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Introduction to Mathematical Biology: Modeling, Analysis, and Simulations

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This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies.  The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations.  In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience.

The second set of case studies were adapted from recent and current research papers to the level of the students.  Topics have been selected based on public health interest.  This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis.  Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research.

Considered to be the undergraduate companion to the more advanced book "Mathematical Modeling of Biological Processes" (A. Friedman, C.-Y. Kao, Springer – 2014), this book is geared towards undergraduate students with little background in mathematics and no biological background.

Authors: Friedman Avner, Chou Ching Shan
Publisher: SPRINGER
Pages: 172
ISBN: 9783319296364
Cover: Hardback
Edition Number: 1
Release Year: 2016

Avner Friedman is a Distinguished University Professor at Ohio State University.  He received his Ph.D. in 1956 from the Hebrew University.  His research interests include partial differential equations, both general mathematical theory as well as applications to models that arise in the physical and life sciences, in engineering, and in industry.

Ching-Shan Chou is an Associate Professor in the Department of Mathematics at Ohio State University.  She received her Ph.D. in the area of applied mathematics from Brown University.  She is currently working in the area of computational and mathematical biology.

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