Stochastic processes in genetics and evolution : computer experiments in the quantification of mutation and selection / Charles J. Mode, Candace K. Sleeman.

Format:

Book

Author/Creator:

Mode, Charles J.

Contributor:

Sleeman, Candace K.

Language:

English

Subjects (All):

Genetics--Mathematical models.

Genetics.

Evolution (Biology)--Mathematical models.

Evolution (Biology).

Stochastic processes.

Physical Description:

1 online resource (695 p.)

Place of Publication:

Hackensack, N.J. : World Scientific, 2012.

Language Note:

English

Summary:

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

Contents:

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

Example 1.5.2: Offspring From a Mating of Type Aa AaExample 1.5.3: Observing at Least One Mutation with High Probability; 1.6 The Multinomial Distribution; Example 1.6.1: A,B,AB and O Blood Types - Matings of Type AB AB; Example 1.6.2: Sex and Blood Types in Mating of Type ABXX ABXY; 1.7 Conditional Probabilities and a Bayesian Theorem; Example 1.7.1: Natural Selection with Respect to One Autosomal Locus with Two Alleles; 1.8 Expectations and Generating Functions for Binomial and Multinomial Distributions; 1.9 Marginal and Conditional Distributions of the Multinomial Distribution

1.10 A Law of Large Numbers and the Frequency Interpretation of Probability1.11 On Computing Monte Carlo Realizations of a Random Variable with a Binomial Distribution; 1.12 The Beta-Binomial Distribution; Example 1.12.1: Empirical Distribution of the Number of Boys in German Families with 8 Children; Bibliography; 2. Linkage and Recombination at Multiple Loci; 2.1 Introduction; 2.2 Some Thoughts on Constructing Databases of DNA Markers From Sequenced Genomes of Relatives; 2.3 Examples of Informative Matings for the Case of Two Loci; 2.4 General Case of Two Linked Loci

2.5 General Case of Three Linked Loci2.6 General Case of Four or More Linked Loci; 2.7 Theoretical Calculations in Statistical and Population Genetics; 2.8 Appendix: Proof of Theorem 2.6.1; Bibliography; 3. Linkage and Recombination in Large Random Mating Diploid PopulationsRandom Mating Diploid Populations; 3.1 Introduction; 3.2 The One Locus Case; Definition 3.2.1: The population is said to mate at random in generation n if, and only if

Theorem 3.3.4: If in the initial generation

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

9786613646408

9781280669477

1280669470

9789814350686

9814350680

OCLC:

785777973