Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010123667 | QH323.5 A44 2004 | Open Access Book | Book | Searching... |
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Summary
Summary
This introductory textbook on mathematical biology focuses on discrete models across a variety of biological subdisciplines. Biological topics treated include linear and non-linear models of populations, Markov models of molecular evolution, phylogenetic tree construction, genetics, and infectious disease models. The coverage of models of molecular evolution and phylogenetic tree construction from DNA sequence data is unique among books at this level. Computer investigations with MATLAB are incorporated throughout, in both exercises and more extensive projects, to give readers hands-on experience with the mathematical models developed. MATLAB programs accompany the text. Mathematical tools, such as matrix algebra, eigenvector analysis, and basic probability, are motivated by biological models and given self-contained developments, so that mathematical prerequisites are minimal.
Reviews 1
Choice Review
Allman (Univ. of Southern Maine) and Rhodes (Bates College) present an elementary introduction to mathematical difference-equation models in biology. The authors avoid discussions involving calculus or differential equations, and this may limit the book's appeal. Still, the work is well written; it includes basic, informal reviews of topics in linear algebra and probability and discusses linear (e.g., Malthusian population, molecular evolution) and nonlinear (predator-prey) models. Other topics include phylogenetic trees (evolutionary modeling), genetics, and infectious disease modeling. Many examples, both basic and more complicated; 61 references and suggested readings; 388 exercises; 18 suggested projects. ^BSumming Up: Highly recommended. Lower- and upper-division undergraduates. J. D. Fehribach Worcester Polytechnic Institute
Table of Contents
| 1 Dynamic modeling with different equations |
| 2 Linear models of structured populations |
| 3 Non-linear models of interactions |
| 4 Modeling molecular evolution |
| 5 Constructing phylogenic trees |
| 6 Genetics |
| 7 Infectious disease modeling |
| 8 Curve fitting and biological modeling |
| Appendix A Basic analysis of numerical data |
| Appendix B For further reading |
