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Pavel Karpov
Pavel Karpov
Researcher, Moscow State University, Chemistry department
Verified email at qsar.chem.msu.ru
Title
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Cited by
Year
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
2852020
Transformer-CNN: Swiss knife for QSAR modeling and interpretation
P Karpov, G Godin, IV Tetko
Journal of cheminformatics 12, 1-12, 2020
1882020
A transformer model for retrosynthesis
P Karpov, G Godin, IV Tetko
International Conference on Artificial Neural Networks, 817-830, 2019
1262019
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
902021
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
772019
Augmentation is what you need!
IV Tetko, P Karpov, E Bruno, TB Kimber, G Godin
International Conference on Artificial Neural Networks, 831-835, 2019
432019
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
292011
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
202019
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
202011
Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and Special Sessions
P Karpov, G Godin, IV Tetko
Springer International Publishing, 2019
182019
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
162011
“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
162007
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
122021
Transformer-CNN: Swiss knife for QSAR modeling and interpretation. J Cheminform 12: 17
P Karpov, G Godin, IV Tetko
92020
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
92019
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
92011
Virtual screening based on one-class classification
PV Karpov, II Baskin, VA Palyulin, NS Zefirov
Doklady Chemistry 437, 107-111, 2011
92011
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
82020
International conference on artificial neural networks
P Karpov, G Godin, IV Tetko
Springer, Cham,, 2019
82019
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
82011
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