Overview

Focusing on the roles of different segments of DNA, Statistics in Human Genetics and Molecular Biology provides a basic understanding of problems arising in the analysis of genetics and genomics. It presents statistical applications in genetic mapping, DNA/protein sequence alignment, and analyses of gene expression data from microarray experiments. The text introduces a diverse set of problems and a number of approaches that have been used to address these problems. It discusses basic molecular biology and likelihood-based statistics, along with physical mapping, markers, linkage analysis, parametric and nonparametric linkage, sequence alignment, and feature recognition. The text illustrates the use of methods that are widespread among researchers who analyze genomic data, such as hidden Markov models and the extreme value distribution. It also covers differential gene expression detection as well as classification and cluster analysis using gene expression data sets. Ideal for graduate students in statistics, biostatistics, computer science, and related fields in applied mathematics, this text presents various approaches to help students solve problems at the interface of these areas.

Full Product Details

Author:   Cavan Reilly ,  Chris Chatfield (University of Bath, UK) ,  Bradley. P. Carlin (University of Minnesota, Minneapolis, Minnesota, USA) ,  Martin A. Tanner (Northwestern University, Evanston, Illinois, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Volume:   v. 82
Dimensions:   Width: 15.60cm , Height: 2.00cm , Length: 23.40cm
Weight:   0.544kg
ISBN:  

9781420072631

ISBN 10:   1420072633
Pages:   280
Publication Date:   19 June 2009
Audience:   College/higher education ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Basic Molecular Biology for Statistical Genetics and Genomics. Basics of Likelihood-Based Statistics. Markers and Physical Mapping. Basic Linkage Analysis. Extensions of the Basic Model for Parametric Linkage. Nonparametric Linkage and Association Analysis. Sequence Alignment. Significance of Alignments and Alignment in Practice. Hidden Markov Models. Feature Recognition in Biopolymers. Multiple Alignment and Sequence Feature Discovery. Statistical Genomics. Detecting Differential Expression. Cluster Analysis in Genomics. Classification in Genomics. References. Index.

Reviews

Thankfully, some brave souls are willing to serve as guides to rigorous application and understanding of statistical approaches to genetically informative data. Cavan Reilly is among them. ! The book is self-contained and well organized, covering a substantial breadth of the core topics in genetics and genomics. ! this book is a valuable reference source for both statistics-oriented and human-genetics-oriented researchers and graduate students to learn the specialized methodology for analysis of diverse genetic data. ! a useful textbook for beginners trained in applied mathematics and statistics to take in a panoramic snapshot of the very evolving field of statistical genetics and genomics. --Xiang-Yang Lou and David B. Allison, Biometrics, December 2011 Very useful for those taking courses in statistics and geneticists. --Pediatric Endocrinology Reviews, Vol. 7, No. 4, June 2010

Very useful for those taking courses in statistics and geneticists. --Pediatric Endocrinology Reviews, Vol. 7, No. 4, June 2010

Author Information

Cavan Reilly is associate professor of biostatistics at the University of Minnesota.

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