Reference: Heyer LJ, et al. (1999) Exploring expression data: identification and analysis of coexpressed genes. Genome Res 9(11):1106-15

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Abstract

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.

Reference Type
Journal Article | Review | Research Support, Non-U.S. Gov't | Research Support, U.S. Gov't, Non-P.H.S. | Research Support, U.S. Gov't, P.H.S.
Authors
Heyer LJ, Kruglyak S, Yooseph S
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Interactor Interactor Type Assay Annotation Action Modification Phenotype Source Reference

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Gene Gene Ontology Term Qualifier Aspect Method Evidence Source Assigned On Annotation Extension Reference

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