Proteomics

Dataset Information

0

Prediction of glycopeptide fragment mass spectra by deep learning


ABSTRACT: Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we propose a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrated that predicted spectral libraries can be used for analyzing DIA data of glycopeptides as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.

ORGANISM(S): Homo Sapiens Mus Musculus Schizosaccharomyces Pombe Saccharomyces Cerevisiae

SUBMITTER: Yi Yang  

PROVIDER: PXD045248 | iProX | Sun Dec 17 00:00:00 GMT 2023

REPOSITORIES: iProX

Similar Datasets

2022-03-04 | PXD031025 | Pride
2022-03-04 | PXD031032 | Pride
2023-10-19 | PXD030277 | Pride
2020-05-11 | PXD016865 | Pride
2023-09-25 | PXD045630 | iProX
2018-02-08 | PXD005931 | Pride
2020-04-21 | PXD015622 | Pride
2016-08-17 | PXD002803 | Pride
2020-10-06 | PXD021196 | Pride
2021-07-07 | PXD025859 | Pride