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

被引:16
|
作者
Liu, Zhi-Ping [1 ,2 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Dept Biomed Engn, Jinan 250061, Shandong, Peoples R China
[2] Shandong Univ, Ctr Intelligent Med, Jinan 250061, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
LncRNA-protein interaction; lncRNA functionality; machine learning; bioinformatics; carcinogenesis; molecular; LONG NONCODING RNAS; DATABASE; MICRORNAS; EVOLUTION; RESOURCE; DNA;
D O I
10.2174/1574893615666200224095925
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:831 / 840
页数:10
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