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Table of contents (16 chapters)
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Front Matter
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Best Presentation Award
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Normalizing Raw Data
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Investigating Cross Hybridization on Oligonucleotide Microarrays
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Finding Patterns and Seeking Biological Explanations
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Back Matter
About this book
As microarray technology has matured, data analysis methods have advanced as well. Methods Of Microarray Data Analysis III is the third book in this pioneering series dedicated to the existing new field of microarrays. While initial techniques focused on classification exercises (volume I of this series), and later on pattern extraction (volume II of this series), this volume focuses on data quality issues. Problems such as background noise determination, analysis of variance, and errors in data handling are highlighted.
Three tutorial papers are presented to assist with a basic understanding of underlying principles in microarray data analysis, and twelve new papers are highlighted analyzing the same CAMDA'02 datasets: the Project Normal data set or the Affymetrix Latin Square data set. A comparative study of these analytical methodologies brings to light problems, solutions and new ideas. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of art of microarray data analysis.
Editors and Affiliations
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Cancer Center Information Systems, Duke University Medical Center, Durham
Kimberly F. Johnson
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Duke Bioinformatics Shared Resource, Duke University Medical Center, Durham
Simon M. Lin
About the editors
Bibliographic Information
Book Title: Methods of Microarray Data Analysis III
Book Subtitle: Papers from CAMDA ‘02
Editors: Kimberly F. Johnson, Simon M. Lin
DOI: https://doi.org/10.1007/b105346
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2003
Hardcover ISBN: 978-1-4020-7582-7Published: 30 September 2003
Softcover ISBN: 978-1-4757-8504-3Published: 05 May 2013
eBook ISBN: 978-0-306-48354-7Published: 08 May 2007
Edition Number: 1
Number of Pages: XI, 252
Number of Illustrations: 52 b/w illustrations, 1 illustrations in colour
Topics: Evolutionary Biology, Artificial Intelligence, Human Genetics, Physical Chemistry