LPI-IBNRA: Long Non-coding RNA-Protein Interaction Prediction Based on Improved Bipartite Network Recommender Algorithm

Xie, Guobo and Wu, Cuiming and Sun, Yuping and Fan, Zhiliang and Liu, Jianghui (2019) LPI-IBNRA: Long Non-coding RNA-Protein Interaction Prediction Based on Improved Bipartite Network Recommender Algorithm. Frontiers in Genetics, 10. ISSN 1664-8021

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Abstract

According to the latest research, lncRNAs (long non-coding RNAs) play a broad and important role in various biological processes by interacting with proteins. However, identifying whether proteins interact with a specific lncRNA through biological experimental methods is difficult, costly, and time-consuming. Thus, many bioinformatics computational methods have been proposed to predict lncRNA-protein interactions. In this paper, we proposed a novel approach called Long non-coding RNA-Protein Interaction Prediction based on Improved Bipartite Network Recommender Algorithm (LPI-IBNRA). In the proposed method, we implemented a two-round resource allocation and eliminated the second-order correlations appropriately on the bipartite network. Experimental results illustrate that LPI-IBNRA outperforms five previous methods, with the AUC values of 0.8932 in leave-one-out cross validation (LOOCV) and 0.8819 ± 0.0052 in 10-fold cross validation, respectively. In addition, case studies on four lncRNAs were carried out to show the predictive power of LPI-IBNRA.

Item Type: Article
Subjects: STM Digital Press > Medical Science
Depositing User: Unnamed user with email support@stmdigipress.com
Date Deposited: 14 Feb 2023 10:17
Last Modified: 24 Jun 2024 05:11
URI: http://publications.articalerewriter.com/id/eprint/237

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