Alexander Mattausch

HT SpaceM is a high-throughput single-cell metabolomics method that detects small molecules with high reproducibility and identifies cell-type markers and metabolic pathways in diverse cell lines.

DeePiCt is a deep-learning framework for segmenting and localizing macromolecular complexes in cryo-electron tomograms, showing effectiveness in identifying low-abundance structures across species.

This study investigates how Cupriavidus necator reallocates its proteome under different growth conditions and finds that many proteins are not utilized and autotrophy-related enzymes are underutilized.