A joint mizture model for clustering genes from Gaussian and beta distributed data

摘要：

BackgroundCluster analysis has become a standard computational method for gene function discovery as well as for more general explanatory data analysis. A number of different approaches have been proposed for that purpose out of which different mixture models provide a principled probabilistic framework. Cluster analysis is increasingly often supplemented with multiple data sources nowadays and these heterogeneous information sources should be made as efficient use of as possible.

作者: Xiaofeng Dai Timo Erkkil(a) Olli Yli-Harja Harri L(a)hdesm(a)ki

作者单位: Department of Signal Processing, Tampere University of Technology, Tampere, Finland

会议类型: 国际会议

会议名称: The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)

会议地点: 北京

会议语种:英文

页码: 839

在线出版日期: 2009-01-01（万方平台首次上网日期，不代表论文的发表时间）