| Molecular sets (MOSES): a benchmarking platform for molecular generation models D Polykovskiy, A Zhebrak, B Sanchez-Lengeling, S Golovanov, O Tatanov, ... Frontiers in pharmacology 11, 565644, 2020 | 630 | 2020 |
| A de novo molecular generation method using latent vector based generative adversarial network O Prykhodko, SV Johansson, PC Kotsias, J Arús-Pous, EJ Bjerrum, ... Journal of Cheminformatics 11, 1-13, 2019 | 375 | 2019 |
| Randomized SMILES strings improve the quality of molecular generative models J Arús-Pous, SV Johansson, O Prykhodko, EJ Bjerrum, C Tyrchan, ... Journal of cheminformatics 11, 1-13, 2019 | 317 | 2019 |
| Uncertainty quantification in drug design LH Mervin, S Johansson, E Semenova, KA Giblin, O Engkvist Drug discovery today 26 (2), 474-489, 2021 | 77 | 2021 |
| Artificial intelligence and automation in computer aided synthesis planning A Thakkar, S Johansson, K Jorner, D Buttar, JL Reymond, O Engkvist Reaction chemistry & engineering 6 (1), 27-51, 2021 | 66 | 2021 |
| AI-assisted synthesis prediction S Johansson, A Thakkar, T Kogej, E Bjerrum, S Genheden, T Bastys, ... Drug Discovery Today: Technologies 32, 65-72, 2019 | 53 | 2019 |
| Using active learning to develop machine learning models for reaction yield prediction S Viet Johansson, H Gummesson Svensson, E Bjerrum, A Schliep, ... Molecular Informatics 41 (12), 2200043, 2022 | 24 | 2022 |
| Molecular sets (moses): a benchmarking platform for molecular generation models. Front Pharmacol D Polykovskiy, A Zhebrak, B Sanchez-Lengeling, S Golovanov, O Tatanov, ... | 16 | 2020 |
| Randomized SMILES strings improve the quality of molecular generative models. J Cheminform 11: 71 J Arús-Pous, SV Johansson, O Prykhodko, EJ Bjerrum, C Tyrchan, ... | 12 | 2019 |
| A de novo molecular generation method using latent vector based generative adversarial network. J Cheminform 11: 74 O Prykhodko, SV Johansson, PC Kotsias, J Arús-Pous, EJ Bjerrum, ... | 10 | 2019 |
| Improving deep generative models with randomized smiles J Arús-Pous, S Johansson, O Prykhodko, EJ Bjerrum, C Tyrchan, ... International Conference on Artificial Neural Networks, 747-751, 2019 | 4 | 2019 |
| De novo generated combinatorial library design SV Johansson, MH Chehreghani, O Engkvist, A Schliep Digital Discovery 3 (1), 122-135, 2024 | 3 | 2024 |
| Comparison between SMILES-based differential neural computer and recurrent neural network architectures for de novo molecule design SV Johansson, O Prykhodko, J Arús-Pous, O Engkvist, H Chen | 2 | 2019 |
| Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes S Johansson, O Engkvist, MH Chehreghani, A Schliep 2023 IEEE International Conference on Big Data (BigData), 5260-5265, 2023 | | 2023 |
| Intelligent data acquisition for drug design through combinatorial library design S Johansson PQDT-Global, 2023 | | 2023 |
| Differentiable Neural Computers for in silico molecular design: Benchmarks of architectures in generative modeling of molecules O PRYKHODKO, S JOHANSSON | | 2019 |
| Additional methods J Arús-Pous, S Johansson, O Prykhodko, EJ Bjerrum, C Tyrchan, ... ratio 2, 1,564,030, 0 | | |
| Supplementary methods J Arús-Pous, S Johansson, O Prykhodko, EJ Bjerrum, C Tyrchan, ... ratio 2, 1,564,030, 0 | | |
Ola EngkvistAstraZeneca R&D Gothenburg Orcid:0000-0003-4970-6461Verified email at astrazeneca.com
