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Current Genomics

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ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

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Mini-Review Article

A Mini-review of the Computational Methods Used in Identifying RNA 5- Methylcytosine Sites

Author(s): Jianwei Li, Yan Huang and Yuan Zhou*

Volume 21, Issue 1, 2020

Page: [3 - 10] Pages: 8

DOI: 10.2174/2213346107666200219124951

open access plus

Abstract

RNA 5-methylcytosine (m5C) is one of the pillars of post-transcriptional modification (PTCM). A growing body of evidence suggests that m5C plays a vital role in RNA metabolism. Accurate localization of RNA m5C sites in tissue cells is the premise and basis for the in-depth understanding of the functions of m5C. However, the main experimental methods of detecting m5C sites are limited to varying degrees. Establishing a computational model to predict modification sites is an excellent complement to wet experiments for identifying m5C sites. In this review, we summarized some available m5C predictors and discussed the characteristics of these methods.

Keywords: 5-methylcytosine, RNA modification, machine learning, prediction, sequence encoding, pseudo dinucleotide composition.

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