An expert discussion of simulation-based approaches to teaching genome sciences
In Digital Genomes: Monte Carlo Simulations of Microbes and Evolution, distinguished researcher Weigang Qiu delivers a comprehensive exploration of the role of Monte Carlo simulations in understanding complex biological processes. Beginning with an introduction to microbial evolution, computer simulations, and evolutionary algorithms, the book moves on to explore the evolution of DNA sequences and concepts like neutral evolution, Mendelian inheritance, Darwinian natural selection, and genome evolution.
Qiu offers exercises to help readers retain the concepts discussed within, as well as links to open-source code on a complimentary companion website. Those links point to code that serves as a programming recipe for solving evolutionary problems that can be implemented in Python, Bash, R, and other popular programming languages.
Readers will also find:
- A thorough introduction to a new approach to teaching population genetics and evolution
- Comprehensive explorations of algorithm-centered, programming language-agnostic learning
- Practical exercises at the end of each chapter that clarify key concepts with guided application
- In-depth treatments of evolutionary mechanisms, like recombination, genetic linkage, balancing selection, genome evolution, bacterial clonality, and negative frequency-dependent selection
Perfect for senior undergraduate and graduate students studying population genetics, evolution, genetics, and bioinformatics, this book will also benefit researchers with an interest in evolutionary biology, genetics, microbiology, and virology.