Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (CoRR, 2023)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (ICLR, 2024)

Real-World Molecular Out-Of-Distribution: Specification and Investigation. - Prudencio Tossou; Cas Wognum; Michael Craig; Hadrien Mary; Emmanuel Noutahi (J. Chem. Inf. Model., 2024)

A call for an industry-led initiative to critically assess machine learning for real-world drug discovery. - Cas Wognum; Jeremy R. Ash; Matteo Aldeghi; Raquel Rodríguez-Pérez; Cheng Fang; Alan C. Cheng; Daniel J. Price; Djork-Arné Clevert; Ola Engkvist; W. Patrick Walters (Nat. Mac. Intell., 2024)

RxRx3-core: Benchmarking drug-target interactions in High-Content Microscopy. - Oren Kraus; Federico Comitani; John Urbanik; Kian Kenyon-Dean; Lakshmanan Arumugam; Saber Saberian; Cas Wognum; Safiye Celik; Imran S. Haque (CoRR, 2025)

Virtual Cells: Predict, Explain, Discover. - Emmanuel Noutahi; Jason S. Hartford; Prudencio Tossou; Shawn Whitfield; Alisandra K. Denton; Cas Wognum; Kristina Ulicna; Michael Craig; Jonathan Hsu; Michael Cuccarese; Emmanuel Bengio; Dominique Beaini; et al. (CoRR, 2025)