iRNA(m6A)-PseDNC: Identifying N 6 -methyladenosine sites using pseudo dinucleotide composition.

As a prevalent post-transcriptional modification, N6 -methyladenosine (m6 A) plays key roles in a series of biological processes. Although experimental technologies have been developed and applied to identify m6 A sites, they are still cost-ineffective for transcriptome-wide detections of m6 A. As good complements to the experimental techniques, some computational methods have been proposed to identify m6 A sites. However, their performance remains unsatisfactory. In this study, we firstly proposed an Euclidean distance based method to construct a high quality benchmark dataset. By encoding the RNA sequences using pseudo nucleotide composition, a new predictor called iRNA(m6A)-PseDNC was developed to identify m6 A sites in the Saccharomyces cerevisiae genome. It has been demonstrated by the 10-fold cross validation test that the performance of iRNA(m6A)-PseDNC is superior to the existing methods. Meanwhile, for the convenience of most experimental scientists, established at the site https://lin-group.cn/server/iRNA(m6A)-PseDNC.php is its web-server, by which users can easily get their desired results without need to go through the detailed mathematics. It is anticipated that iRNA(m6A)-PseDNC will become a useful high throughput tool for identifying m6 A sites in the S. cerevisiae genome.