Abstract
N(6)-methyladenosine (m(6)A) plays important roles in a branch of biological and physiological processes. Accurate identification of m(6)A sites is especially helpful for understanding their biological functions. Since the wet-lab techniques are still expensive and time-consuming, it's urgent to develop computational methods to identify m(6)A sites from primary RNA sequences. Although there are some computational methods for identifying m(6)A sites, no methods whatsoever are available for detecting m(6)A sites in microbial genomes. In this study, we developed a computational method for identifying m(6)A sites in Escherichia coli genome. The accuracies obtained by the proposed method are >90% in both 10-fold cross-validation test and independent dataset test, indicating that the proposed method holds the high potential to become a useful tool for the identification of m(6)A sites in microbial genomes.