Jonne Rietdijk

The paper compares single-cell and aggregated morphological profiling to identify programmed cell death mechanisms, finding aggregated data performs better in supervised models.

A human-supervised multi-agent LLM system covered drug repurposing from knowledge graph building to assay analysis in three case studies; retrospective COVID-19 screen AUC-ROC 0.986 without predefined thresholds.

This paper introduces LCTP, a workflow for analyzing live-cell time series data to improve mode of action classification by capturing temporal phenotypes across compounds and cell lines.

The paper identifies host-targeting antivirals against SARS-CoV-2 using morphological profiling, finding compounds that reverse infected cell phenotypes and validate host processes hijacked by viruses.

This study compares the predictive performance of models trained on fluorescence and brightfield images for drug mechanism of action prediction, finding comparable results.