Quasispecies Equation and Classical Population Models

“This book is a welcome and timely addition to the existing literature on rigorous mathematical analysis of various genetics models, with a special focus on a careful understanding of the impact of stochastic effects. The book is written with the potential reader in mind, such that it is a real pleasure to read. It should be interesting to anyone working at the interface of mathematics and population genetics.” (Artem S. Novozhilov, Mathematical Reviews, August, 2023)“The text is written in an easy-to-read style and is suitable for use in various courses, including probability theory, Markov chains, mathematical ecology and population dynamics. The book can be expected to provide several ideas for further investigation of finite population models.” (Attila Dénes, zbMATH 1507.92072, 2023)

• 1. Introduction.- Part I.Finite Genotype Space.- 2. The Quasispecies equation.- 3. Non-Overlapping Generations.- 4. Overlapping Generations.- 5. Probabilistic Representations.- Part II. The Sharp Peak Landscape.- 6. Long Chain Regime.- 7. Error Threshold and Quasispecies.- 8. Probabilistic Derivation.- 9. Summation of the Series.- 10. Error Threshold in Infinite Populations.- Part III. Error Threshold in Finite Populations.- 11.Phase Transition.- 12. Computer Simulations.- 13. Heuristics.- 14. Shape of the Critical Curve.- 15. Framework for the Proofs.- Part IV. Proof for Wright-Fisher.- 16. Strategy of the Proof.- 17. The Non-Neutral Phase M.- 18. Mutation Dynamics.- 19. The Neutral Phase N.- 20. Synthesis.- Part V. Class-Dependent Fitness Landscapes.- 21. Generalized Quasispecies Distributions.- 22. Error Threshold.- 23. Probabilistic Representation.- 24. Probabilistic Interpretations.- 25. Infinite Population Models.- Part VI. A Glimpse at the Dynamics.- 26. Deterministic Level.- 27. From Finite to Infinite Population.- 28. Class-Dependent Landscapes.- A. Markov Chains and Classical Results.- References.- Index.