Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty. - Lewis H. Mervin; Maria-Anna Trapotsi; Avid M. Afzal; Ian P. Barrett; Andreas Bender 002; Ola Engkvist (J. Cheminformatics, 2021)

Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions. - Maria-Anna Trapotsi; Lewis H. Mervin; Avid M. Afzal; Noé Sturm; Ola Engkvist; Ian P. Barrett; Andreas Bender 002 (J. Chem. Inf. Model., 2021)

Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data. - Srijit Seal; Hongbin Yang; Maria-Anna Trapotsi; Satvik Singh; Jordi Carreras Puigvert; Ola Spjuth; Andreas Bender 002 (J. Cheminformatics, 2023)