Pengmian Feng*, Lijing Feng and Chaohui Tang Pages 1 - 11 ( 11 )
Background: N 6 -methyladenosine (m6A) plays critical roles in a broad set 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 good complements 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 give a comprehensive review and comparison on existing methods.
Results: Since researches on m6A in Saccharomyces cerevisiae are relatively clear, in this review, we summarized recent progresses on computational prediction of m6A sites in S. cerevisiae and assessed the performance of existing computational methods. Finally, future directions of computationally identifying m6A sites were presented.
Conclusion: Taken together, we anticipate that this review will provide important guides for computational analysis of m 6A modifications.
RNA modification, N6 -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