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Modeling Biological Systems

Principles and Applications

  • James W. Haefner

Table of contents

  1. Front Matter
    Pages i-xix
  2. Principles

    1. Front Matter
      Pages 1-1
    2. James W. Haefner
      Pages 3-15
    3. James W. Haefner
      Pages 16-30
    4. James W. Haefner
      Pages 31-56
    5. James W. Haefner
      Pages 57-100
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      Pages 101-117
    7. James W. Haefner
      Pages 118-132
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      Pages 133-150
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      Pages 151-178
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      Pages 179-211
    11. James W. Haefner
      Pages 212-229
  3. Applications

    1. Front Matter
      Pages 231-231
    2. James W. Haefner
      Pages 233-256
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      Pages 257-268
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      Pages 269-292
    5. James W. Haefner
      Pages 293-305
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    7. James W. Haefner
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    9. James W. Haefner
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    10. James W. Haefner
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    11. James W. Haefner
      Pages 424-437
  4. Back Matter
    Pages 439-473

About this book

Introduction

This book is intended as a text for a first course on creating and analyzing computer simulation models of biological systems. The expected audience for this book are students wishing to use dynamic models to interpret real data mueh as they would use standard statistical techniques. It is meant to provide both the essential principles as well as the details and equa­ tions applicable to a few particular systems and subdisciplines. Biological systems, however, encompass a vast, diverse array of topics and problems. This book discusses only a select number of these that I have found to be useful and interesting to biologists just beginning their appreciation of computer simulation. The examples chosen span classical mathematical models of well-studied systems to state-of-the-art topics such as cellular automata and artificial life. I have stressed the relationship between the models and the biology over mathematical analysis in order to give the reader a sense that mathematical models really are useful to biologists. In this light, I have sought examples that address fundamental and, I think, interesting biological questions. Almost all of the models are directly COIIl­ pared to quantitative data to provide at least a partial demonstration that some biological models can accurately predict.

Keywords

biology evolution mammals plant plant growth population

Authors and affiliations

  • James W. Haefner
    • 1
  1. 1.Utah State UniversityUSA

Bibliographic information