Carsten Jörn Beese

Four-model hiPSC screen in 384-well imaging reached 83% accuracy (88% sensitivity, 75% specificity) on 130 scored compounds from a 146-compound reference set, scalable to hundreds of compounds monthly.

The paper presents a morphological profiling dataset of EU-OPENSCREEN bioactive compounds across multiple imaging sites and cell lines, validated for robustness and used to map profiles to activity and toxicity.

This paper introduces a semi-supervised contrastive learning method for bioactivity prediction from Cell Painting image data, improving classification of pharmacological classifications and biological targets.