Discriminative mining of gene microarray data

Jianping Lu, Yue Wang, Zuyi Wang, Jianhua Xuan, Sun-Yuan Kung, Zhiping Gu, Robert Clarke

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Pages23-32
Number of pages10
StatePublished - Dec 1 2001

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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