Identifying Characteristic Genes Based on Robust Principal Component Analysis

被引:0
作者
Zheng, Chun-Hou [1 ]
Liu, Jin-Xing [2 ,3 ]
Mi, Jian-Xun [2 ]
Xu, Yong [2 ]
机构
[1] Anhui Univ, Coll Elect Engn & Automat, Hefei 230039, Peoples R China
[2] Harbin Inst Technol, Shenzhen Grad Sch, BioComp Res Ctr, Shenzhen, Peoples R China
[3] Qufu Normal Univ, Coll Informat & Commun Technol, Rizhao, Peoples R China
来源
EMERGING INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS | 2012年 / 304卷
关键词
robust PCA; gene identification; gene expression data;
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
In this paper, based on robust PCA, a novel method of characteristic genes identification is proposed. In our method, the differentially expressed genes and non-differentially expressed genes are treated as perturbation signals S-0 and low-rank matrix A(0), respectively, which can be recovered from the gene expression data using robust PCA. The scheme to identify the characteristic genes is as following. Firstly, the matrix S-0 of perturbation signals is discovered from gene expression data matrix D by using robust PCA. Secondly, the characteristic genes are selected according to matrix S-0. Finally, the characteristic genes are checked by the tool of Gene Ontology. The experimental results show that our method is efficient and effective.
引用
收藏
页码:174 / +
页数:2
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