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Mathematical Models in Biology (Classics in Applied Mathematics)

Posted on 2010-04-16




Name:Mathematical Models in Biology (Classics in Applied Mathematics)
ASIN/ISBN:0898715547
Author:Leah Edelstein-Keshet
Publisher:SIAM: Society for Industrial and Applied Mathematics (2005)
Pages:Paperback, 586 pages
   Mathematical Models in Biology (Classics in Applied Mathematics)

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Author: Leah Edelstein-Keshet


Publisher: SIAM: Society for Industrial and Applied Mathematics (2005)


Binding: Paperback, 586 pages


pricer: $54.50


ISBN-10: 0898715547


editorialreviews

Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community since its first publication in 1988, the book shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in Mathematical Models in Biology are still important and informative. Shortly after the first publication of Mathematical Models in Biology, the genomics revolution turned Mathematical Biology into a prominent area of interdisciplinary research. In this new millennium, biologists have discovered that mathematics is not only useful, but indispensable! As a result, there has been much resurgent interest in, and a huge expansion of, the fields collectively called mathematical biology. This book serves as a basic introduction to concepts in deterministic biological modeling. Mathematical Models in Biology does not assume too much background knowledgeessentially some calculus and high-school algebra. It was originally written with third- and fourth-year undergraduate mathematical-biology majors in mind; however, it was picked up by beginning graduate students as well as a number of researchers in math (and some in biology) who wanted to learn about this field.




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