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Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation

Authors: Zheng Fang; Mingliang Ye;

Glyco-Decipher enables glycan database-independent peptide matching and in-depth characterization of site-specific N-glycosylation

Abstract

Archived versions of Glyco-Decipher at the time of publication. Please visit GitHub(https://github.com/DICP-1809/Glyco-Decipher/releases) for the latest version of Glyco-Decipher. Glyco-Decipher is a freely available software tool aimed at interpreting tandem mass spectrometry (MS/MS) spectra of N-glycopeptides fragmented by higher-energy collisional dissociation (HCD) in stepped energy mode. Glyco-Decipher enables glycan database-independent peptide search for N-glycopeptide mass spectra and provides comprehensive profiling of N-glycans in samples. Glyco-Decipher can detect new glycans that not present in glycan databases and can elucidate monosaccharide composition of new glycans and potential modifications on them. Glyco-Decipher can sensitively and reliably identify thousands of site-specific glycans for glycoproteomics analysis. Label-free quantification is achieved in Glyco-Decipher by extracting elution profiles of intact glycopeptides in MS1. And the quantification results are able to map to the glycosites in proteins for biological study. Glyco-Decipher is designed for the analysis of intact glycopeptide mass spectrum acquired from stepped collision mode fragmentation and exhibits best identification performance for mass spectrum acquired at normalized collision energy (NCE) at 20%-30%-40% with long chromatography gradient.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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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.
BIP!Impulse provided by BIP!
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