Inferring contagion in regulatory networks.
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.
Fujita
André
A
A. Fujita is with the Computational Science Research Program, RIKEN, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. andrefujita@riken.jp
Sato
João Ricardo
JR
Angelo
Marcos
M
Demasi
Almeida
A
Yamaguchi
Rui
R
Shimamura
Teppei
T
Ferreira
Carlos Eduardo
CE
Sogayar
Mari Cleide
MC
Miyano
Satoru
S
D000465:Algorithms; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D016159:Tumor Suppressor Protein p53 / Q000235:genetics
D016159:Tumor Suppressor Protein p53