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
收藏
页码：1134 / +
页数：3
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