| Target prediction utilising negative bioactivity data covering large chemical space LH Mervin, AM Afzal, G Drakakis, R Lewis, O Engkvist, A Bender Journal of cheminformatics 7, 1-16, 2015 | 138 | 2015 |
| Trisubstituted-imidazoles induce apoptosis in human breast cancer cells by targeting the oncogenic PI3K/Akt/mTOR signaling pathway CD Mohan, V Srinivasa, S Rangappa, L Mervin, S Mohan, S Paricharak, ... PLoS One 11 (4), e0153155, 2016 | 126 | 2016 |
| Uncertainty quantification in drug design LH Mervin, S Johansson, E Semenova, KA Giblin, O Engkvist Drug discovery today 26 (2), 474-489, 2021 | 69 | 2021 |
| Optimizing the Cell Painting assay for image-based profiling BA Cimini, SN Chandrasekaran, M Kost-Alimova, L Miller, A Goodale, ... Nature protocols 18 (7), 1981-2013, 2023 | 61 | 2023 |
| Understanding cytotoxicity and cytostaticity in a high-throughput screening collection LH Mervin, Q Cao, IP Barrett, MA Firth, D Murray, L McWilliams, ... ACS chemical biology 11 (11), 3007-3023, 2016 | 59 | 2016 |
| Toward understanding the cold, hot, and neutral nature of Chinese medicines using in silico mode-of-action analysis X Fu, LH Mervin, X Li, H Yu, J Li, SZ Mohamad Zobir, A Zoufir, Y Zhou, ... Journal of chemical information and modeling 57 (3), 468-483, 2017 | 57 | 2017 |
| Novel adamantanyl-based thiadiazolyl pyrazoles targeting EGFR in triple-negative breast cancer A Sebastian, V Pandey, CD Mohan, YT Chia, S Rangappa, J Mathai, ... ACS omega 1 (6), 1412-1424, 2016 | 50 | 2016 |
| JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations SN Chandrasekaran, J Ackerman, E Alix, DM Ando, J Arevalo, M Bennion, ... BioRxiv, 2023.03. 23.534023, 2023 | 46 | 2023 |
| Orthologue chemical space and its influence on target prediction LH Mervin, KC Bulusu, L Kalash, AM Afzal, F Svensson, MA Firth, I Barrett, ... Bioinformatics 34 (1), 72-79, 2018 | 42 | 2018 |
| Melloddy: Cross-pharma federated learning at unprecedented scale unlocks benefits in qsar without compromising proprietary information W Heyndrickx, L Mervin, T Morawietz, N Sturm, L Friedrich, A Zalewski, ... Journal of chemical information and modeling 64 (7), 2331-2344, 2023 | 39 | 2023 |
| Reinvent 4: Modern AI–driven generative molecule design HH Loeffler, J He, A Tibo, JP Janet, A Voronov, LH Mervin, O Engkvist Journal of Cheminformatics 16 (1), 20, 2024 | 36 | 2024 |
| Cell morphological profiling enables high-throughput screening for PROteolysis TArgeting Chimera (PROTAC) phenotypic signature MA Trapotsi, E Mouchet, G Williams, T Monteverde, K Juhani, R Turkki, ... ACS Chemical Biology 17 (7), 1733-1744, 2022 | 36 | 2022 |
| Comparison of chemical structure and cell morphology information for multitask bioactivity predictions MA Trapotsi, LH Mervin, AM Afzal, N Sturm, O Engkvist, IP Barrett, ... Journal of chemical information and modeling 61 (3), 1444-1456, 2021 | 36 | 2021 |
| A Nano-MgO and ionic liquid-catalyzed ‘green’synthesis protocol for the development of adamantyl-imidazolo-thiadiazoles as anti-tuberculosis agents targeting sterol 14α … S Anusha, B Cp, CD Mohan, J Mathai, S Rangappa, S Mohan, Chandra, ... PLoS One 10 (10), e0139798, 2015 | 26 | 2015 |
| Industry-scale orchestrated federated learning for drug discovery M Oldenhof, G Ács, B Pejó, A Schuffenhauer, N Holway, N Sturm, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 15576 …, 2023 | 25 | 2023 |
| Comparison of scaling methods to obtain calibrated probabilities of activity for protein–ligand predictions LH Mervin, AM Afzal, O Engkvist, A Bender Journal of Chemical Information and Modeling 60 (10), 4546-4559, 2020 | 23 | 2020 |
| Current trends in drug sensitivity prediction I Cortes-Ciriano, L H Mervin, A Bender Current pharmaceutical design 22 (46), 6918-6927, 2016 | 21 | 2016 |
| Computer-aided design of multi-target ligands at A1R, A2AR and PDE10A, key proteins in neurodegenerative diseases L Kalash, C Val, J Azuaje, MI Loza, F Svensson, A Zoufir, L Mervin, ... Journal of Cheminformatics 9, 1-19, 2017 | 18 | 2017 |
| Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty LH Mervin, MA Trapotsi, AM Afzal, IP Barrett, A Bender, O Engkvist Journal of Cheminformatics 13, 1-17, 2021 | 16 | 2021 |
| Systemic neurotransmitter responses to clinically approved and experimental neuropsychiatric drugs HR Noori, LH Mervin, V Bokharaie, Ö Durmus, L Egenrieder, S Fritze, ... Nature Communications 9 (1), 4699, 2018 | 15 | 2018 |
