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Vol. 9, Issue 11, 1106-1115, November 1999

METHODS
Exploring Expression Data: Identification and Analysis of Coexpressed Genes

Laurie J. Heyer,1 Semyon Kruglyak,1,2 and Shibu Yooseph1

Department of Mathematics, University of Southern California, California USA

Analysis procedures are needed to extract useful information from the large amount of gene expression data that is becoming available. This work describes a set of analytical tools and their application to yeast cell cycle data. The components of our approach are (1) a similarity measure that reduces the number of false positives, (2) a new clustering algorithm designed specifically for grouping gene expression patterns, and (3) an interactive graphical cluster analysis tool that allows user feedback and validation. We use the clusters generated by our algorithm to summarize genome-wide expression and to initiate supervised clustering of genes into biologically meaningful groups.

1 The authors contributed equally to this work and are listed in alphabetical order.

2 Corresponding author.

9:1106-1115 ©1999 by Cold Spring Harbor Laboratory Press  ISSN 1088-9051/99 $5.00
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