DocumentCode :
1496172
Title :
Inferring Contagion in Regulatory Networks
Author :
Fujita, André ; Sato, João Ricardo ; Demasi, Marcos Angelo Almeida ; Yamaguchi, Rui ; Shimamura, Teppei ; Ferreira, Carlos Eduardo ; Sogayar, Mari Cleide ; Miyano, Satoru
Author_Institution :
Comput. Sci. Res. Program, RIKEN, Tokyo, Japan
Volume :
8
Issue :
2
fYear :
2011
Firstpage :
570
Lastpage :
576
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.
Keywords :
biology computing; genetics; inference mechanisms; physiological models; Pearl; TP53 pathway; bootstrap algorithm; contagion; gene expression; gene regulatory network models; regulatory networks; Biological system modeling; Biology computing; Gene expression; Mathematics; Probability distribution; Random variables; Switches; Switching circuits; Testing; US Department of Transportation; Contagion; local correlation; regulatory network.; Algorithms; Gene Expression Profiling; Gene Regulatory Networks; Genomics; Oligonucleotide Array Sequence Analysis; Tumor Suppressor Protein p53;
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2010.40
Filename :
5467038
Link To Document :
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