| 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 | 100 | 2021 |
| Comparative study of multitask toxicity modeling on a broad chemical space S Sosnin, D Karlov, IV Tetko, MV Fedorov Journal of chemical information and modeling 59 (3), 1062-1072, 2018 | 94 | 2018 |
| 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 | 78 | 2019 |
| graphDelta: MPNN scoring function for the affinity prediction of protein–ligand complexes DS Karlov, S Sosnin, MV Fedorov, P Popov ACS omega 5 (10), 5150-5159, 2020 | 75 | 2020 |
| Chemical space exploration guided by deep neural networks DS Karlov, S Sosnin, IV Tetko, MV Fedorov RSC advances 9 (9), 5151-5157, 2019 | 50 | 2019 |
| Real-time detection of hogweed: UAV platform empowered by deep learning A Menshchikov, D Shadrin, V Prutyanov, D Lopatkin, S Sosnin, ... IEEE Transactions on Computers 70 (8), 1175-1188, 2021 | 47 | 2021 |
| Transformer-based artificial neural networks for the conversion between chemical notations L Krasnov, I Khokhlov, MV Fedorov, S Sosnin Scientific Reports 11 (1), 14798, 2021 | 33* | 2021 |
| Machine learning to predict retention time of small molecules in nano-HPLC S Osipenko, I Bashkirova, S Sosnin, O Kovaleva, M Fedorov, E Nikolaev, ... Analytical and Bioanalytical Chemistry 412, 7767-7776, 2020 | 33 | 2020 |
| Image2SMILES: Transformer‐based molecular optical recognition engine I Khokhlov, L Krasnov, MV Fedorov, S Sosnin Chemistry‐Methods 2 (1), e202100069, 2022 | 32 | 2022 |
| Exploring chemical reaction space with reaction difference fingerprints and parametric t-SNE M Andronov, MV Fedorov, S Sosnin ACS omega 6 (45), 30743-30751, 2021 | 26 | 2021 |
| Recommender systems in antiviral drug discovery EA Sosnina, S Sosnin, AA Nikitina, I Nazarov, DI Osolodkin, MV Fedorov ACS omega 5 (25), 15039-15051, 2020 | 25 | 2020 |
| Hydrogen/deuterium exchange aiding compound identification for LC-MS and MALDI imaging lipidomics Y Kostyukevich, G Vladimirov, E Stekolschikova, D Ivanov, A Yablokov, ... Analytical chemistry 91 (21), 13465-13474, 2019 | 22 | 2019 |
| 3D matters! 3D-RISM and 3D convolutional neural network for accurate bioaccumulation prediction S Sosnin, M Misin, DS Palmer, MV Fedorov Journal of Physics: Condensed Matter 30 (32), 32LT03, 2018 | 20 | 2018 |
| PyFragMS─ A Web Tool for the Investigation of the Collision-Induced Fragmentation Pathways Y Kostyukevich, S Sosnin, S Osipenko, O Kovaleva, L Rumiantseva, ... ACS omega 7 (11), 9710-9719, 2022 | 7 | 2022 |
| Improvement of multi-task learning by data enrichment: application for drug discovery EA Sosnina, S Sosnin, MV Fedorov Journal of Computer-Aided Molecular Design 37 (4), 183-200, 2023 | 6 | 2023 |
| Influence of descriptor implementation on compound ranking based on multiparameter assessment EA Sosnina, DI Osolodkin, EV Radchenko, S Sosnin, VA Palyulin Journal of Chemical Information and Modeling 58 (5), 1083-1093, 2018 | 6 | 2018 |
| System for prediction of pharmacokinetic properties and toxicity of drug compounds EV Radchenko, PV Karpov, SB Sosnin, AS Dyabina, EA Sosnina, ... XX Mendeleev Congress on general and applied chemistry 4, 424, 2016 | 6 | 2016 |
| Identifying differences in the performance of machine learning models for off-targets trained on publicly available and proprietary data sets A Smajić, I Rami, S Sosnin, GF Ecker Chemical Research in Toxicology 36 (8), 1300-1312, 2023 | 5 | 2023 |
| BigSolDB: Solubility Dataset of Compounds in Organic Solvents and Water in a Wide Range of Temperatures L Krasnov, S Mikhaylov, M Fedorov, S Sosnin | 3 | 2023 |
| The macrocycle inhibitor landscape of SLC‐transporter N Granulo, S Sosnin, D Digles, GF Ecker Molecular Informatics, e202300287, 2024 | 1 | 2024 |
Igor V. TetkoBIGCHEM GmbH & Helmholtz Munich在 helmholtz-munich.de 的电子邮件经过验证
