Small 4to 9" - 11" tall; 189 pages; Glossy Illustrated Boards, No Dust Jacket, Book Tight, Text is clean no markings seen Page 14 manufacturing defect Page was cut at wrong angle; BX260.

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Bibliographic Details

Title: Methods of Microarray Data Analysis Papers from CAMDA '00
Publisher: Kluwer Academic Publishers, Boston, MA
Publication Date: 2001
Language: English
ISBN 10: 0792375645
ISBN 13: 9780792375647
Binding: Hardcover
Edition: 2nd Printing.
Condition: Very Good

About this title

Synopsis

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis is one of the first books dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods ranging from data normalization, feature selection and discriminative analysis to machine learning techniques.
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.

About the Author

Simon M. Lin is Manager of Duke Bioinformatics Shared Resource, Duke University Medical Center. Kimberly F. Johnson is Director of Duke Cancer Center Information Systems and Director of Duke Bioinformatics Shared Resource, Duke University Medical Center.

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