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Inferring Contagion in Regulatory Networks
March/April 2011 (vol. 8 no. 2)
pp. 570-576
ASCII Text
x 
 
André Fujita, João Ricardo Sato, Marcos Angelo Almeida Demasi, Rui Yamaguchi, Teppei Shimamura, Carlos Eduardo Ferreira, Mari Cleide Sogayar, Satoru Miyano, "Inferring Contagion in Regulatory Networks," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 2, pp. 570-576, March/April, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2010.40,
author = {André Fujita and João Ricardo Sato and Marcos Angelo Almeida Demasi and Rui Yamaguchi and Teppei Shimamura and Carlos Eduardo Ferreira and Mari Cleide Sogayar and Satoru Miyano},
title = {Inferring Contagion in Regulatory Networks},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {8},
number = {2},
issn = {1545-5963},
year = {2011},
pages = {570-576},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2010.40},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - Inferring Contagion in Regulatory Networks
IS - 2
SN - 1545-5963
SP570
EP576
EPD - 570-576
A1 - André Fujita,
A1 - João Ricardo Sato,
A1 - Marcos Angelo Almeida Demasi,
A1 - Rui Yamaguchi,
A1 - Teppei Shimamura,
A1 - Carlos Eduardo Ferreira,
A1 - Mari Cleide Sogayar,
A1 - Satoru Miyano,
PY - 2011
KW - Contagion
KW - local correlation
KW - regulatory network.
VL - 8
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
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.

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Index Terms:
Contagion, local correlation, regulatory network.
Citation:
André Fujita, João Ricardo Sato, Marcos Angelo Almeida Demasi, Rui Yamaguchi, Teppei Shimamura, Carlos Eduardo Ferreira, Mari Cleide Sogayar, Satoru Miyano, "Inferring Contagion in Regulatory Networks," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 2, pp. 570-576, March-April 2011, doi:10.1109/TCBB.2010.40
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