O-GlcNAcylation functions in a protein- and site-specific manner. Despite the great progress in experimentally mapping O-GlcNAc sites, it is still a challenging task in many cases. We constructed an ensemble model O-GlcNAcPRED-DL to predict O-GlcNAc sites on proteins by using deep learning approaches. In comparison to existing methods, O-GlcNAcPRED-DL shows improved sensitivity and accuracy. We anticipate that it will be used as a valuable tool to expedite the discovery of O-GlcNAc sites on proteins (especially of humans and mice) and elucidation of their functions in physiology and diseases.


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