Predicting lncRNA-protein Interactions by Machine Learning Methods: A Review

Title:Predicting lncRNA-protein Interactions by Machine Learning Methods: A Review

Volume: 15 Issue: 8

Author(s): Zhi-Ping Liu*

Affiliation:

• Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061,China

Keywords: LncRNA-protein interaction, lncRNA functionality, machine learning, bioinformatics, carcinogenesis, molecular.

Abstract: In this work, a review of predicting lncRNA-protein interactions by bioinformatics methods is provided with a focus on machine learning. Firstly, a computational framework for predicting lncRNA-protein interactions is presented. Then, the currently available data resources for the predictions have been listed. The existing methods will be reviewed by introducing their crucial steps in the prediction framework. The key functions of lncRNA, e.g., mediator on transcriptional regulation, are often involved in interacting with proteins. The interactions with proteins provide a tunnel of leveraging the molecular cooperativity for fulfilling crucial functions. Thus, the important directions in bioinformatics have been highlighted for identifying essential lncRNA-protein interactions and deciphering the dysfunctional importance of lncRNA, especially in carcinogenesis.

Cite this article as:

Liu Zhi-Ping *, Predicting lncRNA-protein Interactions by Machine Learning Methods: A Review, Current Bioinformatics 2020; 15 (8) . https://dx.doi.org/10.2174/1574893615666200224095925