期刊
NUCLEIC ACIDS RESEARCH
卷 43, 期 3, 页码 1370-1379出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkv020
关键词
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资金
- National Institutes of Health [1R01LM010185, 1U01CA166886, 1U01HL111560]
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1236983] Funding Source: National Science Foundation
RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with similar to 94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with similar to 83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA- protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred.
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