Identifying Transcription Factors and microRNAs as Key Regulators of Pathways Using Bayesian Inference on Known Pathway Structures

Transcription factors and microRNAs are both known to regulate gene expression in eukaryotes in a sequence- specific manner. This has led to the creation of numerous computational approaches that aim at predicting what genes are the targets of certain transcription factors and microRNAs. These methods, although powerful, provide a static snapshot of how genes may be regulated and are often plagued by the presence of false positives. We propose a method that combines: a) transcription factors and microRNAs that are predicted to target genes in pathways, with b) microarray expression profiles, in conjunction with c) the known structure of molecular pathways. These elements are integrated in a Bayesian network that allows the identification of the main regulators in different pathways, based on probability inference, of ER+ and ER-tumors.