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


BACKGROUND
Free, at http://ctwc.weizmann.ac.il..


BACKGROUND
http://www.weizmann.ac.il/physics/complex/compphys/bioinfo2/
Getz
Gad
G
Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel.
Gal
Hilah
H
Kela
Itai
I
Notterman
Daniel A
DA
Domany
Eytan
E
D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D016000:Cluster Analysis; D003110:Colonic Neoplasms / Q000235:genetics*; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity