LPI-NRLMF: lncRNA-protein interaction prediction by neighborhood regularized logistic matrix factorization
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Hongsheng Liu1,2,3,*, Guofei Ren4,*, Huan Hu1, Li Zhang1, Haixin Ai1, Wen Zhang5 and Qi Zhao2,6
1School of Life Science, Liaoning University, Shenyang, 110036, China
2Research Center for Computer Simulating and Information Processing of Bio-macromolecules of Liaoning Province, Shenyang, 110036, China
3Engineering Laboratory for Molecular Simulation and Designing of Drug Molecules of Liaoning, Shenyang, 110036, China
4School of Information, Liaoning University, Shenyang, 110036, China
5School of Computer, Wuhan University, Wuhan, 430072, China
6School of Mathematics, Liaoning University, Shenyang, 110036, China
*These authors share co-first authorship
Qi Zhao, email: [email protected]
Keywords: lncRNA; protein; interaction prediction; neighborhood regularized
Received: July 26, 2017 Accepted: August 28, 2017 Published: October 19, 2017
LncRNA-protein interactions play important roles in many important cellular processes including signaling, transcriptional regulation, and even the generation and progression of complex diseases. However, experimental methods for determining proteins bound by a specific lncRNA remain expensive, difficult and time-consuming, and only a few theoretical approaches are available for predicting potential lncRNA-protein associations. In this study, we developed a novel matrix factorization computational approach to uncover lncRNA-protein relationships, namely lncRNA-protein interactions prediction by neighborhood regularized logistic matrix factorization (LPI-NRLMF). Moreover, it is a semi-supervised and does not need negative samples. As a result, new model obtained reliable performance in the leave-one-out cross validation (the AUC of 0.9025 and AUPR of 0.6924), which significantly improved the prediction performance of previous models. Furthermore, the case study demonstrated that many lncRNA-protein interactions predicted by our method can be successfully confirmed by experiments. It is anticipated that LPI-NRLMF could serve as a useful resource for potential lncRNA-protein association identification.
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