Statistics in Human Genetics and Molecular Biology

1. Auflage 2009
ISBN: 978-1-4200-7263-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 280 Seiten, Format (B × H): 162 mm x 245 mm, Gewicht: 542 g

Reihe: Chapman & Hall/CRC Texts in Statistical Science

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.

Zielgruppe

Undergraduate

Autoren/Hrsg.

Reilly, Cavan

Fachgebiete

• Naturwissenschaften Biowissenschaften Proteinforschung
• Naturwissenschaften Biowissenschaften Botanik Pflanzenreproduktion, Verbreitung, Genetik
• Naturwissenschaften Biowissenschaften Molekularbiologie
• Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
• Naturwissenschaften Biowissenschaften Tierkunde / Zoologie Tiergenetik, Reproduktion
• Naturwissenschaften Biowissenschaften Humanbiologie

Inhaltsverzeichnis

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.

Über Autor(innen)

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