| State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesis IV Tetko, P Karpov, R Van Deursen, G Godin Nature communications 11 (1), 5575, 2020 | 270 | 2020 |
| Transformer-CNN: Swiss knife for QSAR modeling and interpretation P Karpov, G Godin, IV Tetko Journal of cheminformatics 12, 1-12, 2020 | 180 | 2020 |
| A transformer model for retrosynthesis P Karpov, G Godin, IV Tetko International Conference on Artificial Neural Networks, 817-830, 2019 | 121 | 2019 |
| CATMoS: collaborative acute toxicity modeling suite K Mansouri, AL Karmaus, J Fitzpatrick, G Patlewicz, P Pradeep, D Alberga, ... Environmental health perspectives 129 (4), 047013, 2021 | 86 | 2021 |
| A survey of multi‐task learning methods in chemoinformatics S Sosnin, M Vashurina, M Withnall, P Karpov, M Fedorov, IV Tetko Molecular informatics 38 (4), 1800108, 2019 | 75 | 2019 |
| Augmentation is what you need! IV Tetko, P Karpov, E Bruno, TB Kimber, G Godin International Conference on Artificial Neural Networks, 831-835, 2019 | 42 | 2019 |
| One-class classification as a novel method of ligand-based virtual screening: The case of glycogen synthase kinase 3β inhibitors PV Karpov, DI Osolodkin, II Baskin, VA Palyulin, NS Zefirov Bioorganic & medicinal chemistry letters 21 (22), 6728-6731, 2011 | 29 | 2011 |
| Prokineticin receptor-1 signaling inhibits dose-and time-dependent anthracycline-induced cardiovascular toxicity via myocardial and vascular protection A Gasser, YW Chen, A Audebrand, A Daglayan, M Charavin, B Escoubet, ... Cardio Oncology 1 (1), 84-102, 2019 | 20 | 2019 |
| Prediction of rate constants of SN 2 reactions by the multicomponent QSPR method AA Kravtsov, PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 440 (2), 299, 2011 | 20 | 2011 |
| Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and Special Sessions P Karpov, G Godin, IV Tetko Springer International Publishing, 2019 | 17 | 2019 |
| Prediction of the preferable mechanism of nucleophilic substitution at saturated carbon atom and prognosis of S N 1 rate constants by … AA Kravtsov, PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 441, 314-317, 2011 | 16 | 2011 |
| “Bimolecular” QSPR: Estimation of the solvation free energy of organic molecules in different solvents AA Kravtsov, PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 414, 128-131, 2007 | 15 | 2007 |
| Structure-activity relationship modeling and experimental validation of the imidazolium and pyridinium based ionic liquids as potential antibacterials of MDR Acinetobacter … IV Semenyuta, MM Trush, VV Kovalishyn, SP Rogalsky, DM Hodyna, ... International Journal of Molecular Sciences 22 (2), 563, 2021 | 12 | 2021 |
| Transformer-CNN: Swiss knife for QSAR modeling and interpretation. J Cheminform 12: 17 P Karpov, G Godin, IV Tetko | 9 | 2020 |
| Artificial Neural Networks and Machine Learning–ICANN 2019: Deep Learning: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019 … IV Tetko, V Kůrková, P Karpov, F Theis Springer Nature, 2019 | 9 | 2019 |
| One-class approach: models for virtual screening of non-nucleoside HIV-1 reverse transcriptase inhibitors based on the concept of continuous molecular fields PV Karpov, II Baskin, NI Zhokhova, MB Nawrozkij, AN Zefirov, ... Russian Chemical Bulletin 60, 2418-2424, 2011 | 9 | 2011 |
| Virtual screening based on one-class classification PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 437, 107-111, 2011 | 9 | 2011 |
| Focused library generator: case of Mdmx inhibitors Z Xia, P Karpov, G Popowicz, IV Tetko Journal of Computer-Aided Molecular Design 34 (7), 769-782, 2020 | 8 | 2020 |
| International conference on artificial neural networks P Karpov, G Godin, IV Tetko Springer, Cham,, 2019 | 8 | 2019 |
| Method of continuous molecular fields in the one-class classification task PV Karpov, II Baskin, NI Zhokhova, NS Zefirov Doklady Chemistry 440 (2), 263, 2011 | 8 | 2011 |
