| Molecular representations in AI-driven drug discovery: a review and practical guide L David, A Thakkar, R Mercado, O Engkvist Journal of cheminformatics 12 (1), 56, 2020 | 521 | 2020 |
| Applications of deep-learning in exploiting large-scale and heterogeneous compound data in industrial pharmaceutical research L David, J Arús-Pous, J Karlsson, O Engkvist, EJ Bjerrum, T Kogej, ... Frontiers in pharmacology 10, 1303, 2019 | 59 | 2019 |
| Identification of compounds that interfere with high‐throughput screening assay technologies L David, J Walsh, N Sturm, I Feierberg, JWM Nissink, H Chen, J Bajorath, ... ChemMedChem 14 (20), 1795-1802, 2019 | 37 | 2019 |
| A toolkit for covalent docking with GOLD: from automated ligand preparation with KNIME to bound protein–ligand complexes L David, A Mdahoma, N Singh, S Buchoux, E Pihan, C Diaz, O Rabal Bioinformatics Advances 2 (1), vbac090, 2022 | 6 | 2022 |
| Molecular representations in AI-driven drug discovery: A review and practical guide. J Cheminform 2020; 12 (1): 56 L David, A Thakkar, R Mercado, O Engkvist | 6 | |
| ESR 5: Analysis of Compounds Promiscuity based on a Bioassay Ontology L David | | |
| HTS Technologies L David, J Walsh, J Bajorath | | |
Ola EngkvistAstraZeneca R&D Gothenburg Orcid:0000-0003-4970-6461Email được xác minh tại astrazeneca.com