Sophia Steigerwald

The paper quantifies proteins and transcripts in the same cell, finding that the proteome defines stable cell states while the transcriptome reflects transitions.

This study uses single-cell spatial proteomics to map human liver zonation patterns and shows their disruption in fibrosis.

The paper uses Deep Visual Proteomics to show that human colon organoids switch to an in vivo-like phenotype after xenotransplantation.

The paper introduces a novel hybrid mass spectrometer, Stellar MS, enabling rapid and sensitive clinical biomarker validation using 15N labeled proteins.

This study uses spatial proteomics and machine learning to analyze AATD in human liver tissue, revealing peroxisomal upregulation and a terminal hepatocyte state with distinct proteomic signatures.

This study uses Deep Visual Proteomics to analyze SRCC proteomics, identifying DNA replication stress and immune-related features, suggesting pembrolizumab may be more effective than chemotherapy.

AlphaDIA enables end-to-end transfer learning for feature-free proteomics, improving identification and quantification of post-translational modifications.

The paper develops a high-throughput workflow for subcellular proteome and phospho-proteome profiling and applies it to study EGFR signaling and stress responses in cells.