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Non-Coding RNA 2017, 3(1), 1;

Recent Advances in Identification of RNA Modifications

1,* and 2,*
Department of Physics, School of Sciences, and Center for Genomics and Computational Biology, North China University of Science and Technology, Tangshan 063000, China
Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
Authors to whom correspondence should be addressed.
Academic Editors: Jian-Hua Yang and Liang-Hu Qu
Received: 22 November 2016 / Revised: 19 December 2016 / Accepted: 23 December 2016 / Published: 28 December 2016
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-Coding RNA Research)
Full-Text   |   PDF [191 KB, uploaded 28 December 2016]


RNA modifications are involved in a broad spectrum of biological and physiological processes. To reveal the functions of RNA modifications, it is important to accurately predict their positions. Although high-throughput experimental techniques have been proposed, they are cost-ineffective. As good complements of experiments, many computational methods have been proposed to predict RNA modification sites in recent years. In this review, we will summarize the existing computational approaches directed at predicting RNA modification sites. We will also discuss the challenges and future perspectives in developing reliable methods for predicting RNA modification sites. View Full-Text
Keywords: RNA modification; N6-methyladenosine; pseudouridine; N1-methyladenosine RNA modification; N6-methyladenosine; pseudouridine; N1-methyladenosine
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Chen, W.; Lin, H. Recent Advances in Identification of RNA Modifications. Non-Coding RNA 2017, 3, 1.

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