Andreas Möck

This study uses single-nucleus RNA sequencing and spatial transcriptomics to compare primary and metastatic leiomyosarcoma, identifying antigen-presenting fibroblasts associated with metastasis.

Phoenix predicts spatially resolved single-cell gene expression from histology, identifying new biomarkers and validating them across cancers and treatment regimens.

This paper introduces a method to infer signaling pathway activities from H&E slides in HNSCC, revealing two prognostic tumor states.

This study compares deep learning and machine learning for biomarker prediction in cancer genomes, finding DL performs better in cross-assay and data-sparse settings.