Genetic Algorithms Applied to Multi-Class Clustering for Gene Ex-pression Data

被引：9

作者：

Haiyan Pan Jun Zhu and Danfu HanInstitute of Bioinformatics Zhejiang University Hangzhou China ^{[310029
]}

Department of MathematicsZhejiang University Hangzhou China ^{[310027
]}

Hangzhou Genomics Institute Hangzhou China ^{[310008
]}

机构：

来源：

Genomics Proteomics & Bioinformatics | 2003年 / 04期

关键词：

genetic algorithms; gene expression; clustering; medoid;

D O I：

暂无

中图分类号：

Q343 [细胞遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

<正> A hybrid GA (genetic algorithm)-based clustering (HGACLUS) schema, combining merits of the Simulated Annealing, was described for finding an optimal or near-optimal set of medoids. This schema maximized the clustering success by achieving internal cluster cohesion and external cluster isolation. The performance

引用

页码：279 / 287

页数：9

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