Morten Thaysen‐Andersen

The paper develops an enrichment-free glycoproteomics method using mass defect-driven glycopeptide classification to identify sex differences in murine plasma fucosylation.

This study identifies ST6GAL1-mediated sialyl linkage switching in TAMs that drives cancer-promoting nanotubes with α2,6-sialylation, affecting immune interactions and CRC progression.

The paper defines sex-specific glycoproteomes in mouse tissues using multi-omics integration, revealing distinct glycoform patterns and enzyme relationships across 19 tissues.

This study identifies glyco-signatures in serum samples from septic shock patients that predict survival outcomes upon ICU admission using glycomics and machine learning.

This study identifies N-acetyl-β-D-hexosaminidase as a driver of colorectal cancer progression and a prognostic marker in patient plasma.

This paper introduces a compositional data analysis framework for glycomics to address statistical issues in comparative glycan data, reducing false positives and revealing new biological insights.

The paper maps N-glycoproteome changes during neutrophil granulopoiesis, showing granule-specific glycosylation and remodelling driven by protein expression shifts.