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...
| Main Author: | |
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| Other Authors: | |
| Format: | Book |
| Language: | English |
| Published: |
Hackensack, N.J. :
World Scientific,
2012
Singapore ; Hackensack, NJ : c2012 |
| Subjects: |
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| 100 | 1 | |a Mode, Charles J |1 http://viaf.org/viaf/85154734 | |
| 100 | 1 | |a Mode, Charles J |? UNAUTHORIZED | |
| 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 | ||
| 260 | |a Singapore ; |a Hackensack, NJ : |b World Scientific, |c c2012 | ||
| 300 | |a 1 online resource (xxviii, 666 pages) : |b illustrations | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index | ||
| 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 | |
| 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 | ||
| 588 | |a Description based on online resource; title from digital title page (viewed on February 20, 2012) | ||
| 596 | |a 22 | ||
| 650 | 0 | |a Evolution (Biology) |x Mathematical models | |
| 650 | 0 | |a Genetics |x Mathematical models | |
| 650 | 0 | |a Genetics | |
| 650 | 0 | |a Natural selection | |
| 650 | 0 | |a Stochastic processes | |
| 650 | 7 | |a Evolution (Biology) |x Mathematical models |2 fast | |
| 650 | 7 | |a Genetics |x Mathematical models |2 fast | |
| 650 | 7 | |a MATHEMATICS |x Linear & Nonlinear Programming |2 bisacsh | |
| 650 | 7 | |a Stochastic processes |2 fast | |
| 655 | 0 | |a Electronic books | |
| 655 | 4 | |a Electronic books | |
| 700 | 1 | |a Sleeman, Candace K | |
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