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Using Natural Language Processing to Learn the Grammar of Glycans

By Daniel Bojar, Diogo M. Camacho, James J. Collins

Posted 11 Jan 2020
bioRxiv DOI: 10.1101/2020.01.10.902114

While nucleic acids and proteins receive ample attention, progress on understanding the structural and functional roles of carbohydrates has lagged behind. Here, we develop a language model for glycans, SweetTalk, taking into account glycan connectivity and composition. We use this model to investigate motifs in glycan substructures, classify them according to their O-/N-linkage, and predict their immunogenicity with an accuracy of ~92%, opening up the potential for rational glycoengineering.

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