RESUMO
RNA-binding proteins (RBPs) play a key role in post-transcriptional regulation via binding to coding and non-coding RNAs. Recent development in experimental technologies, aimed to identify the targets of RBPs, has significantly broadened our knowledge on protein-RNA interactions. However, for many RBPs in many organisms and cell types, experimental RNA-binding data is not available. In this chapter we describe a computational approach, named RBPmap, available as a web service via http://rbpmap.technion.ac.il/ and as a stand-alone version for download. RBPmap was designed for mapping and predicting the binding sites of any RBP within a nucleic acid sequence, given the availability of an experimentally defined binding motif of the RBP. The algorithm searches for a sub-sequence that significantly matches the RBP motif, considering the clustering propensity of other weak matches within the motif environment. Here, we present different applications of RBPmap for discovering the involvement of RBPs and their targets in a variety of cellular processes, in health and disease states. Finally, we demonstrate the performance of RBPmap in predicting the binding targets of RBPs in large-scale RNA-binding data, reinforcing the strength of the tool in distinguishing cognate binding sites from weak motifs.