Digital Genomes : Monte Carlo Simulations of Microbes and Evolution

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Digital Genomes : Monte Carlo Simulations of Microbes and Evolution

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  • Wiley（2026/02発売）
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  • 製本 Paperback:紙装版/ペーパーバック版／ページ数 288 p.
  • 言語 ENG
  • 商品コード 9781394314614

Full Description

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.

Contents

List of Algorithms xi
List of Figures xiii
List of Tables xvii
About the Author xix
Preface xxi
Acknowledgments xxiii

1 Introduction and Overview 1
1.1 Microbial Evolution 1
1.2 Probability by Simulation 2
1.3 A Learner's Guide 3

Part I Foundational Algorithms 9

2 Digital Genomes 11
2.1 Random DNA Sequences 12
2.2 DNA Replication and Transcription 13
2.3 Genetic Code and DNA Translation 14

3 Digital Populations 21
3.1 Quantifying Genetic Diversity 22
3.2 Genetic Drift 27
3.3 Mutation 28
3.4 Recombination 30
3.5 Natural Selection 32
3.6 Trait-associated SNPs 36

4 Digital Species 41
4.1 Population Divergence 41
4.2 Species Divergence 44
4.3 Trait Evolution on a Tree: Binary Traits 46
4.4 Trait Evolution on a Tree: Quantitative Traits 48

5 Digital Life and Learning 53
5.1 Fitness Landscape 53
5.2 Fitness Ascent with Greedy and Genetic Algorithms 54
5.3 Open-ended Evolution with Novelty Search 56
5.4 Self-optimization with Hebbian Learning and Hopfield Networks 59
5.5 Foresighted Evolution with Perceptron 60
5.6 Artificial Life with Finite Automata 63
5.7 Case Study: Evolution-inspired Vaccine Designs 65

Part II Gene Evolution 71

6 Gene Frequencies as Genetic Information 73
6.1 Frequentist vs. Bayesian Paradigms 74
6.2 Case Study: Taster/Nontaster Gene Frequencies in New York City 75
6.3 Quantifying Genetic Information 77
6.4 Case Studies: Gene Frequencies of Lyme Bacteria in Eastern United States 83

7 Mendelian Genetics and Darwinian Selection 95
7.1 Neutral Evolution 95
7.2 Darwinian Selection 102
7.3 Frequency-dependent Selection 111

8 Stochastic Evolution with Genetic Drift 115
8.1 Forward- and Backward-evolution Simulations 116
8.2 Neutral DNA Polymorphisms 119
8.3 Case Study: Genetic Structures of Lyme Bacteria and Tick Vectors in the Eastern United States 127

Part III Genome Evolution 133

9 Recombination: Genomic Footprints 135
9.1 Four Gametes and Novel Haplotypes 136
9.2 Linkage Disequilibrium 139
9.3 Linkage Decay Over Distance and Time 140
9.4 Haplotype Diversity with Recombinants 143
9.5 Multilocus Allelic Association 146
9.6 Sequence of Trees 148
9.7 Case Studies: Recombination in Lyme Bacterial Populations 149

10 Recombination: Adaptive Consequences 155
10.1 Neutral and Nearly Neutral Mutations 156
10.2 Essentiality of Recombination and Sex 160
10.3 Linked Selection 163

11 Microbial Genome Clusters: Causes and Consequences 181
11.1 Clonality-sexuality Threshold 182
11.2 Selective Sweeps 184
11.3 Immune Selection 186
11.4 Genome-wide Association Studies in Bacteria 188

Exercises 192
Afterword 193
Bibliography 195
Index 211