Mathematical Concepts and Methods in Modern Biology book cover

Mathematical Concepts and Methods in Modern Biology

Using Modern Discrete Models

Mathematical Concepts and Methods in Modern Biology offers a quantitative framework for analyzing, predicting, and modulating the behavior of complex biological systems. The book presents important mathematical concepts, methods and tools in the context of essential questions raised in modern biology.

Designed around the principles of project-based learning and problem-solving, the book considers biological topics such as neuronal networks, plant population growth, metabolic pathways, and phylogenetic tree reconstruction. The mathematical modeling tools brought to bear on these topics include Boolean and ordinary differential equations, projection matrices, agent-based modeling and several algebraic approaches. Heavy computation in some of the examples is eased by the use of freely available open-source software.


Researchers, educators, and students engaged in Biological Research and Mathematics

Hardbound, 372 Pages

Published: January 2013

Imprint: Academic Press

ISBN: 978-0-12-415780-4


  • "Contributors in biology, in mathematics, and in bioinformatics introduce undergraduate students and their instructors to more applications of discrete mathematics to biology than can be found in standard textbooks. The goal is not to be comprehensive, but to open the door to more advanced and specialized resources."--Reference and Research Book News, August 2013


  • Preface by Raina Robeva and Terrell Hodge
    Chapter 1. Mechanisms for Gene Regulation: A Boolean Network Model of the Lac Operon
    Chapter 2. Epigenetic Features of the Lac Operon: Comparing Boolean and Ordinary Differential Equations Models
    Chapter 3. Inferring the Topology of Gene Regulatory Networks: An Algebraic Approach to Reverse Engineering
    Chapter 4. Global Dynamics Emerging from Local Interactions: Agent-based Modeling for the Life Sciences
    Chapter 5. Agent-based Models and Optimal Control in Biology: An Algebraic Approach
    Chapter 6. Neuronal Networks: A Discrete Model
    Chapter 7. Predicting Plant Population Growth: Modeling with Projection Matrices
    Chapter 8. Metabolic Pathways Analysis: A Linear Algebraic Approach
    Chapter 9. Identifying CpG Islands: Sliding Windows and Hidden Markov Models
    Chapter 10. Codon Usage: From Elementary Probability to Algebraic Geometry
    Chapter 11. Phylogenetic Tree Reconstruction: Geometric Approaches


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