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Predicting lncRNA-Protein Interactions With miRNAs as Mediators in a Heterogeneous Network Model.
- Source :
-
Frontiers in genetics [Front Genet] 2020 Jan 22; Vol. 10, pp. 1341. Date of Electronic Publication: 2020 Jan 22 (Print Publication: 2019). - Publication Year :
- 2020
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Abstract
- Long non-coding RNAs (lncRNAs) play important roles in various biological processes, where lncRNA-protein interactions are usually involved. Therefore, identifying lncRNA-protein interactions is of great significance to understand the molecular functions of lncRNAs. Since the experiments to identify lncRNA-protein interactions are always costly and time consuming, computational methods are developed as alternative approaches. However, existing lncRNA-protein interaction predictors usually require prior knowledge of lncRNA-protein interactions with experimental evidences. Their performances are limited due to the number of known lncRNA-protein interactions. In this paper, we explored a novel way to predict lncRNA-protein interactions without direct prior knowledge. MiRNAs were picked up as mediators to estimate potential interactions between lncRNAs and proteins. By validating our results based on known lncRNA-protein interactions, our method achieved an AUROC (Area Under Receiver Operating Curve) of 0.821, which is comparable to the state-of-the-art methods. Moreover, our method achieved an improved AUROC of 0.852 by further expanding the training dataset. We believe that our method can be a useful supplement to the existing methods, as it provides an alternative way to estimate lncRNA-protein interactions in a heterogeneous network without direct prior knowledge. All data and codes of this work can be downloaded from GitHub (https://github.com/zyk2118216069/LncRNA-protein-interactions-prediction).<br /> (Copyright © 2020 Zhou, Shen, Yu, Luo, Gao and Du.)
Details
- Language :
- English
- ISSN :
- 1664-8021
- Volume :
- 10
- Database :
- MEDLINE
- Journal :
- Frontiers in genetics
- Publication Type :
- Academic Journal
- Accession number :
- 32038709
- Full Text :
- https://doi.org/10.3389/fgene.2019.01341