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The availability of cross-platform, large-scale genomic data has enabled the investigation of complex biological relationships for many cancers. Identification of reliable cancer-related biomarkers requires the characterization of multiple interactions across complex genetic networks. MicroRNAs are small non-coding RNAs that regulate gene expression; however, the direct relationship between a microRNA and its target gene is difficult to measure. We propose a novel Bayesian model to identifydoi:10.1111/biom.12266 pmid:25639276 pmcid:PMC4499566 fatcat:rlbzuqdd5bft3hqmjmevi6nwv4