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GlypNirO: An automated workflow for quantitative N- and O-linked glycoproteomic data analysis.
Phung, Toan K; Pegg, Cassandra L; Schulz, Benjamin L.
Afiliación
  • Phung TK; School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, 4072, Australia.
  • Pegg CL; School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, 4072, Australia.
  • Schulz BL; School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, 4072, Australia.
Beilstein J Org Chem ; 16: 2127-2135, 2020.
Article en En | MEDLINE | ID: mdl-32952729
ABSTRACT
Mass spectrometry glycoproteomics is rapidly maturing, allowing unprecedented insights into the diversity and functions of protein glycosylation. However, quantitative glycoproteomics remains challenging. We developed GlypNirO, an automated software pipeline which integrates the complementary outputs of Byonic and Proteome Discoverer to allow high-throughput automated quantitative glycoproteomic data analysis. The output of GlypNirO is clearly structured, allowing manual interrogation, and is also appropriate for input into diverse statistical workflows. We used GlypNirO to analyse a published plasma glycoproteome dataset and identified changes in site-specific N- and O-glycosylation occupancy and structure associated with hepatocellular carcinoma as putative biomarkers of disease.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Beilstein J Org Chem Año: 2020 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Beilstein J Org Chem Año: 2020 Tipo del documento: Article País de afiliación: Australia