Bob van de Water

This study evaluates transcriptomic and morphological profiling methods for hazard assessment using reference chemicals in renal cells, finding HTTr provides higher mechanistic resolution than CPP.

This study develops a method to generate functional mammary gland organoids from human induced pluripotent stem cells, showing they can form layered epithelium and respond to hormonal signals.

The paper evaluates Cell Painting (CP) and Cell Painting PLUS (CPP) for predicting compound mechanisms of action, finding CPP better resolves off-target effects and improves MoA prediction for lysosome-related compounds.

This study uses Cell Painting PLUS to identify nephrotoxicity-related morphological signatures in human RPTEC/TERT1 cells by analyzing over 300 compounds.

This study introduces proxiloids, a scalable human-induced pluripotent stem cell differentiation method that models kidney proximal tubule toxicity more accurately than existing methods.

The paper evaluates how different transcriptomic analysis workflows affect potency estimates in toxicogenomics, finding significant variability driven by normalization, filtering, and pathway definitions.

This study identifies metabolic targets in breast cancer by analyzing multi-omics data from cell lines, revealing subtype-specific dependencies and potential drug targets.

This study uses live cell imaging to analyze NRF2 activation dynamics in response to repeated electrophile exposure, showing that recovery periods enable adaptive responses.

The paper develops a mathematical model to study how DNA damage affects cell cycle progression, finding that polyploidisation is a key response in HepG2 cells.

This study builds gene co-expression networks from rat kidney toxicogenomics data and integrates them into a web tool to improve safety assessment and biomarker identification for drug development.

H5CellProfiler is an R package that enables user-friendly analysis of large single-cell datasets on a local desktop with efficient memory usage and track labeling.

This study investigates how cancer cell density affects migration speed and persistence in TNBC cells using experimental data and computational modeling.

This study compares proliferation and migration transcriptomic signatures in breast cancer, finding migration is more strongly linked to patient survival.