Jonas Schulte-Schrepping

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

This study compares T cell development in humanized mice with and without murine MHC, finding that busulfan conditioning in MHC-deficient mice promotes activated T cells while irradiation favors naive T cells.

The paper develops an in vitro platform to screen immune senomodulators using human-derived immune cells, enabling personalized anti-aging treatments through multi-scale molecular analysis.

This study shows that Satb1 downregulation prevents autoimmunity by maintaining Tfh cell homeostasis and preventing excessive GC formation and auto-antibody secretion.

The paper identifies OSMR and SST as molecular markers for human dermal sleeping nociceptors, providing new therapeutic targets for neuropathic pain.

This study identifies molecular factors shaping brain-resident CD8+ T cell formation and function in health and disease.

This study shows that primary cilia dysfunction in Bbs8-/- mice reduces adipose stem cells and promotes fibrogenic progenitors via disrupted Hedgehog signaling, affecting adipogenesis and lipid uptake.

This paper integrates transcriptome and chromatin state data to develop a scalable pipeline for drug discovery, predicting cancer cell line sensitivity and guiding compound development.

This paper introduces Swarm Learning, a decentralized machine learning approach for disease classification using transcriptomic data, demonstrating its effectiveness in developing classifiers for COVID-19, tuberculosis, and leukemias while preserving privacy.

This study uses single-cell RNA-seq and computational methods to analyze macrophage states in COPD patients, revealing transcriptional changes and metabolic shifts associated with the disease.

This paper demonstrates that memory-driven computing significantly accelerates NGS data processing and reduces energy consumption for RNA-seq tasks.

The paper develops robust and accurate classifiers for AML diagnosis using blood gene expression data and machine learning across 12,029 samples from 105 studies.

This study investigates how IL4 signalling and NCOR2 regulate the reprogramming of human monocytes into dendritic cells and macrophages, revealing distinct transcriptional and functional profiles based on cytokine exposure timing.