Stefan K. Weidt

This study compares lipidomic profiles of Trypanosoma congolense and Trypanosoma brucei to understand their metabolic differences and implications for in vitro culture and therapy development.

This paper develops a CRISPR base-editing library for genome-wide loss-of-function screening in Leishmania mexicana to study drug response mechanisms and identify novel biomarkers.

The paper introduces a maximum bipartite matching workflow for LC-MS/MS data acquisition to improve the identification of metabolites by optimizing fragmentation spectra collection.

TopNEXt improves data acquisition in multi-sample LC-MS/MS metabolomics by extending DDA exclusion methods across samples using a Region of Interest and intensity-based scoring system.

This study benchmarks DDA and DIA acquisition methods in metabolomics using simulations and real-world validation, showing performance differences based on co-eluting ion counts.

This paper develops new data-dependent acquisition strategies for metabolomics using an in silico framework, showing they fragment more unique ions than standard methods.

The paper introduces ViMMS, a simulator for LC-MS/MS fragmentation strategies, enabling in-silico testing and optimization of mass spectrometry acquisition methods.