The Analysis of Gene Expression Data: Methods and Software (Hardcover)

Introduction. - Visualization and annotation of genomic experiments. - Bioconductor R packages for exploratory data analysis and normalization of cDNA microarray data. - An R package for analyses of affymetrix oligonucleotide arrays. - DNA-Chip analyzer (d-Chip). - Expression Profiler. - An S-Plus library for the analysis of microarray data. - DRAGON and DRAGON View: Methods for the annotation, analysis, and visualization of large-scale gene expression data. - SNOMAD: User-friendly web tools for the standardization and normalization of microarry data. - Microarray analysis using the MicroArray Explorer. - Parametric empirical Bayes methods for microarrays. - SAM thresholding and false discovery rates for detecting differential gene expression in DNA microarrays. - Adaptive gene picking with microarray data: Detecting important low abundance signals. -MAANOVA: A software package for the analysis of spotted cDNA microarray experiments. - GeneClust. - POE Statistical Tools for molecular profiling. - Bayesian decomposition. - Cluster analysis of gene expression dynamics. - Relevance networks: A first step towards finding genetic regulatory networks within microarray data.