Stefan Schreiber

This study shows that STING acts as a genome-integrity checkpoint in epithelial cells, independent of interferon, and its loss leads to chromosomal instability and tumor development.

This study identifies HLA-associated CDR3-QTLs that influence T-cell receptor composition in IBD and healthy controls, revealing disease-specific and universal effects on TRB repertoires.

FixNCut is a reversible fixation and dissociation method that preserves RNA integrity and cellular composition in human and mouse tissues, enabling robust single-cell and spatial analyses.

The paper identifies ten new genes with coding variants linked to Crohn's disease risk using sequencing data from over 30,000 patients and 80,000 controls.

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 identifies shared and ethnicity-specific HLA associations with ulcerative colitis through trans-ethnic analysis of diverse populations.

This paper introduces AVA,Dx, a machine learning method using whole exome sequencing to predict Crohn's disease status with 71% precision and 73% recall.

This study identifies shared genetic loci between multiple system atrophy and inflammatory bowel disease using conjFDR, highlighting immune and gut-related molecular mechanisms.