Predicting Long Noncoding RNA and Protein Interactions Using Heterogeneous Network Model.

Journal: BioMed research international
Published Date:

Abstract

Recent study shows that long noncoding RNAs (lncRNAs) are participating in diverse biological processes and complex diseases. However, at present the functions of lncRNAs are still rarely known. In this study, we propose a network-based computational method, which is called lncRNA-protein interaction prediction based on Heterogeneous Network Model (LPIHN), to predict the potential lncRNA-protein interactions. First, we construct a heterogeneous network by integrating the lncRNA-lncRNA similarity network, lncRNA-protein interaction network, and protein-protein interaction (PPI) network. Then, a random walk with restart is implemented on the heterogeneous network to infer novel lncRNA-protein interactions. The leave-one-out cross validation test shows that our approach can achieve an AUC value of 96.0%. Some lncRNA-protein interactions predicted by our method have been confirmed in recent research or database, indicating the efficiency of LPIHN to predict novel lncRNA-protein interactions.

Authors

  • Ao Li
    Beijing University of Chinese Medicine, Beijing, China.
  • Mengqu Ge
    School of Information Science and Technology, University of Science and Technology of China, 443 Huangshan Road, Hefei 230027, China.
  • Yao Zhang
    Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
  • Chen Peng
    Department of Pharmacy, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
  • Minghui Wang
    College of Chemistry and Material Science, Shandong Agricultural University, Tai'an 271018, PR China.