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	A DSRPCL-SVM approach to informative gene analysis
	Xiong Wei ; Cai Zhibin ; Ma Jinwen
	2008
英文摘要	Microarray data based tumor diagnosis is a very interesting topic in bioinformatics. One of the key problems is the discovery and analysis of informative genes of a tumor. Although there are many elaborate approaches to this problem, it is still difficult to select a reasonable set of informative genes for tumor diagnosis only with microarray data. In this paper, we classify the genes expressed through microarray data into a number of clusters via the distance sensitive rival penalized competitive learning (DSRPCL) algorithm and then detect the informative gene cluster or set with the help of support vector machine (SVM). Moreover, the critical or powerful informative genes can be found through further classifications and detections on the obtained informative gene clusters. It is well demonstrated by experiments on the colon, leukemia, and breast cancer datasets that our proposed DSRPCL-SVM approach leads to a reasonable selection of informative genes for tumor diagnosis.; PubMed; 中国科学引文数据库(CSCD); 0; 2; 83-90; 6
语种	英语
出处	PubMed
出版者	genomics proteomics bioinformatics
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/197721]
专题	数学科学学院
推荐引用方式 GB/T 7714	Xiong Wei,Cai Zhibin,Ma Jinwen. A DSRPCL-SVM approach to informative gene analysis. 2008-01-01.

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