| Trade-off predictivity and explainability for machine-learning powered predictive toxicology: An in-depth investigation with Tox21 data sets L Wu, R Huang, IV Tetko, Z Xia, J Xu, W Tong Chemical research in toxicology 34 (2), 541-549, 2021 | 50 | 2021 |
| 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 | 13 | 2021 |
| Anti-MRSA drug discovery by ligand-based virtual screening and biological evaluation X Lian, Z Xia, X Li, P Karpov, H Jin, IV Tetko, J Xia, S Wu Bioorganic Chemistry 114, 105042, 2021 | 10 | 2021 |
| 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 | 10 | 2020 |
| Computational models for the classification of mPGES-1 inhibitors with fingerprint descriptors Z Xia, A Yan Molecular Diversity 21, 661-675, 2017 | 9 | 2017 |
| Computer modeling in predicting the bioactivity of human 5-lipoxygenase inhibitors M Zhang, Z Xia, A Yan Molecular diversity 21, 235-246, 2017 | 5 | 2017 |
| What features of ligands are relevant to the opening of cryptic pockets in drug targets? Z Xia, P Karpov, G Popowicz, M Sattler, IV Tetko Informatics 9 (1), 8, 2022 | 2 | 2022 |
| The state-of-the-art machine learning model for Plasma Protein Binding Prediction: computational modeling with OCHEM and experimental validation Z Han, Z Xia, J Xia, IV Tetko, S Wu European Journal of Pharmaceutical Sciences 204, 106946, 2025 | | 2025 |
| In silico structure-based approaches to design Mdmx inhibitors Z Xia Technische Universität München, 2022 | | 2022 |
Igor V. TetkoBIGCHEM GmbH & Helmholtz MunichVerified email at helmholtz-munich.de