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

[ Vol. 15 , Issue. 8 ]


Zhi-Ping Liu*   Pages 831 - 840 ( 10 )


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.


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


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

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