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	The application of feature selection methods to analyze the tissue microarray data
	Lin, Weipeng ; Liu, Kunhong ; Liu, Guoyan ; Liu KH(刘昆宏) ; Liu GY(刘国彦)
	2011
关键词	Artificial intelligence Data reduction Genes
英文摘要	Conference Name:4th International Workshop on Advanced Computational Intelligence, IWACI 2011. Conference Address: Wuhan, Hubei, China. Time:October 19, 2011 - October 21, 2011.; In this paper, two feature selection methods, binary genetic algorithm (GA) and sequential floating forward selection (SFFS), were deployed to analyze tissue microarray dataset. The tissue microarray materials in our experiments consisted of 15 tumor-related genes in histological normal tissues adjacent to clinic tumors and different tumors, and the data were arranged in three different datasets and all the collection works were done by the Affiliated Zhongshan Hospital of Xiamen University. For each dataset, we used three distinguished classifiers to obtain the AUC of receive operating characteristic (ROC) curve. The experimental results showed that both feature selection methods could lead to reliable and accuracy results, and be used to discover the connection of genes and cancers. ? 2011 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/IWACI.2011.6160050
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/85842]
专题	软件学院－会议论文
推荐引用方式 GB/T 7714	Lin, Weipeng,Liu, Kunhong,Liu, Guoyan,et al. The application of feature selection methods to analyze the tissue microarray data. 2011-01-01.

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