Analysis approaches for the identification and prediction of N 6 -methyladenosine sites.

The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m 6 A sites, in particular full-transcriptome m 6 A. And individual m 6 A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single nucleotide resolution. Currently, the identification of m 6 A sites is mainly carried out by experiment and prediction methods, based on high-throughput sequencing and machine learning model respectively. This review summarizes the recent topics and progress made in bioinformatics methods of deciphering the m 6 A methylation, including the experimental detection of m 6 A methylation sites, techniques of data analysis, the way of predicting m 6 A methylation sites, m 6 A methylation databases, and detection of m 6 A modification in circRNA. At the end, the essay makes a brief discussion for the development perspective in this area.