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dc:abstract "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 ∼94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ∼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." ;
dc:creator "['Suresh, V.', 'Liu, Liang', 'Adjeroh, Donald', 'Zhou, Xiaobo']" ;
dc:identifier ,
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dc:issued "2015-01-01"^^xsd:date ;
dc:license "CC BY" ;
dc:title "RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information" ;
sso:has_full_text "True" ;
sso:journal "Nucleic Acids Res" ;
sso:sha "6973170d4c8d9576b0e3bfd8391e907d779ee355" ;
sso:source_x "PMC" .