Simon Renders

This study uses Perturb-seq to identify gene regulatory programs in HSPCs that link genetic regulators to cell biological processes and stem cell phenotypes.

The paper develops a hierarchical classification framework combining epigenetic and genetic data with machine learning to improve diagnosis and risk stratification in hematologic malignancies.

UCS enables high-throughput single-cell proteomic analysis of blood samples, revealing disease-specific expression profiles and immune subpopulations in acute myeloid leukemia.

This study identifies rare tumor-reactive T cells and conserved antigen repertoires in multiple myeloma and acute myeloid leukemia, developing a TCR fitness model to predict immunotherapy response.