Two-way clustering of gene expression profiles by sparse matrix factorization


We propose a new methodology for two-way cluster analysis of gene expression data using a novel sparse matrix factorization technique that produces a decomposition of a matrix in a set of sparse factors. This method produces a set of bases and coding matrices that are not only able to represent the original data, but they also extract important localized… (More)
DOI: 10.1109/CSBW.2005.137

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