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Discriminative mining of gene microarray data

Authors :
Jianhua Xuan
San Yuan Kung
Zuyi Wang
Zhiping Gu
Jianping Lu
Robert Clarke
Yue Wang
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