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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…mehr

Produktbeschreibung
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.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

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