Inferring Contagion in Regulatory Networks

被引:1
|
作者
Fujita, Andre [1 ]
Sato, Joao Ricardo [2 ]
Almeida Demasi, Marcos Angelo [3 ,4 ]
Yamaguchi, Rui [5 ]
Shimamura, Teppei [5 ]
Ferreira, Carlos Eduardo [6 ]
Sogayar, Mari Cleide [3 ,4 ]
Miyano, Satoru [5 ]
机构
[1] RIKEN, Computat Sci Res Program, Minato Ku, Tokyo 1088639, Japan
[2] Univ Fed ABC, Ctr Math Computat & Cognit, BR-09280550 Santo Andre, SP, Brazil
[3] Univ Sao Paulo, Inst Chem, Dept Biochem, BR-05508900 Sao Paulo, Brazil
[4] Univ Sao Paulo, Cell & Mol Therapy Ctr NUCEL, BR-05508900 Sao Paulo, Brazil
[5] Univ Tokyo, Ctr Human Genome, Minato Ku, Tokyo 1088639, Japan
[6] Univ Sao Paulo, Inst Math & Stat, BR-05508090 Sao Paulo, Brazil
关键词
Contagion; local correlation; regulatory network; GENE-EXPRESSION; CORRELATION CURVES; BAYESIAN NETWORKS; P53; ASSOCIATION; PROTEIN;
D O I
10.1109/TCBB.2010.40
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Several gene regulatory network models containing concepts of directionality at the edges have been proposed. However, only a few reports have an interpretable definition of directionality. Here, differently from the standard causality concept defined by Pearl, we introduce the concept of contagion in order to infer directionality at the edges, i.e., asymmetries in gene expression dependences of regulatory networks. Moreover, we present a bootstrap algorithm in order to test the contagion concept. This technique was applied in simulated data and, also, in an actual large sample of biological data. Literature review has confirmed some genes identified by contagion as actually belonging to the TP53 pathway.
引用
收藏
页码:570 / 576
页数:7
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