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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795616 | PMC |
http://dx.doi.org/10.1093/bioinformatics/btv629 | DOI Listing |
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