Jochen M. Schwenk

The paper uses frequent blood microsampling and proteome analysis in a mouse model to detect early biomarkers of type 1 diabetes, enabling timely intervention.

The paper identifies a proteomic signature associated with menopausal hormonal therapy use and increased breast cancer risk using a data-driven analysis of plasma proteins.

This study develops machine learning models to predict liver fat content using multi-omic and clinical data from NAFLD patients, achieving higher accuracy than existing tools.

The paper provides considerations and recommendations for designing and analyzing plasma proteomics studies to improve translational applications in clinical settings.

This study investigates the association between genetic variants in PMAT and OCT1 transporters and metformin gastrointestinal intolerance in type 2 diabetes patients.

The paper maps and characterizes the human secretome by annotating 2,623 predicted secreted proteins and their spatial distribution, using a high-throughput cell factory for recombinant protein production and analysis.