iMRM is a predictor for identifying post-transcriptional modification sites.

We developed a new predictor called iMRM, which is able to simultaneously identify m6A, m5C, m1A, ψ and A-to-I modifications in Homo sapiens, Mus musculus and Saccharomyces cerevisiae. In iMRM, the feature selection technique was used to pick out the optimal features. The results from both 10-fold cross validation and jackknife test demonstrated that the performance of iMRM is superior to existing methods for identifying RNA modifications.