Ebook: Modeling Biological Systems: Principles and Applications
Author: James W. Haefner (auth.)
- Tags: Ecology, Ecotoxicology, Zoology, Animal Systematics/Taxonomy/Biogeography
- Year: 1996
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
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.
Content:
Front Matter....Pages i-xix
Front Matter....Pages 1-1
Models of Systems....Pages 3-15
The Modeling Process....Pages 16-30
Qualitative Model Formulation....Pages 31-56
Quantitative Model Formulation....Pages 57-100
Simulation Paradigms....Pages 101-117
Numerical Techniques....Pages 118-132
Parameter Estimation....Pages 133-150
Model Validation....Pages 151-178
Model Analysis: Uncertainty and Behavior....Pages 179-211
Stochastic Models....Pages 212-229
Front Matter....Pages 231-231
Photosynthesis and Plant Growth....Pages 233-256
Hormonal Control in Mammals....Pages 257-268
Populations and Individuals....Pages 269-292
Chemostats....Pages 293-305
Spatial Patterns and Processes....Pages 306-324
Scaling Models....Pages 325-339
Chaos in Biology....Pages 340-376
Cellular Automata and Recursive Growth....Pages 377-400
Evolutionary Computation....Pages 401-423
Complex Adaptive Systems....Pages 424-437
Back Matter....Pages 439-473
Content:
Front Matter....Pages i-xix
Front Matter....Pages 1-1
Models of Systems....Pages 3-15
The Modeling Process....Pages 16-30
Qualitative Model Formulation....Pages 31-56
Quantitative Model Formulation....Pages 57-100
Simulation Paradigms....Pages 101-117
Numerical Techniques....Pages 118-132
Parameter Estimation....Pages 133-150
Model Validation....Pages 151-178
Model Analysis: Uncertainty and Behavior....Pages 179-211
Stochastic Models....Pages 212-229
Front Matter....Pages 231-231
Photosynthesis and Plant Growth....Pages 233-256
Hormonal Control in Mammals....Pages 257-268
Populations and Individuals....Pages 269-292
Chemostats....Pages 293-305
Spatial Patterns and Processes....Pages 306-324
Scaling Models....Pages 325-339
Chaos in Biology....Pages 340-376
Cellular Automata and Recursive Growth....Pages 377-400
Evolutionary Computation....Pages 401-423
Complex Adaptive Systems....Pages 424-437
Back Matter....Pages 439-473
....