Constrained Competitive Learning Algorithm for DNA Microarray Gene Expression Data Analysis

摘要：

Cluster analysis is an important tool for discovering the structures and patterns hidden in gene expression data. In this paper, a new algorithm for clustering gene expression profiles is proposed. In this method, we find natural dusters in the data based on a competitive learning strategy. Using partially known modes as constraints in our method, we reduce the sensitivity of the clustering procedure to the algorithm initialization and produce more reliable results. Also the proposed algorithm can give the correct estimation of the number of clusters in the data. Experiments on simulated and real gene expression data demonstrate the robustness of our method. Comparative studies with several other clustering algorithms illustrated the effectiveness of our method.

作者: Shuanhu Wu Hong Yan Qingshang Zeng Yanjie Zhang Yibin Song

作者单位: School of Computer Science and Technology, Yantai university, Yantai 264005, Shandong, China Departm Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong K School of Computer Science and Technology, Yantai university, Yantai 264005, Shandong, China

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 44-51

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）