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Discriminative mining of gene microarray data
- Source :
- Scopus-Elsevier, Experts@Minnesota
- Publication Year :
- 2002
- Publisher :
- IEEE, 2002.
-
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.
Details
- Database :
- OpenAIRE
- Journal :
- Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584)
- Accession number :
- edsair.doi.dedup.....afe8fbbc2fcc6dc7c12c0173bf06b149
- Full Text :
- https://doi.org/10.1109/nnsp.2001.943107