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Applications of Machine Learning in miRNA Discovery and Target Prediction

[ Vol. 20 , Issue. 8 ]


Alisha Parveen, Syed H. Mustafa, Pankaj Yadav and Abhishek Kumar*   Pages 537 - 544 ( 8 )


MicroRNA (miRNA) is a small non-coding molecule that is involved in gene regulation and RNA silencing by complementary on their targets. Experimental methods for target prediction can be time-consuming and expensive. Thus, the application of the computational approach is implicated to enlighten these complications with experimental studies. However, there is still a need for an optimized approach in miRNA biology. Therefore, machine learning (ML) would initiate a new era of research in miRNA biology towards potential diseases biomarker. In this article, we described the application of ML approaches in miRNA discovery and target prediction with functions and future prospective. The implementation of a new era of computational methodologies in this direction would initiate further advanced levels of discoveries in miRNA.


microRNA, machine learning, target prediction, gene expression, feature generation, feature selection.


Institute of Medical Bioinformatics and Systems Medicine Medical Center, Faculty of Medicine, Albert-Ludwigs University of Freiburg, 79110 Freiburg, Department of Computer Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, Uttar Pradesh, Department of Bioscience and Bioengineering, Indian Institute of Technology, Jodhpur, Institute of Bioinformatics, International Technology Park, Bangalore, 560066

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