Pengmian Feng*, Lijing Feng and Chaohui Tang Pages 1219 - 1229 ( 11 )
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.
RNA modification, N<sup>6</sup>-methyladenosine, epitranscriptome, machine learning, feature representation, web server.
School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611730, School of Sciences, North China University of Science and Technology, Tangshan 063000, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611730