Computational Biomathematics: Building and Simulating Models with Code

Computational biomathematics sits at the intersection of biology, mathematics, and computer science. This book teaches you how to translate biological systems into working computational models and simulate them using code.

You will learn to:

• Build mathematical representations of biological processes (population dynamics, reaction networks, epidemiological models, ecological systems, and more)
• Implement models in Python from first principles
• Run deterministic and stochastic simulations
• Analyze, visualize, and validate simulation results
• Handle common challenges such as parameter estimation, sensitivity analysis, and model scaling

Each chapter combines clear mathematical derivation with practical, well-commented code examples that you can run, modify, and extend immediately. The focus is on understanding the modeling process rather than any single software package or black-box tool.

Whether you are a biologist seeking to add quantitative rigor, a mathematician or computer scientist exploring biological applications, or a student in computational biology, bioinformatics, or systems biology, this book provides a solid foundation for turning conceptual models into testable, simulatable code.

No prior experience in scientific computing is assumed beyond basic Python familiarity. All necessary numerical methods and biological context are introduced as needed.

Ideal for researchers, graduate students, and advanced undergraduates who want to move beyond theory and start building and experimenting with biological models in code.