Daniel Johannes Stekhoven

This paper introduces scClone2DR, a framework predicting tumour drug response at the clone level using single-cell DNA/RNA sequencing and drug-screening data, showing improved accuracy in identifying clonal sensitivities and resistance.

scAmpi provides a clinical workflow for scRNA-seq analysis, extracting clinically relevant information and supporting drug treatment identification.

gExcite is a start-to-end framework for analyzing single-cell gene expression and CITE-seq data, including hashing deconvolution, and is scalable for multiple samples.

The paper presents an automated workflow for in-silico drug response prediction in bladder cancer using multi-omic profiles, identifying personalized treatment options for most patients.