Michael J. Geuenich

This study integrates spatial proteomics and genomics in PDAC to identify tumour-immune-stroma interactions and their genomic associations, showing multi-omics models improve patient survival prediction.

The paper introduces Cytomarker, an interactive platform for designing antibody panels using single-cell RNA-seq data, and validates it on human mammary tissue subpopulations.

The paper infers multicellular ecosystems from nonspatial scRNA-seq data and shows they predict therapy response and are linked to somatic mutations.

This paper benchmarks active and self-supervised learning strategies for single-cell data annotation, showing benefits in handling cell type imbalance and demonstrating marker-aware heuristics improve accuracy.

This study evaluates how dataset imbalance affects single-cell RNA sequencing integration and introduces metrics to assess integration stability in imbalanced settings.

Astir assigns cell identities to single-cell imaging and proteomic data by integrating prior knowledge, outperforming existing methods in accuracy and scalability.