Independent Subspaces of Gene Expression Data

H. Kim and S. Choi (Korea)

Keywords

DNA chip data, gene clustering, genegene interaction analysis, independent component analysis, independent subspace analysis.

Abstract

Independent subspace anlaysis (ISA) is a linear model based method which generalizes independent component analysis (ICA) by incorporating the invariant feature sub space into multidimensional ICA. In this paper we apply ISA to the problem of gene expression data analysis and show the useful behavior of the independent subspaces of gene expression data in the task of gene clustering and gene-gene interaction analysis.

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