A Robust Clustering Technique for Grouping Biological Data: an Illustrative Study in Gene Ezpression Data

摘要：

Clustering data based on a measure of similarity (or dissimilarity) is a critical step in scientific data analysis and especially in current bioinformatics field. A typical example is, with the advent of DNA Microarrays, clustering analysis becomes a powerful way to explore the expression profiles of all genes in the genome. And many algorithms have been developed for this problem. Here, we aim to introduce a more robust clustering technique (neural gas algorithm) for this problem and hope it can be applied to other problems in bioinformatics.

关键词： Gene ezpression profiles Neural Gas K-means Clustering analysis

作者: Xuemei Ning Shihua Zhang

作者单位: College of Science,Beijing Forestry University,Beijing 100083 Academy of Mathematics and Systems Science,CAS,Beijing 100190

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 267-275

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）