Tim Becker

The paper predicts compound activity using chemical structures, images, and gene-expression profiles, showing that combining these modalities can improve prediction accuracy in drug discovery.

The paper develops a method to predict cell health phenotypes from Cell Painting images using machine learning, validated across multiple perturbations and assays.

This study evaluates deep learning strategies for nucleus segmentation in fluorescence images, showing U-Net outperforms classical methods and reduces biologically relevant errors.