Models in Biology: Mathematics, Statistics and Computing

About this book

Includes discussion of deterministic vs random, linear vs non-linear and dynamic vs time-independent models. Tables, figs. A supplement to this is also available, with diskette, to be used to implement the statistical analyses and to simulate the biological models presented.

Contents

MODELS FOR SINGLE POPULATIONS AND PROCESSES; Deterministic Models of Growth and Decline; Deterministic Genetic Models; Stochastic Models of Genetic, Environmental and Sampling Variation; Structured Stochastic Models: Models with Both Deterministic and Stochastic Elements; Fitting Models: Constants, Straight Lines, Polynomials and Non-Linear Models; BIOLOGICAL COMPARISONS AND DESIGN ISSUES; Statistical Methods for Comparing Biological Populations and Processes; Sampling, Controlling and Measuring the Random and Systematic Variation: Design of Experiments and Surveys; BIOLOGICAL INTERACTIONS; The Mathematics of Interaction; Biochemistry and Physiology; Ecology and Epidemiology; Advanced Model Fitting; ADVANCED TOPICS; Transport and Diffusion; Statistical Analysis of Pattern and Sequence: Temporal and Spatial Series and DNA Sequences; Descriptive Models of Complex Relationships: Multiple Regression and Response Surface Models; Models of the Brain: Neural Networks; GLOSSARY, TABLES, REFERENCES AND INDEX; Mathematical Glossary; Statistical Tables; References; Index.

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