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Predicting glycan structure from tandem mass spectrometry via deep learning

Research datakeyboard_double_arrow_right Dataset 01 Jan 2023Embargo end date: 31 Oct 2023 English Publisher:Zenodo
Authors: Urban, James; Chunsheng, Jin; Thomsson, Kristina A.; Karlsson, Niclas G.; Ives, Callum M.; Fadda, Elisa; Bojar, Daniel;

doi: 10.5281/zenodo.10997110 , 10.5281/zenodo.10029271 , 10.5281/zenodo.7940047 , 10.5281/zenodo.7940046

Predicting glycan structure from tandem mass spectrometry via deep learning

Abstract

Curated set of LC-MS/MS data from glycomics studies. Used for training and applying CandyCrunch, a deep learning model to predict glycan structure from LC-MS/MS data, described in Urban et al., Nat Methods, 2024 and https://github.com/BojarLab/CandyCrunch. Files: full_dataset.xlsx: Full dataset with all annotated LC-MS/MS glycan spectra X_train.pkl: spectra and metadata from our training set y_train.pkl: labels from our training set X_test.pkl: spectra and metadata from our independent test set y_test.pkl: labels from our independent test set glycans.pkl: glycans in IUPAC-condensed nomenclature in the same order as the label-encoding

Related Organizations
Keywords

glycan, machine learning, carbohydrate, deep learning, bioinformatics, mass spectrometry

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citations
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BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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