Related books on 'computational-biology'
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by: G. Bard Ermentrout publisher: Springer, published: 2010-07-08 ASIN: 038787707X EAN: 9780387877075 sales rank: 330523 This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University. “This excellent 422 page hardcover publication is an accessible and concise monograph. … Mathematical Foundations is a timely contribution that will prove useful to mathematics graduate students and faculty interested in the application of dynamical systems theory to cellular and systems neuroscience. … welcome addition to the pedagogical literature. … For mathematics graduate students who are investigating the field of computational neuroscience, I would highly recommend Mathematical Foundations of Neuroscience as their first computational neuroscience text.” (Gregory D. Smith, The Mathematical Association of America, December, 2010) "...it is a good substitute for a lengthy regime of abstract maths classes, but it is also well integrated into the field of neuroscience. Ermentrout and Terman's book conveys much of the advanced mathematics used in theoretical neuroscience today." (Vincent A. Billock, Nature) |
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by: Stephen P. Ellner publisher: Princeton University Press, published: 2006-03-27 ASIN: 0691125899 EAN: 9780691125893 sales rank: 286135 From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering. |
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by: Bernhard Ø. Palsson publisher: Cambridge University Press, published: 2011-06-30 ASIN: 1107001595 EAN: 9781107001596 sales rank: 701353 Biophysical models have been used in biology for decades, but they have been limited in scope and size. In this book, Bernhard Ø. Palsson shows how network reconstructions that are based on genomic and bibliomic data, and take the form of established stoichiometric matrices, can be converted into dynamic models using metabolomic and fluxomic data. The Mass Action Stoichiometric Simulation (MASS) procedure can be used for any cellular process for which data is available and allows a scalable step-by-step approach to the practical construction of network models. Specifically, it can treat integrated processes that need explicit accounting of small molecules and protein, which allows simulation at the molecular level. The material has been class-tested by the author at both the undergraduate and graduate level. All computations in the text are available online in MATLAB and MATHEMATICA® workbooks, allowing hands-on practice with the material. |
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by: Aidong Zhang publisher: Cambridge University Press, published: 2009-04-06 ASIN: 0521888956 EAN: 9780521888950 sales rank: 789071 The analysis of protein-protein interactions is fundamental to the understanding of cellular organization, processes, and functions. Recent large-scale investigations of protein-protein interactions using such techniques as two-hybrid systems, mass spectrometry, and protein microarrays have enriched the available protein interaction data and facilitated the construction of integrated protein-protein interaction networks. The resulting large volume of protein-protein interaction data has posed a challenge to experimental investigation. This book provides a comprehensive understanding of the computational methods available for the analysis of protein-protein interaction networks. It offers an in-depth survey of a range of approaches, including statistical, topological, data-mining, and ontology-based methods. The author discusses the fundamental principles underlying each of these approaches and their respective benefits and drawbacks, and she offers suggestions for future research. |
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by: Satyan L. Devadoss publisher: Princeton University Press, published: 2011-04-11 ASIN: 0691145539 EAN: 9780691145532 sales rank: 196311 Discrete geometry is a relatively new development in pure mathematics, while computational geometry is an emerging area in applications-driven computer science. Their intermingling has yielded exciting advances in recent years, yet what has been lacking until now is an undergraduate textbook that bridges the gap between the two. Discrete and Computational Geometry offers a comprehensive yet accessible introduction to this cutting-edge frontier of mathematics and computer science. This book covers traditional topics such as convex hulls, triangulations, and Voronoi diagrams, as well as more recent subjects like pseudotriangulations, curve reconstruction, and locked chains. It also touches on more advanced material, including Dehn invariants, associahedra, quasigeodesics, Morse theory, and the recent resolution of the Poincar conjecture. Connections to real-world applications are made throughout, and algorithms are presented independently of any programming language. This richly illustrated textbook also features numerous exercises and unsolved problems.
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by: Peter Clote publisher: Wiley, published: 2000-09-22 ASIN: 0471872520 EAN: 9780471872528 sales rank: 1318996 Recently molecular biology has undergone unprecedented development generating vast quantities of data needing sophisticated computational methods for analysis, processing and archiving. This requirement has given birth to the truly interdisciplinary field of computational biology, or bioinformatics, a subject reliant on both theoretical and practical contributions from statistics, mathematics, computer science and biology. * Provides the background mathematics required to understand why certain algorithms work * Guides the reader through probability theory, entropy and combinatorial optimization * In-depth coverage of molecular biology and protein structure prediction * Includes several less familiar algorithms such as DNA segmentation, quartet puzzling and DNA strand separation prediction * Includes class tested exercises useful for self-study * Source code of programs available on a Web site Primarily aimed at advanced undergraduate and graduate students from bioinformatics, computer science, statistics, mathematics and the biological sciences, this text will also interest researchers from these fields. |
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by: Marek Kimmel publisher: Springer, published: 2010-12-01 ASIN: 1441929584 EAN: 9781441929587 sales rank: 3834157 This book introduces biological examples of Branching Processes from molecular and cellular biology as well as from the fields of human evolution and medicine and discusses them in the context of the relevant mathematics. It provides a useful introduction to how the modeling can be done and for what types of problems branching processes can be used. |
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by: Forbes J. Burkowski publisher: Chapman and Hall/CRC, published: 2012-02-15 ASIN: 1439836612 EAN: 9781439836613 This book emphasizes computer programs that analyze protein structural data with program output generating data files and visual feedback in the form of a molecular display. The theoretical part of the text considers both the mathematical models related to molecular structure and the computational strategies that work with these models to derive results. The practical part of the text presents UCSF Chimera as a "workbench" that provides a Python programming environment and the ability to see program output in the molecular display. The accompanying CD-ROM includes Python code, color figures, and session files for Chimera. |
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publisher: Chapman and Hall/CRC, published: 2012-07-15 ASIN: 1439839832 EAN: 9781439839836 Translational bioinformatics is an emerging research field at the intersection of bioinformatics and clinical medicine. This book bridges the gaps among basic bioinformatics research, clinical informatics applications, and informatics practices in the biopharmaceutical and health management industries. It features the latest knowledge discovery advances while providing an interdisciplinary overview of translational bioinformatics concepts, techniques, and practices. Written by expert researchers, the text covers such fundamental concepts as applied systems biomedicine, computational diagnostics, integrative biomedical informatics, and predictive pharmacology. |
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by: Paul M.K. Gordon publisher: Chapman and Hall/CRC, published: 2012-05-15 ASIN: 1439841179 EAN: 9781439841174 From individual tools to genome analysis, this book provides an overview of annotation strategies and toolkits currently in use. Presenting a combination of principles and practice, the authors elucidate database search engines and HTML-based annotation systems for specialists in computational biology and bioinformatics who use genome annotation in their work. They also introduce web service-based annotation pipelines. The text includes a CD-ROM with MAGPIE and Bluejay, genome annotation systems and viewers that are used in thousands of laboratories around the world. |