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