DocumentCode
3259297
Title
Minimum Redundancy Gene Selection Based on Grey Relational Analysis
Author
Zhang, Li-Juan ; Li, Zhou-Jun ; Chen, Huo-Wang ; Wen, Jian
fYear
2006
fDate
Dec. 2006
Firstpage
120
Lastpage
124
Abstract
In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from these groups to avoid redundancy. A new gene similarity measure based on grey relational analysis (GRA), called grey relational grade (GRG), is used in clustering. Experiments on three public data sets demonstrate the effectiveness of our method
Keywords
genetics; grey systems; pattern clustering; gene similarity measure; grey relational analysis; grey relational grade; informative genes; microarray data; minimum redundancy gene selection; Computer science; Conferences; Data analysis; Data engineering; Data mining; Distributed processing; Gene expression; Laboratories; Mutual information; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2702-7
Type
conf
DOI
10.1109/ICDMW.2006.108
Filename
4063610
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