| A transformer model for retrosynthesis P Karpov, G Godin, IV Tetko International Conference on Artificial Neural Networks, 817-830, 2019 | 31 | 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 | 27 | 2011 |
| 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 | 18 | 2011 |
| 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 | 17 | 2019 |
| Transformer-CNN: Swiss knife for QSAR modeling and interpretation P Karpov, G Godin, IV Tetko Journal of Cheminformatics 12 (1), 1-12, 2020 | 15 | 2020 |
| “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 (1), 128-131, 2007 | 15 | 2007 |
| Prediction of the preferable mechanism of nucleophilic substitution at saturated carbon atom and prognosis of SN 1 rate constants by means of QSPR AA Kravtsov, PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 441 (1), 314-317, 2011 | 14 | 2011 |
| 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), 1-11, 2020 | 13 | 2020 |
| 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 (11), 2418-2424, 2011 | 9 | 2011 |
| Virtual screening based on one-class classification PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 437 (2), 107-111, 2011 | 9 | 2011 |
| Augmentation Is What You Need! IV Tetko, P Karpov, E Bruno, TB Kimber, G Godin International Conference on Artificial Neural Networks, 831-835, 2019 | 8 | 2019 |
| 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 | 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 |
| 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 | 6 | 2020 |
| Augmented transformer achieves 97% and 85% for top5 prediction of direct and classical retro-synthesis IV Tetko, P Karpov, R Van Deursen, G Godin arXiv preprint arXiv:2003.02804, 2020 | 5 | 2020 |
| Disorder-free localization in an interacting two-dimensional lattice gauge theory P Karpov, R Verdel, YP Huang, M Schmitt, M Heyl arXiv preprint arXiv:2003.04901, 2020 | 4 | 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 | 4 | 2019 |
| Molecular design of selective ligands of chemokine receptors MN Kurilo, FV Ryzhkov, PV Karpov, EV Radchenko, VA Palyulin, ... Doklady. Biochemistry and biophysics 461 (1), 131, 2015 | 3 | 2015 |
| Transformer-CNN: Fast and Reliable tool for QSAR P Karpov, G Godin, IV Tetko arXiv preprint arXiv:1911.06603, 2019 | 2 | 2019 |
| Neural network modeling of substituent constants on the basis of fragmental descriptors MN Kurilo, PV Karpov, II Baskin, VA Palyulin, NS Zefirov Doklady Chemistry 431 (1), 85-88, 2010 | 1 | 2010 |
