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Microarray Data Analysis: Methods and Applications

Handbook / Manual

Series: Methods in Molecular Biology Volume: 377

Edited By: Michael Korenberg

Humana Press

Hardback | Jan 2007 | #163656 | ISBN-13: 9781588295408
Availability: Usually dispatched within 1-2 weeks Details
NHBS Price: £109.99 $144/€125 approx

About this book

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 BiologyT 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.


Table of Contents; Chapter 1; Microarray Data Analysis: An Overview of Design, Methodology and Analysis; Ashani T. Weeraratna and Dennis D. Taub; Chapter 2; Genomic Signal Processing: From Matrix Algebra to Genetic Networks; Orly Alter; Chapter 3; Online Analysis of Microarray Data Using Artificial Neural Networks; Braden Greer and Javed Khan; Chapter 4; Signal Processing and the Design of Microarray Time Series Experiments; Robert R. Klevecz, Caroline M. Li and James L. Bolen; Chapter 5; Predictive Models of Gene Regulation: Application of Regression Methods to Microarray Data; Debopriya Das and Michael Q. Zhang; Chapter 6; Statistical Framework for Gene Expression Data Analysis; Olga Modlich and Marc Munnes; Chapter 7; Gene Expression Profiles and Prognostic Markers for Primary Breast Cancer; Yixin Wang, Jan Kljin, Yi Zhang, David Atkins and John Foekens; Chapter 8; Comparing microarray studies; Mayte Suarez-Farinas and Marcelo O. Magnasco; Chapter 9; A Pitfall in Series of Microarrays: The Position of Probes Affects the Cross Correlation of Gene Expression Profiles; Gabor Balazsi and Zoltan N. Oltvai; Chapter 10; In Depth Query of Large Genomes using Tiling Arrays; Manoj Pratim Samanta, Waraporn Tongprasit and Viktor Stolc; Chapter 11; Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays; Sven Bilke and Javed Khan; Chapter 12; Integrated high-resolution genome-wide analysis of gene dosage and gene expression in human brain tumors; Dejan Juric, Claudia Bredel, Branimir I. Sikic, and Markus Bredel. Chapter 13; Progression-Associated Genes in Astrocytoma Identified by Novel Microarray Gene Expression Data Reanalysis; Tobey J. MacDonald, Ian F. Pollack, Hideho Okada, Soumyaroop Bhattacharya, and James Lyons-Weiler; Chapter 14; Interpreting Microarray Results with Gene Ontology and MeSH Ontology; John D. Osborne, Lihua (Julie) Zhu, Simon M. Lin, and Warren A. Kibbe; Chapter 15; Incorporation of Gene Ontology Annotations to Enhance Microarray Data Analysis; Michael F. Ochs, Aidan J. Peterson, Andrew Kossenkov, and Ghislain Bidaut; Chapter 16; Predicting Survival in Follicular Lymphoma using Tissue Microarrays; Michael J. Korenberg, Pedro Farinha, and Randy D. Gascoyne.

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