A Practical Approach to Microarray Data Analysis

Editors: Berrar, Daniel P., Dubitzky, Werner, Granzow, Martin (Eds.)

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About this Textbook

In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.

Table of contents (20 chapters)

  • Introduction to Microarray Data Analysis

    Dubitzky, Werner (et al.)

    Pages 1-46

  • Data Pre-Processing Issues in Microarray Analysis

    Tinker, Nicholas A. (et al.)

    Pages 47-64

  • Missing Value Estimation

    Troyanskaya, Olga G. (et al.)

    Pages 65-75

  • Normalization

    Morrison, Norman (et al.)

    Pages 76-90

  • Singular Value Decomposition and Principal Component Analysis

    Wall, Michael E. (et al.)

    Pages 91-109

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-0-306-47815-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $185.00
price for USA
  • ISBN 978-1-4020-7260-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $185.00
price for USA
  • ISBN 978-1-4757-7809-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
A Practical Approach to Microarray Data Analysis
Editors
  • Daniel P. Berrar
  • Werner Dubitzky
  • Martin Granzow
Copyright
2003
Publisher
Springer US
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-0-306-47815-4
DOI
10.1007/b101875
Hardcover ISBN
978-1-4020-7260-4
Softcover ISBN
978-1-4757-7809-0
Edition Number
1
Number of Pages
XVI, 368
Topics