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	Minimum redundancy gene selection based on grey relational analysis
	Zhang, Li-Juan ; Li, Zhou-Jun ; Chen, Huo-Wang ; Wen, Jian
	2006
关键词	EXPRESSION CLASSIFICATION PREDICTION CANCER
英文摘要	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.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000245603100023&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Information Systems; CPCI-S(ISTP); 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/386125]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Li-Juan,Li, Zhou-Jun,Chen, Huo-Wang,et al. Minimum redundancy gene selection based on grey relational analysis. 2006-01-01.

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