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Theoretical Models in ­Biology
The Origin of Life, the Immune System, and the Brain

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Format
Paperback, 440 pages
Published
United Kingdom, 1 January 1998

This book surveys theoretical models in three broad areas of biology (the origin of life, the immune system, and memory in the brain), introducing mathematical and (mainly) computational models that have been used to construct simulations. Most current books on theoretical biology fall into one of two categories: (a) books that specialize in one area of biology and treat theoretical models in considerable depth; and (b) books that concentrate on purely mathematical models, with computers used only to find numerical solutions to differential equations, for example. Although some mathmatical models are considered in this book, the main emphasis is on stochastic computer modles of biological systems. Such techniques have a much greater potential for producting detailed, realistic models of individual systems, and are likely to be the preferred modelling methods of the future. By considering three different areas in biology, the book shows how several of these modelling techniques have been successfully applied in diverse areas.
Put simply, this book is important becuase it shows how the power of modern computers is allowing researchers in theoretical biology to break free of the constraints on modelling that were imposed by the traditional differential equation approach. Anyone who is interested in the theoretical models of complicated living systems should have this in his or her library. G. B. Ermentrout, Bulletin of Mathematical Biology


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Product Description

This book surveys theoretical models in three broad areas of biology (the origin of life, the immune system, and memory in the brain), introducing mathematical and (mainly) computational models that have been used to construct simulations. Most current books on theoretical biology fall into one of two categories: (a) books that specialize in one area of biology and treat theoretical models in considerable depth; and (b) books that concentrate on purely mathematical models, with computers used only to find numerical solutions to differential equations, for example. Although some mathmatical models are considered in this book, the main emphasis is on stochastic computer modles of biological systems. Such techniques have a much greater potential for producting detailed, realistic models of individual systems, and are likely to be the preferred modelling methods of the future. By considering three different areas in biology, the book shows how several of these modelling techniques have been successfully applied in diverse areas.
Put simply, this book is important becuase it shows how the power of modern computers is allowing researchers in theoretical biology to break free of the constraints on modelling that were imposed by the traditional differential equation approach. Anyone who is interested in the theoretical models of complicated living systems should have this in his or her library. G. B. Ermentrout, Bulletin of Mathematical Biology

Product Details
EAN
9780198596875
ISBN
0198596871
Publisher
Other Information
Illustrated
Dimensions
23.5 x 15.3 x 2.4 centimeters (0.67 kg)

Table of Contents

I. The Origin of Life
1: The molecular basis of life
2: Molecular evolution and quasi-species
3: Stochastic processes
4: A spin glass model of the origin of life
5: The origin of the genetic code
6: Hypercycles
7: Artificial life
II. The Immune System
8: The immune system
9: Bell's model
10: Adaptive walks
11: Maturation of the immune response
12: The symmetric immune network model
13: A shape space network model
14: AIDS
III. The Brain
15: Neurons and synapses
16: Memory
17: The McCulloch-Pitts neural net
18: Perceptrons
19: Connectionism
20: Attractor neural networks
21: Unsupervised learning
22: Evolutionary learning
A. Differential equations
C. Computer simulation
Bibliography
Index

About the Author

Dr G. W. Rowe, Department of Mathematics and Computer Science, University of Dundee, Dundee, DD1 4HN

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`Anyone who is interested in the theoretical models of complicated living systems should have this in his or her library.' Bulletin of Mathematical Biology

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