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About this book
Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis focuses on two well-known data sets, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.
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Table of contents (13 chapters)
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Introduction
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Best Presentation — CAMDA ’00
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Quality Analysis and Data Normalization of Spotted Arrays
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Feature Selection, Dimension Reduction, and Discriminative Analysis
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Methods of Microarray Data Analysis
Book Subtitle: Papers from CAMDA ’00
Editors: Simon M. Lin, Kimberly F. Johnson
DOI: https://doi.org/10.1007/978-1-4615-0873-1
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2002
Hardcover ISBN: 978-0-7923-7564-7Published: 30 November 2001
Softcover ISBN: 978-1-4613-5281-5Published: 31 October 2012
eBook ISBN: 978-1-4615-0873-1Published: 06 December 2012
Edition Number: 1
Number of Pages: XIV, 189
Topics: Biochemistry, general, Human Genetics, Statistics for Life Sciences, Medicine, Health Sciences