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General Review Article

Comparison and Analysis of Computational Methods for Identifying N6-Methyladenosine Sites in Saccharomyces cerevisiae

Author(s): Pengmian Feng*, Lijing Feng and Chaohui Tang

Volume 27, Issue 9, 2021

Published on: 09 November, 2020

Page: [1219 - 1229] Pages: 11

DOI: 10.2174/1381612826666201109110703

Price: $65

Abstract

Background: N6-methyladenosine (m6A) plays critical roles in a broad range of biological processes. Knowledge about the precise location of m6A site in the transcriptome is vital for deciphering its biological functions. Although experimental techniques have made substantial contributions to identify m6A, they are still labor intensive and time consuming. As complement to experimental methods, in the past few years, a series of computational approaches have been proposed to identify m6A sites.

Methods: In order to facilitate researchers to select appropriate methods for identifying m6A sites, it is necessary to conduct a comprehensive review and comparison of existing methods.

Results: Since research works on m6A in Saccharomyces cerevisiae are relatively clear, in this review, we summarized recent progress of computational prediction of m6A sites in S. cerevisiae and assessed the performance of existing computational methods. Finally, future directions of computationally identifying m6A sites are presented.

Conclusion: Taken together, we anticipate that this review will serve as an important guide for computational analysis of m6A modifications.

Keywords: RNA modification, N6-methyladenosine, epitranscriptome, machine learning, feature representation, web server.

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