Related books on 'computational-biology'
Return to life science book listNumber of products: 757
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publisher: Academic Press, published: 2005-11-08 ASIN: 012088786X EAN: 9780120887866 sales rank: 809702 Systems Biology is concerned with the quantitative study of complex biosystems at the molecular, cellular, tissue, and systems scales. Its focus is on the function of the system as a whole, rather than on individual parts. This exciting new arena applies mathematical modeling and engineering methods to the study of biological systems. This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches. The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Central themes include strategies for predicting biological properties and methods for elucidating structure-function relationships. |
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publisher: CRC Press, published: 2010-05-04 ASIN: 1439811857 EAN: 9781439811856 sales rank: 673365 The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation methods to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorigenesis, cancer researchers can uncover a series of new discoveries and biological insights. The First Cancer Systems Biology Book Designed for Computational and Experimental Biologists Includes Contributions from more than 30 International Experts Cancer systems biology is still in its infancy as a field of study, but it is fast becoming indispensable in the battle to defeat cancer and develop successful new treatments. Cancer Systems Biology marks an important step toward reaching that goal. |
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by: D.S. Jones publisher: Chapman and Hall/CRC, published: 2009-11-09 ASIN: 1420083570 EAN: 9781420083576 sales rank: 326096 Deepen students’ understanding of biological phenomena Suitable for courses on differential equations with applications to mathematical biology or as an introduction to mathematical biology, Differential Equations and Mathematical Biology, Second Edition introduces students in the physical, mathematical, and biological sciences to fundamental modeling and analytical techniques used to understand biological phenomena. In this edition, many of the chapters have been expanded to include new and topical material. New to the Second Edition
This textbook shows how first-order ordinary differential equations (ODEs) are used to model the growth of a population, the administration of drugs, and the mechanism by which living cells divide. The authors present linear ODEs with constant coefficients, extend the theory to systems of equations, model biological phenomena, and offer solutions to first-order autonomous systems of nonlinear differential equations using the Poincaré phase plane. They also analyze the heartbeat, nerve impulse transmission, chemical reactions, and predator–prey problems. After covering partial differential equations and evolutionary equations, the book discusses diffusion processes, the theory of bifurcation, and chaotic behavior. It concludes with problems of tumor growth and the spread of infectious diseases. |
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by: Dominik Wodarz publisher: World Scientific Publishing Company, published: 2005-04 ASIN: 9812560270 EAN: 9789812560278 sales rank: 394964 The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of cells, genetic instability, and angiogenesis. The book also discusses the use of mathematical models for the analysis of therapeutic approaches such as chemotherapy, immunotherapy, and the use of oncolytic viruses. |
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by: Michael S. Waterman publisher: Chapman and Hall/CRC, published: 1995-06-01 ASIN: 0412993910 EAN: 9780412993916 sales rank: 950957 Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences.Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology. |
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publisher: The MIT Press, published: 2010-02-28 ASIN: 026201386X EAN: 9780262013864 sales rank: 765923 Computational systems biology aims to develop algorithms that uncover the structure and parameterization of the underlying mechanistic model—in other words, to answer specific questions about the underlying mechanisms of a biological system—in a process that can be thought of as learning or inference. This volume offers state-of-the-art perspectives from computational biology, statistics, modeling, and machine learning on new methodologies for learning and inference in biological networks. The chapters offer practical approaches to biological inference problems ranging from genome-wide inference of genetic regulation to pathway-specific studies. Both deterministic models (based on ordinary differential equations) and stochastic models (which anticipate the increasing availability of data from small populations of cells) are considered. Several chapters emphasize Bayesian inference, so the editors have included an introduction to the philosophy of the Bayesian approach and an overview of current work on Bayesian inference. Taken together, the methods discussed by the experts in Learning and Inference in Computational Systems Biology provide a foundation upon which the next decade of research in systems biology can be built. Contributors: Florence d'Alch e-Buc, John Angus, Matthew J. Beal, Nicholas Brunel, Ben Calderhead, Pei Gao, Mark Girolami, Andrew Golightly, Dirk Husmeier, Johannes Jaeger, Neil D. Lawrence, Juan Li, Kuang Lin, Pedro Mendes, Nicholas A. M. Monk, Eric Mjolsness, Manfred Opper, Claudia Rangel, Magnus Rattray, Andreas Ruttor, Guido Sanguinetti, Michalis Titsias, Vladislav Vyshemirsky, David L. Wild, Darren Wilkinson, Guy Yosiphon Computational Molecular Biology series |
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by: Pavel A. Pevzner publisher: The MIT Press, published: 2000-08-21 ASIN: 0262161974 EAN: 9780262161978 sales rank: 401965 In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial "computational biology without formulas" component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science. Computational Molecular Biology series Computer science and mathematics are transforming molecular biology from an informational to a computational science. Drawing on computational, statistical, experimental, and technological methods, the new discipline of computational molecular biology is dramatically increasing the discovery of new technologies and tools for molecular biology. The new MIT Press Computational Molecular Biology series provides a unique venue for the rapid publication of monographs, textbooks, edited collections, reference works, and lecture notes of the highest quality. |
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by: Daniel A. Beard publisher: Cambridge University Press, published: 2008-07-07 ASIN: 0521870704 EAN: 9780521870702 sales rank: 647052 Chemical Biophysics provides an engineering-based approach to biochemical system analysis for graduate-level courses on systems biology, computational bioengineering and molecular biophysics. It is the first textbook to apply rigorous physical chemistry principles to mathematical and computational modeling of biochemical systems for an interdisciplinary audience. The book is structured to show the student the basic biophysical concepts before applying this theory to computational modeling and analysis, building up to advanced topics and current research. Topics explored include the kinetics of nonequilibrium open biological systems, enzyme mediated reactions, metabolic networks, biological transport processes, large-scale biochemical networks and stochastic processes in biochemical systems. End-of-chapter exercises range from confidence-building calculations to computational simulation projects. |
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by: Oleg Demin publisher: Chapman and Hall/CRC, published: 2008-10-24 ASIN: 1584886676 EAN: 9781584886679 sales rank: 728881 With more and more interest in how components of biological systems interact, it is important to understand the various aspects of systems biology. Kinetic Modelling in Systems Biology focuses on one of the main pillars in the future development of systems biology. It explores both the methods and applications of kinetic modeling in this emerging field. The book introduces the basic biological cellular network concepts in the context of cellular functioning, explains the main aspects of the Edinburgh Pathway Editor (EPE) software package, and discusses the process of constructing and verifying kinetic models. It presents the features, user interface, and examples of DBSolve as well as the principles of modeling individual enzymes and transporters. The authors describe how to construct kinetic models of intracellular systems on the basis of models of individual enzymes. They also illustrate how to apply the principles of kinetic modeling to collect all available information on the energy metabolism of whole organelles, construct a kinetic model, and predict the response of the organelle to changes in external conditions. The final chapter focuses on applications of kinetic modeling in biotechnology and biomedicine. Encouraging readers to think about future challenges, this book will help them understand the kinetic modeling approach and how to apply it to solve real-life problems.
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by: Torsten Schwede publisher: World Scientific Publishing Company, published: 2008-09-02 ASIN: 9812778772 EAN: 9789812778772 sales rank: 1059970 Computational structural biology has made tremendous progress over the last two decades, and this book provides a recent and broad overview of such computational methods in structural biology. It covers the impact of computational structural biology on protein structure prediction methods, macromolecular function and protein design, and key methods in drug discovery. It also addresses the computational challenges of experimental approaches in structural biology. In addition to reviewing the current state of computational structural biology, each chapter ends with a brief, visionary discussion on the future outlook, whereby the main challenges for the coming years are elucidated. Written by an international panel of expert contributors, this book can serve as a reference manual for students and practitioners alike. Contents: Structure Prediction and Assessment Methods: Protein Fold Recognition and Threading (L J McGuffin); Assessment of Protein Structure Predictions (E Capriotti & M A Marti-Renom); From Structure to Function to Design: Evolution of Protein Folds (A N Lupas & K K Koretke); Atomistic Simulations of Reactions and Transition States (M Meuwly); Protein Protein Interactions and Aggregation Processes (R I Dima); Drug Discovery and Pharmacology: MD-Based Free Energy Simulations (M A Cuendet et al.); Structure-Based Computational Approaches to Drug Metabolism (M A Lill); New Frontiers in Experimental Methods: New Frontiers in X-ray Crystallography (C U Stirnimann & M G Grütter); New Frontiers in Characterizing Structure and Dynamics by NMR (M Nilges et al.); Selected Topics: Docking for Neglected Diseases as Community Efforts (M Podvinec et al.); Protein Structure Databases (M John et al.); Molecular Graphics in Structural Biology (A M Lesk et al.); and other chapters. |