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Microarray Data Analysis

Methods and Applications

Series: Methods in Molecular Biology

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by Michael J. Korenberg

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Main description:

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.

Feature:

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

Contents:

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 Suárez-Fariñas and Marcelo O. Magnasco

Chapter 9
A Pitfall in Series of Microarrays: The Position of Probes Affects the Cross Correlation of Gene Expression Profiles
Gábor Balázsi and Zoltán 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 JamesLyons-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

PRODUCT DETAILS

ISBN-13: 9781627039093
Publisher: Springer (Humana Press)
Publication date: October, 2014
Pages: 288
Weight: 444g
Availability: Not available (reason unspecified)
Subcategories: Biochemistry, Genetics

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