In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. Information on an array of topics is included in this innovative book including in-depth insights into presentations of genomic signal processing.

Information on an array of topics including genomic signal processing, matrix algebra and genetic networks, predictive models of gene regulation, comparing microarray studies, identifying progression-associated genes in astrocytoma, analysis of comparative genomic hybridization data on cDNA microarrays, statistical framework for gene expression analysis, and interpretation ingof microarray results with gene ontology and MeSH ontology Use classic, novel, and state-of-the-art methods in a readily reproducible format Master tricks of the trade, troubleshoot, and avoid known pitfalls

Inhalt
Microarray Data Analysis.- Genomic Signal Processing: From Matrix Algebra to Genetic Networks.- Online Analysis of Microarray Data Using Artificial Neural Networks.- Signal Processing and the Design of Microarray Time-Series Experiments.- Predictive Models of Gene Regulation.- Statistical Framework for Gene Expression Data Analysis.- Gene Expression Profiles and Prognostic Markers for Primary Breast Cancer.- Comparing Microarray Studies.- A Pitfall in Series of Microarrays.- In-Depth Query of Large Genomes Using Tiling Arrays.- Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays.- Integrated High-Resolution Genome-Wide Analysis of Gene Dosage and Gene Expression in Human Brain Tumors.- Progression-Associated Genes in Astrocytoma Identified by Novel Microarray Gene Expression Data Reanalysis.- Interpreting Microarray Results With Gene Ontology and MeSH.- Incorporation of Gene Ontology Annotations to Enhance Microarray Data Analysis.- Predicting Survival in Follicular Lymphoma Using Tissue Microarrays.