  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.
