With worked examples and end-of-chapter exercises, this book provides a basic understanding of problems arising in the analysis of genetics and genomics and presents statistical applications in genetic mapping, DNA/protein sequence alignment, and analyses of gene expression data from microarray experiments. It covers basic molecular biology, likelihood-based statistics, physical mapping, markers, linkage analysis, parametric and nonparametric linkage, sequence alignment, feature recognition, hidden Markov models, and Bayesian approaches. It also discusses differential gene expression detection as well as classification and cluster analysis using gene expression data sets.
