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As biology increasingly depends on data, algorithms, and models, it has become necessary to use a computing language, such as the user-friendly MATLAB, to focus more on building and analyzing models as opposed to configuring tedious calculations. Explorations of Mathematical Models in Biology with MATLAB provides an introduction to model creation using MATLAB, followed by the translation, analysis, interpretation, and observation of the models.
With an integrated and interdisciplinary approach that embeds mathematical modeling into biological applications, the book illustrates numerous applications of mathematical techniques within biology, ecology, and environmental sciences. Featuring a quantitative, computational, and mathematical approach, the book includes:
Explorations of Mathematical Models in Biology with MATLAB is an ideal textbook for upper-undergraduate courses in mathematical models in biology, theoretical ecology, bioeconomics, forensic science, applied mathematics, and environmental science. The book is also an excellent reference for biologists, ecologists, mathematicians, biomathematicians, and environmental and resource economists.
MAZEN SHAHIN, PhD, is Professor in the Department of Mathematical Sciences at Delaware State University. He has extensive background and experience in designing interdisciplinary instructional materials that integrate mathematics and other disciplines, such as biology, ecology, and finance. Dr. Shahin's research interests include boundary value problems, dynamical systems, impulsive differential equations, and mathematics education.
Chapter 1
Introduction to Modeling and Difference Equations
The Modeling Process
Getting Started with MATLAB
Chapter 2
2.1 Modeling with First-order Linear Homogenous Difference Equations With Constant Coefficients
2.2 Modeling with Non-Homogenous First-order Linear Difference Equations
2.3 Modeling with Nonlinear Difference Equations: Logistic Growth Models
2.4 Logistic Equations and Chaos
Chapter 3
3.1 Systems of Linear Equations Having Unique Solutions
3.2 The Gauss-Jordan Elimination Method with Models
3.3 Introduction to Matrices
3.4 Determinants and Systems of Linear Equations
3.5 Eigenvalues and Eigenvectors
3.6 Eigenvalues and Stability of Linear Models
Chapter 4
4.1 Modeling with Markov Chains
4.2 Age Structured Population Models
4.3 Modeling with Second-order Linear Difference Equations
Chapter 5 Modeling with Nonlinear Systems of Difference Equations
5.1 Modeling of Interacting Species
5.2 The SIR Model of Infectious Disease
5.3 Modeling with Second-order Nonlinear Difference Equations
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