Korenberg Microarray Data Analysis

Methods and Applications
Erscheinungsjahr 2008
ISBN: 978-1-59745-390-5
Verlag: Humana Press
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 377, 273 Seiten, eBook

Reihe: Methods in Molecular Biology

In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. Included in this innovative book includes are in-depth looks intopresentations 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 sprofiles 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 genomes analysis using tiling arrays, acomparative 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 predicting survival prediction in follicular lymphoma using tissue microarrays.The protocols 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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Korenberg, Michael J.

Inhaltsverzeichnis

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.