Inferring contagion in regulatory networks.

IEEE/ACM Trans. Comput. Biology Bioinform.(2011)

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摘要
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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关键词
inferring contagion,standard causality concept,actual large sample,biological data,simulated data,local correlation,regulatory network.,contagion concept,gene regulatory network model,tp53 pathway,regulatory networks,bootstrap algorithm,gene expression dependence,regulatory network,contagion,spline,genetics,random variables,gene regulatory network,gene expression,bioinformatics,data models,pearl,correlation
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