Frank Oliver Nestle

The paper constructs a multi-ancestry single-cell eQTL map for SLE, identifying colocalized eQTLs with GWAS loci and highlighting cell-type-specific regulatory mechanisms.

This study uses deep learning to predict YAP1/TEAD activity from histology slides, linking histological patterns to disease aggressiveness in cancer patients.

This study investigates how scRNA-seq data can predict the clinical success of drug targets by analyzing cell type and disease-specific expression patterns.