RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information.

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.

journal_name

Nucleic Acids Res

journal_title

Nucleic acids research

authors

Suresh V,Liu L,Adjeroh D,Zhou X

doi

10.1093/nar/gkv020

subject

Has Abstract

pub_date

2015-02-18 00:00:00

pages

1370-9

issue

3

eissn

0305-1048

issn

1362-4962

pii

gkv020

journal_volume

43

pub_type

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