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

Ao Li,Chen Peng,Yao Zhang,Minghui Wang,Mengqu Ge

doi:10.1155/2015/671950

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.

Highlights

Long noncoding RNAs, a class of important non-protein coding transcripts with lengths more than 200 nucleotides [1], have gained wide attention recently, and a large number of lncRNAs have been discovered by analysis of chromatin-state maps [2] and full-length complementary DNA [3] based on RNA-seq data [4]
We introduce a network-based method LPIHN to predict the proteins interacting with lncRNAs
A heterogeneous network is constructed by connecting protein-protein interaction (PPI) and lncRNA-lncRNA similarity network using known lncRNA-protein interactions

Summary

Introduction

Long noncoding RNAs (lncRNAs), a class of important non-protein coding transcripts with lengths more than 200 nucleotides [1], have gained wide attention recently, and a large number of lncRNAs have been discovered by analysis of chromatin-state maps [2] and full-length complementary DNA (cDNA) [3] based on RNA-seq data [4]. Recent researches show that lncRNAs play critical roles in complex cellular processes, such as epigenetic regulation of gene expression [5,6,7,8,9], chromatin modification [10], and cell differentiation. Uncovering the functions of lncRNAs is of great importance in understanding the mechanisms of biological processes. Almost all of the lncRNAs function through interactions with corresponding RNA binding proteins [14,15,16]. RNA binding proteins can interact with different lncRNAs to regulate diverse cellular processes [17, 18]. In 2013, Lu et al [20] introduced a method named lncPro, which predicts lncRNA-protein interactions by using scores yielded by amino acid and nucleotide sequences and Fisher’s linear discriminant method

Methods

Results

Conclusion