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.
journal_name
Genome Resjournal_title
Genome researchauthors
Heyer LJ,Kruglyak S,Yooseph Sdoi
10.1101/gr.9.11.1106subject
Has Abstractpub_date
1999-11-01 00:00:00pages
1106-15issue
11eissn
1088-9051issn
1549-5469journal_volume
9pub_type
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