Abstract
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 CONTACT: gian.tartaglia@crg.es or gian@tartaglialab.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.