Gene Expression Network Reconstruction by LEP Method Using Microarray Data

被引：0
|
作者：
You, Na [1 ]
Mou, Peng [1 ]
Qiu, Ting [1 ]
Kou, Qiang [1 ]
Zhu, Huaijin [1 ]
Chen, Yuexi [1 ]
Wang, Xueqin [1 ]
机构：
[1] Sun Yat Sen Univ, Sch Math Computat Sci, Guangzhou 510275, Guangdong, Peoples R China
来源：
SCIENTIFIC WORLD JOURNAL | 2012年
关键词：
SELECTION; INFERENCE; LASSO; MODEL;
D O I：
10.1100/2012/753430
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Gene expression network reconstruction using microarray data is widely studied aiming to investigate the behavior of a gene cluster simultaneously. Under the Gaussian assumption, the conditional dependence between genes in the network is fully described by the partial correlation coefficient matrix. Due to the high dimensionality and sparsity, we utilize the LEP method to estimate it in this paper. Compared to the existing methods, the LEP reaches the highest PPV with the sensitivity controlled at the satisfactory level. A set of gene expression data from the HapMap project is analyzed for illustration.
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页数：6
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