MOTIVATION: Recent technological advances revealed that an unexpected large number of proteins interact with transcripts even if the RNA-binding domains are not annotated. We introduce catRAPID signature to identify ribonucleoproteins based on physico-chemical features instead of sequence similarity searches. The algorithm, trained on human proteins and tested on model organisms, calculates the overall RNA-binding propensity followed by the prediction of RNA-binding regions. catRAPID signature outperforms other algorithms in the identification of RNA-binding proteins and detection of non-classical RNA-binding regions. Results are visualized on a webpage and can be downloaded or forwarded to catRAPID omics for predictions of RNA targets. AVAILABILITY AND IMPLEMENTATION: catRAPID signature can be accessed at http://s.tartaglialab.com/new_submission/signature

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement nº RIBOMYLOME_309545. We acknowledge support of the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’, SEV-2012-0208 and FEDER funds (European Regional Development Fund) under the project number BFU2014-55054-P. R. Delli Ponti is supported by the MINECO’s pre-doctoral grant Severo Ochoa 2013–2017 (SVP-2014-068402).