RNAcommender: genome-wide recommendation of RNA-protein interactions

MOTIVATION: Information about RNA-protein interactions is a vital pre-requisite to tackle the dissection of RNA regulatory processes. Despite the recent advances of the experimental techniques, the currently available RNA interactome involves a small portion of the known RNA binding proteins. The importance of determining RNA-protein interactions, coupled with the scarcity of the available information, calls for in silico prediction of such interactions. RESULTS: We present RNAcommender, a recommender system capable of suggesting RNA targets to unexplored RNA binding proteins, by propagating the available interaction information taking into account the protein domain composition and the RNA predicted secondary structure. Our results show that RNAcommender is able to successfully suggest RNA interactors for RNA binding proteins using little or no interaction evidence. RNAcommender was tested on a large dataset of human RBP-RNA interactions, showing a good ranking performance (average AUC ROC of 0.75) and significant enrichment of correct recommendations for 75% of the tested RBPs. RNAcommender can be a valid tool to assist researchers in identifying potential interacting candidates for the majority of RBPs with uncharacterized binding preferences.