Application of a New Similarity Measure in Clustering Gene Ezpression Data

摘要：

A new similarity measure for gene expression data, CorHsim, is proposed. It is compared with the other two commonly used measures over some very simple examples. Together with the other two measures, it is implemented in Kmeans clustering method over two real gene expression data sets. The clustering results show that the CorHsim measure has better performances than the other two measures, which demonstrates that it is a promising measure for gene expression data to discover gene expression patterns.

关键词： similarity measure gene ezpression data clustering analysis

作者: Gangguo Li Zhengzhi Wang Qingshan Ni Xiaomin Wang Han Qing-juan

作者单位: Institute of Automation,National University of Defense Technology,Changsha 410073,Hunan,PR China Fangchenggang Entry-Exit Inspection and Quarantine Bureau Fangchenggang,Guangxi,538001,PR China

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）