Predictor for m6A readouts: Reading-m6A

N6-methyladenosine (m6A) methylation has emerged as a prevalent RNA modification that extensively impacts various physiological and pathological processes via various post-transcriptional readout effects in mammals. Our analysis on m6A readouts, coupled with the integration of public and re-profiled m6A methylome data, revealed high cell type specificity in m6A readouts where m6A level alone is insufficient to predict m6A readouts. Therefore, ad hoc machine learning models focused on the RNA binding protein (RBP) binding context of m6A sites were established to predict the readouts from m6A methylation site/peak data, which have demonstrated substantial predictive ability.