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Mathematical Models in Biology (Classics in Applied Mathematics), by Leah Edelstein-Keshet
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Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. Connections are made between diverse biological examples linked by common mathematical themes, exploring a variety of discrete and continuous ordinary and partial differential equation models. 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.
- Sales Rank: #211632 in Books
- Brand: Brand: SIAM: Society for Industrial and Applied Mathematics
- Published on: 2005-02
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x 1.26" w x 5.98" l, 2.20 pounds
- Binding: Paperback
- 586 pages
- Used Book in Good Condition
About the Author
Leah Edelstein-Keshet is a Professor in the Department of Mathematics at the University of British Columbia, Vancouver, Canada. Her book Mathematical Models in Biology was republished in SIAM's Classics in Applied Mathematics series.
Most helpful customer reviews
35 of 37 people found the following review helpful.
The very BEST book on the subject
By A Customer
There are lots of books about mathematical modeling, and many of them cover biological systems. But no book I've ever seen even comes close to the quality of this beautiful work by Edelstein-Keshet. So what is it that makes this book so special? First of all, the book is both accessible and self-contained. Just start at the beginning, and you're guaranteed to learn A LOT of math. Second, the style of writing and the way in which the author presents the material is utterly beautiful. It is impossible NOT to understand, but the material is not at all 'chewed out' for the reader. Third of all, the book really encourages the reader to pick up pen and paper, go out there and MODEL something; dozens of inspiring and high-quality exercises and research projects are to be found throughout the book. Fourth, the various techniques are easily applied to non-biological problems. Fifth, the book will help to gain insight in the qualitative aspects of biological phenomena. What Peter Atkins is to chemistry, Edelstein-Keshet is to mathematical biology. Sadly, she is not as widely known. Get this book while you can!
13 of 13 people found the following review helpful.
math models in biology
By V. Davide
This is a nice introductory book on math biology models. It is easy to understand and a necessary reading for those who want to approach more difficult books such as Mathematical Physiology. The exercises presented are useful for active learning of this topic.
Be aware: this book requires prior knowledge of calculus (differential equations, partial derivatives, Taylor series expansion...).
11 of 13 people found the following review helpful.
Classic textbook, with some flaws
By T. Glimm
A classic textbook in mathematical biology, and still one of the best I know. It is a testament to the quality of this book that many other textbooks that have been published after it essentially follow the template of this book.
No other book does a better job at explaining clearly and concisely the biological background. The tone is precise and approachable without being aloof.
There are two flaws about this book: One is the mathematical exposition, which is sometimes simply wrong. (The whole section about the Hopf bifurcation is very poor, and I couldn't use this section in classes I taught. It has to be supplemented by other textbooks.) The other, related, flaw is the flood of typos. This is the text with the most typos I've ever seen. (The latest errata list has 16 pages, and there are still many unlisted typos.) And this is the second edition! Normally typos don't bother me too much, but there are so many here that it truly becomes a nuisance.
Overall, though, this is a good textbook. I wish the author would decide to update the text and clean up the typos and some of the math sections.
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