Proteomics

Dataset Information

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Mouse glycoproteome - pGlyco 2

ABSTRACT: Precise and large-scale characterization of glycoproteome is critical for understanding the biological functions of glycoproteins. Due to the complexity of glycosylation, the overall throughput, data quality and accessibility of site-specific glycosylation analysis are overwhelmingly lower than those of routine proteomic studies. Here, we introduce a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry (MS) and pGlyco 2.0, a dedicated search engine for large-scale glycopeptide analysis with comprehensive quality control (false discovery rate evaluation on the glycan, peptide and glycopeptide matches).

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Lung

SUBMITTER: pGlyco pFind  

LAB HEAD: Mingqi Liu

PROVIDER: PXD005555 | Pride | 2017-10-11

REPOSITORIES: Pride

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Dataset's files

Source:
Action DRS
MouseLung-Z-T-1-FDR.txt Txt
MouseLung-Z-T-1.raw Raw
MouseLung-Z-T-2-FDR.txt Txt
MouseLung-Z-T-2.raw Raw
MouseLung-Z-T-3-FDR.txt Txt
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Publications

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 co  ...[more]

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