A Course in Mathematical Biology：Quantitative Modeling with Mathematical and Computational Methods

“There really is not a book that is directly comparable. Students will be able to study any area of biology with a mathematical perspective. The projects and the introduction to computation are a real bonus.” Fred Brauer, Department of Mathematics, University of British Columbia."It would be fun to teach from this book. It covers all the basics and has very nice extra features, including stochastic models, cellular automata, project suggestions, and a Maple tutorial. Highly recommended." — Leah Edelstein-Keshet, University of British Columbia.The field of mathematical biology is growing rapidly. Questions about infectious diseases, heart attacks, cell signaling, cell movement, ecology, environmental changes, and genomics are now being analyzed using mathematical and computational methods. A Course in Mathematical Biology: Quantitative Modeling with Mathematical and Computational Methods teaches all aspects of modern mathematical modeling and is specifically designed to introduce undergraduate students to problem solving in the context of biology.Divided into three parts, the book covers basic analytical modeling techniques and model validation methods; introduces computational tools used in the modeling of biological problems; and provides a source of open-ended problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, and there are many exercises related to biological questions. In addition, the book includes 25 open-ended research projects that can be used by students. The book is accompanied by a Web site that contains solutions to most of the exercises and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MatlabR. Audience Intended for upper level undergraduate students in mathematics or similar quantitative sciences, A Course in Mathematical Biology: Quantitative Modeling with Mathematical and Computational Methods is also appropriate for beginning graduate students in biology, medicine, ecology, and other sciences. It will also be of interest to researchers entering the field of mathematical biology. Contents Preface; Part I: Theoretical Modeling Tools. Chapter 1: Introduction; Chapter 2: Discrete-Time Models; Chapter 3: Ordinary Differential Equations; Chapter 4: Partial Differential Equations; Chapter 5: Stochastic Models; Chapter 6: Cellular Automata and Related Models; Chapter 7: Estimating Parameters; Part II: Self-Guided Computer Tutorial. Chapter 8: Maple Course; Part III: Projects. Chapter 9: Project Descriptions; Chapter 10: Solved Projects; Appendix: Further Reading; Bibliography; Author Index; Index.

Gerda de Vries is Associate Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, Canada.Thomas Hillen is Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, Canada.Mark Lewis is Professor and Senior Canada Research Chair in Mathematical Biology in the Department of Mathematical and Statistical Sciences and the Department of Biological Sciences at the University of Alberta, Canada.Johannes Muller is Professor of Mathematical Methods in Molecular Biology and Biochemistry in the Center for Mathematical Sciences at the Technical University Munich, Germany.Birgitt Schonfisch is a Scientific Employee in the Department of Medical Biometry at the University of Tubingen, Germany.