Identifying co-expressed gene groups with significant functional categories

被引：0
|
作者：
Cai, Li-jun [1 ]
He, Dong [2 ]
机构：
[1] Hunan Univ, Changsha 410082, Peoples R China
[2] Hubei Univ, Huazhong Univ Sci & Technol, Mol Imaging Key Lab, Wuhan 430074, Peoples R China
来源：
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES | 2007年 / 2卷
关键词：
hierarchical clustering method; gene expression profile; functional categories;
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：
Connecting computational results with biological knowledge is one of the most urgent issues in the post genome research. We present a simple but powerful procedure to identify co-expressed gene groups associated with significant functional categories. An R language implementation, named SigClust, was built and tested on a set of gene expression dataset. Further, comparison of linear and nonlinear similarity measurements of gene expression profiles was tested on SigClust. Finally, a consistent conclusion with previous researches was acquired.
引用
收藏
页码：920 / +
页数：3
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