Coupled two-way clustering analysis of breast cancer and colon cancer gene expression data

Gad Getz, Hilah Gal, Itai Kela, Daniel A. Notterman, Eytan Domany

Research output: Contribution to journalReview articlepeer-review

52 Scopus citations

Abstract

We present and review coupled two-way clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis.

Original languageEnglish (US)
Pages (from-to)1079-1089
Number of pages11
JournalBioinformatics
Volume19
Issue number9
DOIs
StatePublished - Jun 12 2003

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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