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Overview
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. Also detailed is the use of tiling arrays for large genomes analysis.
The prools follow the successful Methods in Molecular Biology™ series format, offering step-by-step instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.
Synopsis
In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. This innovative book includes in-depth presentations of genomic signal processing, artificial neural network use for microarray data analysis, signal processing and design of microarray time series experiments, application of regression methods, gene expression profiles and prognostic markers for primary breast cancer, and factors affecting the cross-correlation of gene expression profiles. Also detailed are use of tiling arrays for large genome analysis, comparative genomic hybridization data on cDNA microarrays, integrated high-resolution genome-wide analysis of gene dosage and gene expression in human brain tumors, gene and MeSH ontology, and survival prediction in follicular lymphoma using tissue microarrays. The protocols follow the successful Methods in Molecular Biology[Trademark] series format, offering step-by-step instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.
Features: 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 of 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 avoidknown pitfalls.