DeepGlycan

adjacent

DeepGlycan: adjacent. Deep-learning de novo glycopeptide sequencing that learns the relationship between glycopeptide spectra and fragment ions for both N- and O-glycans, rather than being…

Deep-learning de novo glycopeptide sequencing that learns the relationship between glycopeptide spectra and fragment ions for both N- and O-glycans, rather than being tied to one fragmentation method. Reports over 92% glycan recall and about 95% precision on N-glycopeptide spectra under both sceHCD and EThcD, and sequences O-glycans with no additional training. Identifies an O-glycopeptide in mouse heart tissue confirmed by exoglycosidase treatment and a synthetic standard.

Kind	adjacent
Deep learning	yes
Acquisition	DDA

Code

https://github.com/zqq66/DeepGlycan

Live stars, open issues and last-push figures are on the Code activity chart.

Data

What the papers describing this method trained it on and reported its results on, as each paper states it. A version is named only where the paper names one.

Deposited

High-Accuracy De Novo Prediction for N- and O-linked Glycopeptides Across Multiple Fragmentation Techniques (as deposited)

Also used, purpose not recorded

Mouse glycoproteome - pGlyco 2 (as deposited)
Mouse glycoproteome - pGlyco 2 (PXD005553) (as deposited)
Mouse glycoproteome: Heart - pGlyco 2 (as deposited)
Mouse glycoproteome: Kidney - pGlyco 2 (as deposited)
Proteome-wide discovery of human brain protein glycoforms and glycan modification changes in Alzheimer’s disease (as deposited)
Role of N-glycosylation in FcRIIIa interaction with IgG (as deposited)

Paper describing it

High-accuracy glycan de novo prediction for N- and O-linked glycopeptides across multiple fragmentation techniques (2026, Nature Communications, peer-reviewed)

Authors (6)

Qianqiu Zhang, Zeping Mao, Yuling Chen, Baozhen Shan, Haiteng Deng, Ming Li

Seen in the charts

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