期刊
BIOINFORMATICS
卷 32, 期 5, 页码 773-775出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btv629
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资金
- European Research Council under the European Union's Seventh Framework Programme (FP7) / ERC [RIBOMYLOME_309545]
- Spanish Ministry of Economy and Competitiveness
- Centro de Excelencia Severo Ochoa [SEV-2012-0208]
- FEDER funds (European Regional Development Fund) [BFU2014-55054-P]
- MINECO's pre-doctoral grant Severo Ochoa [SVP-2014-068402]
- ICREA Funding Source: Custom
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.
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