Supporting Information
Raw data were made available in MassIVE: https://doi.org/doi:10.25345/C5JJ00.
Supporting Information File 1: Supporting tables. | ||
Format: XLSX | Size: 2.0 MB | Download |
Supporting Information File 2: Supporting figures. | ||
Format: PDF | Size: 2.6 MB | Download |
Supporting Information File 3: Python script connecting the GlycopeptideGraphMS output and LaCyTools input. | ||
Format: IPYNB | Size: 3.6 KB | Download |
Supporting Information File 4: LaCyTools analyte list. | ||
Format: REF | Size: 2.3 KB | Download |
Supporting Information File 5: Analyte search list. | ||
Format: CSV | Size: 271 B | Download |
Supporting Information File 6: Byonic N-glycan list. | ||
Format: TXT | Size: 11.3 KB | Download |
Supporting Information File 7: Byonic O-glycan list. | ||
Format: TXT | Size: 3.4 KB | Download |
Cite the Following Article
Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification
Steffen Lippold, Arnoud H. de Ru, Jan Nouta, Peter A. van Veelen, Magnus Palmblad, Manfred Wuhrer and Noortje de Haan
Beilstein J. Org. Chem. 2020, 16, 3038–3051.
https://doi.org/10.3762/bjoc.16.253
How to Cite
Lippold, S.; de Ru, A. H.; Nouta, J.; van Veelen, P. A.; Palmblad, M.; Wuhrer, M.; de Haan, N. Beilstein J. Org. Chem. 2020, 16, 3038–3051. doi:10.3762/bjoc.16.253
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