Figure 1.

BayMiR Method. Flowchart of the BayMiR algorithm. For each miRNA, BayMiR first identifies the set of targets based on the presence of conserved complementary sites to the seed region of the miRNA in the 3’UTR of the target. Next, for each miRNA, BayMiR extracts the mRNA expression vectors associated with the selected targets from the mRNA gene expression data set, and averages them to obtain the miRNA activity vector. These miRNA activity vectors are used as regressors in a Bayesian linear regression model to explain the down-regulation in the expression level of the target. Finally, BayMiR infers scores (the regression coefficients) using a penalized likelihood method called elastic net regression. Each score indicates the strength of miRNA- mediated repression on the target genes.

Radfar et al. BMC Genomics 2013 14:592   doi:10.1186/1471-2164-14-592
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