Modeling Biological Systems

1. Front Matter

   Pages i-xix

   PDF

2. Principles

   1. Front Matter

      Pages 1-1

      PDF

   2. Models of Systems

      • James W. Haefner

      Pages 3-15

   3. The Modeling Process

      • James W. Haefner

      Pages 16-30

   4. Qualitative Model Formulation

      • James W. Haefner

      Pages 31-56

   5. Quantitative Model Formulation

      • James W. Haefner

      Pages 57-100

   6. Simulation Paradigms

      • James W. Haefner

      Pages 101-117

   7. Numerical Techniques

      • James W. Haefner

      Pages 118-132

   8. Parameter Estimation

      • James W. Haefner

      Pages 133-150

   9. Model Validation

      • James W. Haefner

      Pages 151-178

   10. Model Analysis: Uncertainty and Behavior

       • James W. Haefner

       Pages 179-211

   11. Stochastic Models

       • James W. Haefner

       Pages 212-229

3. Applications

   1. Front Matter

      Pages 231-231

      PDF

   2. Photosynthesis and Plant Growth

      • James W. Haefner

      Pages 233-256

   3. Hormonal Control in Mammals

      • James W. Haefner

      Pages 257-268

   4. Populations and Individuals

      • James W. Haefner

      Pages 269-292

   5. Chemostats

      • James W. Haefner

      Pages 293-305

   6. Spatial Patterns and Processes

      • James W. Haefner

      Pages 306-324

   7. Scaling Models

      • James W. Haefner

      Pages 325-339

   8. Chaos in Biology

      • James W. Haefner

      Pages 340-376

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.

• biology
• evolution
• mammals
• plant
• plant growth
• population
• ecotoxicology

Throughout the book, the author aims to teach the concepts of mathematical modelling by example, allowing a full understanding of how and why mathematics is so important in biology. This is a superb introduction and complements the more technical literature... - The Biologist;
Covers a broad area with wit and enthusiasm, tempered with an appropriate degree of caution...a valuable introduction...a balanced selection of references makes this a handy source text for those seeking to learn more. - Journal of Animal Ecology;
The book will be useful for those readers who want to get a survey of the use of various types of models in biology. - Eur. Jnl. of Entomology, 1997;
This is an excellent book for the student who wants a mathematical model but does not know how to construct one - Journal of Experimental Marine Biology and Ecology.

• Utah State University, USA

  James W. Haefner

Policies and ethics