福州大学学报（自然科学版）2011，Vol.39Issue(2)：198-205,8.DOI:CNKI:35-1117/N.20110402.1005.017
一种采用新的相似性度量方法的共调控基因动态模糊聚类算法
A dynamic fuzzy clustering algorithm for analyzing co- regulated genes based on new similarity measurement
摘要
Abstract
Based on the quadratic mutual information, this paper presents a new method of similarity measurement, i.e. QMISM. QMISM is developed on the basis of the special properties and disadvantages of existing clustering algorithm of co - regulated genes. The high dimensional samples are mapped into two dimensional spaces by immune genetic algorithm. The algorithm proposed in this paper implements a dynamic fuzzy clustering method and improves the clustering results' visualization.Additionally, experiments on synthetic dataset and real gene expression dataset show that the proposed algorithm has better clustering effect.关键词
共调控基因/相似性度量/免疫遗传算法/动态模糊聚类Key words
co- regulated genes/ similarity measurement/ immune genetic algorithm/ dynamic fuzzy clustering分类
信息技术与安全科学引用本文复制引用
李小梅,郭红,吕暾..一种采用新的相似性度量方法的共调控基因动态模糊聚类算法[J].福州大学学报（自然科学版）,2011,39(2):198-205,8.基金项目
福建省自然科学基金资助项目(2009J01283) （2009J01283）
福建省科技计划重点资助项目(2008H0026) （2008H0026）
