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Biological Modeling and Simulation: A Survey of Practical Models, Algorithms, and Numerical Methods (Computational Molecular Biology)

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Synopses & Reviews

Publisher Comments:

andlt;Pandgt;There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.andlt;/Pandgt;

Synopsis:

A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems.

Synopsis:

andlt;Pandgt;A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems.andlt;/Pandgt;

Synopsis:

There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

About the Author

Russell Schwartz is Associate Professor in the Department of Biological Sciences at Carnegie Mellon University.

Product Details

ISBN:
9780262195843
Subtitle:
A Survey of Practical Models, Algorithms, and Numerical Methods
Author:
Schwartz, Russell
Publisher:
The MIT Press
Location:
Cambridge
Subject:
Biology
Subject:
Simulation methods
Subject:
Life Sciences - Biology - General
Subject:
Data Modeling & Design
Subject:
Research -- Methodology.
Subject:
Applied
Subject:
Bioinformatics
Subject:
Biology -- Mathematical models.
Subject:
Biology -- Simulation methods.
Subject:
Science Reference-General
Series:
Computational Molecular Biology Biological Modeling and Simulation
Publication Date:
20080725
Binding:
Hardback
Grade Level:
Professional and scholarly
Language:
English
Illustrations:
111 figures, 5 tables
Pages:
408
Dimensions:
9 x 7 x 0.6875 in
Age Level:
from 18

Related Subjects

Computers and Internet » Computers Reference » Bioinformatics
Computers and Internet » Database » Design
Engineering » Engineering » General Engineering
Reference » Science Reference » General
Science and Mathematics » Biology » General
Science and Mathematics » Mathematics » Applied

Biological Modeling and Simulation: A Survey of Practical Models, Algorithms, and Numerical Methods (Computational Molecular Biology) New Hardcover
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Product details 408 pages MIT Press (MA) - English 9780262195843 Reviews:
"Synopsis" by , A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems.
"Synopsis" by , andlt;Pandgt;A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems.andlt;/Pandgt;
"Synopsis" by , There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.
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