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Stochastic processes in genetics and evolution : computer experiments in the quantification of mutation and selection /
The scope of this book is the field of evolutionary genetics. The book contains new methods for simulating evolution at the genomic level. It sets out applications using up to date Monte Carlo simulation methods applied in classical population genetics, and sets out new fields of quantifying mutatio...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hackensack, N.J. :
World Scientific,
2012.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Mode, Charles J. | |
| 245 | 1 | 0 | |a Stochastic processes in genetics and evolution : |b computer experiments in the quantification of mutation and selection / |c Charles J. Mode, Candace K. Sleeman. |
| 260 | |a Hackensack, N.J. : |b World Scientific, |c 2012. | ||
| 300 | |a 1 online resource (xxviii, 666 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a The scope of this book is the field of evolutionary genetics. The book contains new methods for simulating evolution at the genomic level. It sets out applications using up to date Monte Carlo simulation methods applied in classical population genetics, and sets out new fields of quantifying mutation and selection at the Mendelian level. A serious limitation of Wright-Fisher process, the assumption that population size is constant, motivated the introduction of self regulating branching processes in this book. While providing a short review of the principles of probability and its application. | ||
| 505 | 0 | |a Prologue; Acknowledgments; Contents; 1. An Introduction to Mathematical Probability with Applications in Mendelian Genetics; 1.1 Introduction; 1.2 Mathematical Probability in Mendelian Genetics; 1.3 Examples of Finite Probability Spaces; Example 1.3.1: An Equal Frequency Model; Example 1.3.2: Partitions of an Abstract Set; Example 1.3.3: A Deterministic Case; Example 1.3.4: Inheritance of Eye Color and Sex; 1.4 Elementary Combinatorial Analysis; 1.5 The Binomial Distribution; Example 1.5.1: Distribution of Boys and Girls in Families of Size N. | |
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| 650 | 0 | |a Genetics |x Mathematical models. | |
| 650 | 0 | |a Evolution (Biology) |x Mathematical models. | |
| 650 | 0 | |a Stochastic processes. | |
| 650 | 6 | |a Processus stochastiques. | |
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| 650 | 7 | |a Genetics |x Mathematical models |2 fast | |
| 650 | 7 | |a Stochastic processes |2 fast | |
| 700 | 1 | |a Sleeman, Candace K. | |
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| 776 | 0 | 8 | |i Print version |z 9789814350679 |
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