A Clustering Algorithm for Gene Ezpression Data Based on Graph Theory

摘要：

The development of the biological technology provides people the opportunities to obtain the information which hides in the gene expression data, however, the huge gene number and the complex biological network increase the difficulty of the comprehending and explaining of these information. Therefore, people introduced clustering algorithms to discover the significative gene patterns, and then we propose and analyze a clustering algorithm which based on graph theory. Proved by the experiment, this algorithm not only can analyze the gene expression data fast, but also get good clustering quality.

关键词： Minimum Spanning Tree Clustering Algorithm Gene Ezpression Data SIS Clustering Algorithm

作者: Xiaoming Du Zheng Zhao Zhongbo Jiang

作者单位: Computer Science and Technology Institute Tianjin University Tianjin,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）