Lukas Reiter

This paper introduces PAMAF, a novel DIA-MS mode using HRIM for proteomics, achieving higher sensitivity and efficiency in protein identification and quantification.

This paper develops a method to quantitatively analyze the structural states of alpha-synuclein in vitro and in situ, revealing conformational changes in yeast and human neurons.

This paper optimizes diagonal-PASEF mass spectrometry with retention time down-sampling, improving identifications and quantification in proteomics.

This study identifies aging-associated proteomic and lipid signatures in exosomes from senescent cells and human plasma, revealing shared biomarkers and pathways linked to senescence and tissue damage.

This paper develops an automated sample preparation platform for bottom-up proteomics, demonstrating improved reproducibility, throughput, and suitability for drug development.

This study introduces a robust multiplex DIA-MS workflow with machine learning and statistical filtering to profile protein turnover in cisplatin-resistant cancer cells, revealing correlations between transcript regulation and protein degradation.

The paper provides detailed experimental protocols and an open-source tool, MhcVizPipe, for analyzing MHC I and II ligand datasets in immunopeptidomics.

LiP-Quant identifies drug targets in complex proteomes using limited proteolysis and mass spectrometry, providing EC50 estimates and distinguishing between homologous proteins.

This paper introduces a label-free quantitative proteomics platform using microLC and SWATH acquisition, achieving high throughput and precision in protein quantification.