Christofer A. Q. Karlsson

The paper introduces mE-DIA, a multi-enzyme DIA-MS workflow that improves proteoform detection in proteomics by integrating analysis and interpretation into a single toolset.

This study examines temporal changes in platelet activation and organ dysfunction during invasive Streptococcus pyogenes infection in mice, showing platelets contribute to liver dysfunction and may be therapeutic targets.

This paper introduces proteome velocity, a framework using flow matching to infer continuous proteome trajectories from proteomics data, showing its application in mouse sepsis and clinical COVID-19.

This paper designs an epitope-centric nanoparticle vaccine against Streptococcus pyogenes using structural mass spectrometry and deep learning to enhance immunogenicity.

The paper develops a proteomics strategy to infer the origin of proteins in human plasma using a proteome atlas and RNA/protein atlases, demonstrating its application in disease cohorts.

This study uses pharmacoproteomics to analyze treatment responses in a murine sepsis model, identifying distinct response patterns and drug interactions across organs and time.

This paper introduces GPS, a machine learning-based method for improving peptide and protein identification accuracy and rates in DIA proteomics by using an external dataset, and demonstrates its effectiveness in identifying biomarkers for acute kidney injury.