The annotation of structural glycomics data is a bottleneck in gaining insight into complex carbohydrates. An artificial intelligence model, CandyCrunch, has now been developed that accelerates the annotation process by orders of magnitude and achieves high accuracy in the prediction of glycan structures from tandem mass spectrometry data.
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This is a summary of: Urban, J. et al. Predicting glycan structure from tandem mass spectrometry via deep learning. Nat. Methods https://doi.org/10.1038/s41592-024-02314-6 (2024).
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Deep learning method for the prediction of glycan structures from mass spectrometry data. Nat Methods (2024). https://doi.org/10.1038/s41592-024-02315-5
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DOI: https://doi.org/10.1038/s41592-024-02315-5
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