Issue No. 02 - March/April (2011 vol. 8)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2010.40
André Fujita , RIKEN, Japan
João Ricardo Sato , Universidade Federal do ABC, São Paulo, Brazil
Marcos Angelo Almeida Demasi , University of São Paulo, São Paulo, Brazil
Rui Yamaguchi , University of Tokyo, Japan
Teppei Shimamura , University of Tokyo, Japan
Carlos Eduardo Ferreira , University of São Paulo, São Paulo, Brazil
Mari Cleide Sogayar , University of São Paulo, São Paulo, Brazil
Satoru Miyano , University of Tokyo, Japan
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.
Contagion, local correlation, regulatory network.
M. C. Sogayar et al., "Inferring Contagion in Regulatory Networks," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. , pp. 570-576, 2010.