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Applications of Machine Learning in miRNA Discovery and Target Prediction

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 thes...

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Detalles Bibliográficos
Autores principales: Parveen, Alisha, Mustafa, Syed H., Yadav, Pankaj, Kumar, Abhishek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Science Publishers 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290058/
https://www.ncbi.nlm.nih.gov/pubmed/32581642
http://dx.doi.org/10.2174/1389202921666200106111813
Descripción
Sumario: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.