Discriminative mining of gene microarray data

Author

Lu, Jianping ; Wang, Yue ; Wang, Zuyi ; Xuan, Jianhua ; Kung, San Yuan ; Gu, Zhiping ; Clarke, Robert

Author_Institution

Catholic Univ. of America, Washington, DC, USA

fYear

2001

fDate

2001

Firstpage

23

Lastpage

32

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

Keywords

biocomputing; data mining; evolutionary computation; cluster discovery; data clusters; data mining; gene expression; sample clusters; spotted cDNA microarrays; statistical modeling; visual pyramid; Costs; Data mining; Gene expression; Large-scale systems; Standards development;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop

Conference_Location

North Falmouth, MA

ISSN

1089-3555

Print_ISBN

0-7803-7196-8

Type

conf

DOI

10.1109/NNSP.2001.943107

Filename

943107