
Mathematical Concepts and Methods in Modern Biology
Using Modern Discrete Models
by Raina Robeva
2nd Edition
Publisher: Academic Press
Book Details
| Print ISBN | 9780443296529 |
| eText ISBN | 9780443296536 |
| Publisher | Academic Press |
| Publishing Year | 2026 |
| Edition | 2nd Edition |
| Language | English |
| Pages | 446 |
Mathematical Concepts and Methods in Modern Biology, 2nd Edition, is a textbook that presents discrete mathematical models designed for investigating complex biological systems. The volume examines key biological topics including gene regulatory networks, neuronal networks, plant population growth, and interacting populations. Each chapter pairs biological scenarios with specific analytical methods to establish quantitative modeling skills.
Mathematical methods covered throughout the chapters include discrete dynamical systems, deterministic and stochastic Boolean networks, ordinary differential equations, and projection matrices. Students examine discrete models alongside traditional differential equation frameworks to evaluate dynamic biological behavior. These techniques allow readers to analyze systemic responses across genetic and ecological scales.
Structured around project-based learning and practical problem-solving, the text supports direct practice in analyzing, predicting, and modulating biological systems. The content is formatted to assist upper-level students in related fields, practicing scientists, and health professionals who require formal discrete mathematical approaches in their work.
Table of Contents
Chapter 1: Modeling gene regulation using Boolean network models
Chapter 2: Bistability in bacterial genetic networks: A comparison of differential equations and Boolean network models
Chapter 3: Inferring the topology of gene regulatory networks: An algebraic approach to reverse engineering
Chapter 4: Stochastic Boolean Networks
Chapter 5: Global dynamics emerging from local interactions: Agent-based modeling for the life sciences
Chapter 6: Agent-based models and optimal control in biology: A discrete approach
Chapter 7: Neuronal networks: A discrete model
Chapter 8: Predicting population growth: Modeling with projection matrices
Chapter 9: Identifying CpG islands: Sliding window and hidden Markov model approaches
Chapter 10: Phylogenetic tree reconstruction: Geometric approaches
Chapter 11: Tropical linear algebra and its applications to phylogenomics
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