Inferring Contagion in Regulatory Networks

Authors:
Andre Fujita;Joao Ricardo Sato;Marcos Almeida Demasi;Rui Yamaguchi;Teppei Shimamura;Carlos Eduardo Ferreira;Mari Cleide Sogayar;Satoru Miyano
Affiliations:
RIKEN, Japan;Universidade Federal do ABC, São Paulo, Brazil;University of São Paulo, São Paulo, Brazil;University of Tokyo, Japan;University of Tokyo, Japan;University of São Paulo, São Paulo, Brazil;University of São Paulo, São Paulo, Brazil;University of Tokyo, Japan
Venue:
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Year:
2011

Citing 4
Cited 0

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Abstract

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.