Fuzzy Biclustering for DNA Microarray Data Analysis

被引：0

作者：

Han, Lixin ^{[1
]}

Yan, Hong ^{[2
,3
]}

机构：

[1] Nanjing Univ Technol, Dept Comp Sci & Engn, Nanjing, Peoples R China

[2] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia

[3] City Univ Hong Kong, Dept Elect Engn, Kowloon, Peoples R China

来源：

2008 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-5 | 2008年

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fuzzy biclustering analysis is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy biclustering clustering method for microarray data analysis. The method employs a combination of the Nelder-Mead and min-max algorithm to construct hierarchically structured biclustering. The method can automatically identify the groups of genes that show similar expression patterns under a specific subset of the samples.

引用

页码：1134 / +

页数：3

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