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ABSTRACT: Spotted cDNA microarrays are emerging as a cost effective tool for
the large scale analysis of gene expression. To reveal the patterns of
genes expressed within a specific cell essentially responsible for its
phenotype, this paper reports our progress in cluster discovery using a
newly developed data mining method. The discussion entails: (1)
statistical modeling of gene microarray data with a standard finite
normal mixture distribution, (2) development of a joint supervised and
unsupervised discriminative mining to discover sample clusters in a
visual pyramid, and (3) evaluation of the data clusters produced by such
scheme with phenotype-known microarray experiments
Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop; 02/2001
