bioink that may achieve 4D bioprinting where transformation of fabricated biological constructs can be realized. We finally conclude with future perspectives.

Economic Aspects of the Chemical Industry

NASA Astrophysics Data System (ADS)

Koleske, Joseph V.

Within the formal disciplines of science at traditional universities, through the years, chemistry has grown to have a unique status because of its close correspondence with an industry and with a branch of engineering—the chemical industry and chemical engineering. There is no biology industry, but aspects of biology have closely related disciplines such as fish raising and other aquaculture, animal cloning and other facets of agriculture, ethical drugs of pharmaceutical manufacture, genomics, water quality and conservation, and the like. Although there is no physics industry, there are power generation, electricity, computers, optics, magnetic media, and electronics that exist as industries. However, in the case of chemistry, there is a named industry. This unusual correspondence no doubt came about because in the chemical industry one makes things from raw materials—chemicals—and the science, manufacture, and use of chemicals grew up together during the past century or so.

Opportunities and challenges for the life sciences community.

PubMed

Kolker, Eugene; Stewart, Elizabeth; Ozdemir, Vural

2012-03-01

Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19-20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16-17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org ) was formed to become a Digital Commons for the life sciences community.

Opportunities and Challenges for the Life Sciences Community

PubMed Central

Stewart, Elizabeth; Ozdemir, Vural

2012-01-01

Abstract Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19–20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16–17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org) was formed to become a Digital Commons for the life sciences community. PMID:22401659

The hair follicle enigma.

PubMed

Bernard, Bruno A

2017-06-01

The hair follicle is a mini-organ endowed with a unique structure and cyclic behaviour. Despite the intense research efforts which have been devoted at deciphering the hair follicle biology over the past 70 years, one must admit that hair follicle remains an enigma. In this brief review, various aspects of hair follicle biology will be addressed, and more importantly, unsolved questions and new possible research tracks will be highlighted, including hair follicle glycobiology and exosome-mediated cell-cell interactions. Even though bricks of knowledge are solidly being acquired, an integrative picture remains to emerge. One can predict that computer science, algorithms and bioinformatics will assist in fostering our understanding hair biology. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Answering Schrödinger's question: A free-energy formulation

NASA Astrophysics Data System (ADS)

Ramstead, Maxwell James Désormeau; Badcock, Paul Benjamin; Friston, Karl John

2018-03-01

The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery.

Using an Adaptive Expertise Lens to Understand the Quality of Teachers' Classroom Implementation of Computer-Supported Complex Systems Curricula in High School Science

ERIC Educational Resources Information Center

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-01-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to…

Computational and Genomic Analysis of Mycobacteriophage: A Longitudinal Study of Technology Engineered Biology Courses That Implemented an Inquiry Based Laboratory Practice Designed to Enhance, Encourage, and Empower Student Learning

ERIC Educational Resources Information Center

Hollowell, Gail P.; Osler, James E.; Hester, April L.

2015-01-01

This paper provides an applied research rational for a longitudinal investigation that involved teaching a "Technology Engineered Science Education Course" via an Interactive Laboratory Based Genomics Curriculum. The Technology st Engineering [TE] methodology was first introduced at the SAPES: South Atlantic Philosophy of Education…

Genomics for Everyone

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

Chain, Patrick

Genomics — the genetic mapping and DNA sequencing of sets of genes or the complete genomes of organisms, along with related genome analysis and database work — is emerging as one of the transformative sciences of the 21st century. But current bioinformatics tools are not accessible to most biological researchers. Now, a new computational and web-based tool called EDGE Bioinformatics is working to fulfill the promise of democratizing genomics.

Establishment of a Vaporous Hydrogen Peroxide Bio-Decontamination Capability

DTIC Science & Technology

2007-02-01

of Colorado at Denver and Health Sciences Center. There he utilised mass spectrometry to investigate the biochemical pathways involved in lipid... techniques (NMR, GC). Since then she has worked in a variety of areas including: (a) computer simulation of vapour dispersion for early warning to...to inactivate biological agents such as B. anthracis and these include beta-propiolactone, chlorine dioxide, ethylene oxide, propylene oxide, ozone

The State of Software for Evolutionary Biology.

PubMed

Darriba, Diego; Flouri, Tomáš; Stamatakis, Alexandros

2018-05-01

With Next Generation Sequencing data being routinely used, evolutionary biology is transforming into a computational science. Thus, researchers have to rely on a growing number of increasingly complex software. All widely used core tools in the field have grown considerably, in terms of the number of features as well as lines of code and consequently, also with respect to software complexity. A topic that has received little attention is the software engineering quality of widely used core analysis tools. Software developers appear to rarely assess the quality of their code, and this can have potential negative consequences for end-users. To this end, we assessed the code quality of 16 highly cited and compute-intensive tools mainly written in C/C++ (e.g., MrBayes, MAFFT, SweepFinder, etc.) and JAVA (BEAST) from the broader area of evolutionary biology that are being routinely used in current data analysis pipelines. Because, the software engineering quality of the tools we analyzed is rather unsatisfying, we provide a list of best practices for improving the quality of existing tools and list techniques that can be deployed for developing reliable, high quality scientific software from scratch. Finally, we also discuss journal as well as science policy and, more importantly, funding issues that need to be addressed for improving software engineering quality as well as ensuring support for developing new and maintaining existing software. Our intention is to raise the awareness of the community regarding software engineering quality issues and to emphasize the substantial lack of funding for scientific software development.

Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

NASA Astrophysics Data System (ADS)

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-05-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

77 FR 50174 - Biological Sciences Advisory Committee; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-20

... NATIONAL SCIENCE FOUNDATION Biological Sciences Advisory Committee; Notice of Meeting In... Foundation announces the following meeting: Name: Biological Sciences Advisory Committee ( 1110). Date and... Biological Sciences [call 703-292-8400 or send an email message to [email protected] ] at least 24 hours prior...

The Number of Scholarly Documents on the Public Web

PubMed Central

Khabsa, Madian; Giles, C. Lee

2014-01-01

The number of scholarly documents available on the web is estimated using capture/recapture methods by studying the coverage of two major academic search engines: Google Scholar and Microsoft Academic Search. Our estimates show that at least 114 million English-language scholarly documents are accessible on the web, of which Google Scholar has nearly 100 million. Of these, we estimate that at least 27 million (24%) are freely available since they do not require a subscription or payment of any kind. In addition, at a finer scale, we also estimate the number of scholarly documents on the web for fifteen fields: Agricultural Science, Arts and Humanities, Biology, Chemistry, Computer Science, Economics and Business, Engineering, Environmental Sciences, Geosciences, Material Science, Mathematics, Medicine, Physics, Social Sciences, and Multidisciplinary, as defined by Microsoft Academic Search. In addition, we show that among these fields the percentage of documents defined as freely available varies significantly, i.e., from 12 to 50%. PMID:24817403

The number of scholarly documents on the public web.

PubMed

Khabsa, Madian; Giles, C Lee

2014-01-01

The number of scholarly documents available on the web is estimated using capture/recapture methods by studying the coverage of two major academic search engines: Google Scholar and Microsoft Academic Search. Our estimates show that at least 114 million English-language scholarly documents are accessible on the web, of which Google Scholar has nearly 100 million. Of these, we estimate that at least 27 million (24%) are freely available since they do not require a subscription or payment of any kind. In addition, at a finer scale, we also estimate the number of scholarly documents on the web for fifteen fields: Agricultural Science, Arts and Humanities, Biology, Chemistry, Computer Science, Economics and Business, Engineering, Environmental Sciences, Geosciences, Material Science, Mathematics, Medicine, Physics, Social Sciences, and Multidisciplinary, as defined by Microsoft Academic Search. In addition, we show that among these fields the percentage of documents defined as freely available varies significantly, i.e., from 12 to 50%.

Vertical and horizontal integration of bioinformatics education: A modular, interdisciplinary approach.

PubMed

Furge, Laura Lowe; Stevens-Truss, Regina; Moore, D Blaine; Langeland, James A

2009-01-01

Bioinformatics education for undergraduates has been approached primarily in two ways: introduction of new courses with largely bioinformatics focus or introduction of bioinformatics experiences into existing courses. For small colleges such as Kalamazoo, creation of new courses within an already resource-stretched setting has not been an option. Furthermore, we believe that a true interdisciplinary science experience would be best served by introduction of bioinformatics modules within existing courses in biology and chemistry and other complementary departments. To that end, with support from the Howard Hughes Medical Institute, we have developed over a dozen independent bioinformatics modules for our students that are incorporated into courses ranging from general chemistry and biology, advanced specialty courses, and classes in complementary disciplines such as computer science, mathematics, and physics. These activities have largely promoted active learning in our classrooms and have enhanced student understanding of course materials. Herein, we describe our program, the activities we have developed, and assessment of our endeavors in this area. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

Intention, emotion, and action: a neural theory based on semantic pointers.

PubMed

Schröder, Tobias; Stewart, Terrence C; Thagard, Paul

2014-06-01

We propose a unified theory of intentions as neural processes that integrate representations of states of affairs, actions, and emotional evaluation. We show how this theory provides answers to philosophical questions about the concept of intention, psychological questions about human behavior, computational questions about the relations between belief and action, and neuroscientific questions about how the brain produces actions. Our theory of intention ties together biologically plausible mechanisms for belief, planning, and motor control. The computational feasibility of these mechanisms is shown by a model that simulates psychologically important cases of intention. © 2013 Cognitive Science Society, Inc.

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

Radman, Ali M

The Division of Natural Sciences and Mathematics is housed in the Wilson-Booker Science Building (WBSB) which previously consisted of six classrooms, a lecture room, three biology laboratories, one physics laboratory, one chemistry laboratory, one research laboratory, and three computer laboratories. However, due to rapid expansion in STEM majors, there was a dire need for more classroom and laboratory space to accommodate this expansion. Further, since the College started integrating research into the curriculum in 2004 in order to keep pace with the national trend in science education, it has become apparent that one small research laboratory that accommodates 10 studentsmore » will not keep pace with the growing needs of the new students interested in research. Therefore , it became imperative to add another research laboratory to augment the existing one. Thus, the new instrumentation/Research Laboratory will provide space for the new equipment and research space for an additional 8 - 10 students. In addition, the new WBSB wing also houses a Biochemisty/Molecular Biology Laboratory, an Organic Chemistry laboratory, an Animal Laboratory, a Seminar Room, two spacious classrooms, and 3 Faculty Offices. The impact of the new facility will be far-reaching.« less

Bioinformatics clouds for big data manipulation.

PubMed

Dai, Lin; Gao, Xin; Guo, Yan; Xiao, Jingfa; Zhang, Zhang

2012-11-28

As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

COAChing Women to Succeed in Academic Careers in the Chemical Sciences

NASA Astrophysics Data System (ADS)

Richmond, Geraldine L.

2005-03-01

COAChing (Committee on the Advancement of Women Chemists) was formed in 1998 by a group of senior women chemists to address issues related to the documented disparity in hiring, promotion, and advancement of women faculty in academic chemistry departments in the United States. Several national programs have been launched by COACh that are already showing a high degree of impact on the lives and careers of many women chemists in the academic arena. As word of the effectiveness of these programs has spread, other science disciplines (including physics, biology, mathematics, and computer science) have adopted COACh programs with similar goals in mind. This article describes several opportunities that COACh is providing to help increase the number and success of women scientists in academia.

The need and potential for building a integrated knowledge-base of the Earth-Human system

NASA Astrophysics Data System (ADS)

Jacobs, Clifford

2011-03-01

The pursuit of scientific understanding is increasingly based on interdisciplinary research. To understand more deeply the planet and its interactions requires a progressively more holistic approach, exploring knowledge coming from all scientific and engineering disciplines including but not limited to, biology, chemistry, computer sciences, geosciences, material sciences, mathematics, physics, cyberinfrastucture, and social sciences. Nowhere is such an approach more critical than in the study of global climate change in which one of the major challenges is the development of next-generation Earth System Models that include coupled and interactive representations of ecosystems, agricultural working lands and forests, urban environments, biogeochemistry, atmospheric chemistry, ocean and atmospheric currents, the water cycle, land ice, and human activities.

Learning physical biology via modeling and simulation: A new course and textbook for science and engineering undergraduates

NASA Astrophysics Data System (ADS)

Nelson, Philip

To a large extent, undergraduate physical-science curricula remain firmly rooted in pencil-and-paper calculation, despite the fact that most research is done with computers. To a large extent, undergraduate life-science curricula remain firmly rooted in descriptive approaches, despite the fact that much current research involves quantitative modeling. Not only does our pedagogy not reflect current reality; it also creates a spurious barrier between the fields, reinforcing the narrow silos that prevent students from connecting them. I'll describe an intermediate-level course on ``Physical Models of Living Systems.'' The prerequisite is first-year university physics and calculus. The course is a response to rapidly growing interest among undergraduates in a broad range of science and engineering majors. Students acquire several research skills that are often not addressed in traditional undergraduate courses: •Basic modeling skills; •Probabilistic modeling skills; •Data analysis methods; •Computer programming using a general-purpose platform like MATLAB or Python; •Pulling datasets from the Web for analysis; •Data visualization; •Dynamical systems, particularly feedback control. Partially supported by the NSF under Grants EF-0928048 and DMR-0832802.

Cox process representation and inference for stochastic reaction-diffusion processes

NASA Astrophysics Data System (ADS)

Schnoerr, David; Grima, Ramon; Sanguinetti, Guido

2016-05-01

Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling.

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems.

PubMed

D'Onofrio, David J; Abel, David L; Johnson, Donald E

2012-03-14

The fields of molecular biology and computer science have cooperated over recent years to create a synergy between the cybernetic and biosemiotic relationship found in cellular genomics to that of information and language found in computational systems. Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called prescriptive information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms.

Towards big data science in the decade ahead from ten years of InCoB and the 1st ISCB-Asia Joint Conference

PubMed Central

2011-01-01

The 2011 International Conference on Bioinformatics (InCoB) conference, which is the annual scientific conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted by Kuala Lumpur, Malaysia, is co-organized with the first ISCB-Asia conference of the International Society for Computational Biology (ISCB). InCoB and the sequencing of the human genome are both celebrating their tenth anniversaries and InCoB’s goalposts for the next decade, implementing standards in bioinformatics and globally distributed computational networks, will be discussed and adopted at this conference. Of the 49 manuscripts (selected from 104 submissions) accepted to BMC Genomics and BMC Bioinformatics conference supplements, 24 are featured in this issue, covering software tools, genome/proteome analysis, systems biology (networks, pathways, bioimaging) and drug discovery and design. PMID:22372736

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

PubMed Central

Cai, Yizhi; Lux, Matthew W.; Adam, Laura; Peccoud, Jean

2009-01-01

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology. PMID:19816554

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.

Environmental Science Literacy in Science Education, Biology and Chemistry Majors.

ERIC Educational Resources Information Center

Robinson, Mike; Crowther, David

2001-01-01

Questions whether biology majors are more environmental science literate than chemistry majors, preservice science teachers, and a general population sample of 1,492 students. Indicates that preservice science teachers are significantly more environmental science literate than chemistry majors, but not more science literate than biology majors.…

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA

PubMed Central

Currin, Andrew; Korovin, Konstantin; Ababi, Maria; Roper, Katherine; Kell, Douglas B.; Day, Philip J.

2017-01-01

The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first physical design of an NUTM. This design is based on Thue string rewriting systems, and thereby avoids the limitations of most previous DNA computing schemes: all the computation is local (simple edits to strings) so there is no need for communication, and there is no need to order operations. The design exploits DNA's ability to replicate to execute an exponential number of computational paths in P time. Each Thue rewriting step is embodied in a DNA edit implemented using a novel combination of polymerase chain reactions and site-directed mutagenesis. We demonstrate that the design works using both computational modelling and in vitro molecular biology experimentation: the design is thermodynamically favourable, microprogramming can be used to encode arbitrary Thue rules, all classes of Thue rule can be implemented, and non-deterministic rule implementation. In an NUTM, the resource limitation is space, which contrasts with classical UTMs and QUTMs where it is time. This fundamental difference enables an NUTM to trade space for time, which is significant for both theoretical computer science and physics. It is also of practical importance, for to quote Richard Feynman ‘there's plenty of room at the bottom’. This means that a desktop DNA NUTM could potentially utilize more processors than all the electronic computers in the world combined, and thereby outperform the world's current fastest supercomputer, while consuming a tiny fraction of its energy. PMID:28250099

Exploring the role of pendant amines in transition metal complexes for the reduction of N2 to hydrazine and ammonia

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

Bhattacharya, Papri; Prokopchuk, Demyan E.; Mock, Michael T.

2017-03-01

This review examines the synthesis and acid reactivity of transition metal dinitrogen complexes bearing diphosphine ligands containing pendant amine groups in the second coordination sphere. This manuscript is a review of the work performed in the Center for Molecular Electrocatalysis. This work was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy (U.S. DOE), Office of Science, Office of Basic Energy Sciences. EPR studies on Fe were performed using EMSL, a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located atmore » PNNL. Computational resources were provided by the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Pacific Northwest National Laboratory is operated by Battelle for the U.S. DOE.« less

Basic energy sciences: Summary of accomplishments

NASA Astrophysics Data System (ADS)

1990-05-01

For more than four decades, the Department of Energy, including its predecessor agencies, has supported a program of basic research in nuclear- and energy related sciences, known as Basic Energy Sciences. The purpose of the program is to explore fundamental phenomena, create scientific knowledge, and provide unique user facilities necessary for conducting basic research. Its technical interests span the range of scientific disciplines: physical and biological sciences, geological sciences, engineering, mathematics, and computer sciences. Its products and facilities are essential to technology development in many of the more applied areas of the Department's energy, science, and national defense missions. The accomplishments of Basic Energy Sciences research are numerous and significant. Not only have they contributed to Departmental missions, but have aided significantly the development of technologies which now serve modern society daily in business, industry, science, and medicine. In a series of stories, this report highlights 22 accomplishments, selected because of their particularly noteworthy contributions to modern society. A full accounting of all the accomplishments would be voluminous. Detailed documentation of the research results can be found in many thousands of articles published in peer-reviewed technical literature.

Basic Energy Sciences: Summary of Accomplishments

DOE R&D Accomplishments Database

1990-05-01

For more than four decades, the Department of Energy, including its predecessor agencies, has supported a program of basic research in nuclear- and energy-related sciences, known as Basic Energy Sciences. The purpose of the program is to explore fundamental phenomena, create scientific knowledge, and provide unique user'' facilities necessary for conducting basic research. Its technical interests span the range of scientific disciplines: physical and biological sciences, geological sciences, engineering, mathematics, and computer sciences. Its products and facilities are essential to technology development in many of the more applied areas of the Department's energy, science, and national defense missions. The accomplishments of Basic Energy Sciences research are numerous and significant. Not only have they contributed to Departmental missions, but have aided significantly the development of technologies which now serve modern society daily in business, industry, science, and medicine. In a series of stories, this report highlights 22 accomplishments, selected because of their particularly noteworthy contributions to modern society. A full accounting of all the accomplishments would be voluminous. Detailed documentation of the research results can be found in many thousands of articles published in peer-reviewed technical literature.

CURRICULUM GUIDES IN BIOLOGY--LIFE SCIENCE, BIOLOGY--GENERAL, AND BIOLOGY--ADVANCED PLACEMENT.

ERIC Educational Resources Information Center

WESNER, GORDON E.; AND OTHERS

"BIOLOGY--LIFE SCIENCE" IS GEARED TO STUDENTS OF AVERAGE ABILITY, "BIOLOGY--GENERAL" IS OFFERED FOR THOSE WHO HAVE COMPLETED "BIOLOGY--GENERAL" IN GRADES 10 OR 11 AND WHO WISH TO PURSUE COLLEGE LEVEL STUDY WHILE IN GRADE 12. THE NONTECHNICAL "BIOLOGY--LIFE SCIENCE" HAS OUTLINED UNITS IN ORGANIZING FOOD,…

Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology.

PubMed

González-Nilo, Fernando; Pérez-Acle, Tomás; Guínez-Molinos, Sergio; Geraldo, Daniela A; Sandoval, Claudia; Yévenes, Alejandro; Santos, Leonardo S; Laurie, V Felipe; Mendoza, Hegaly; Cachau, Raúl E

2011-01-01

After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.

Genomics for Everyone

ScienceCinema

Chain, Patrick

2018-05-31

Genomics — the genetic mapping and DNA sequencing of sets of genes or the complete genomes of organisms, along with related genome analysis and database work — is emerging as one of the transformative sciences of the 21st century. But current bioinformatics tools are not accessible to most biological researchers. Now, a new computational and web-based tool called EDGE Bioinformatics is working to fulfill the promise of democratizing genomics.