| Computer-assisted discovery of retinoid X receptor modulating natural products and isofunctional mimetics D Merk, F Grisoni, L Friedrich, E Gelzinyte, G Schneider Journal of Medicinal Chemistry 61 (12), 5442-5447, 2018 | 38 | 2018 |
| Scaffold hopping from synthetic RXR modulators by virtual screening and de novo design D Merk, F Grisoni, L Friedrich, E Gelzinyte, G Schneider MedChemComm 9 (8), 1289-1292, 2018 | 19 | 2018 |
| Neural network activation similarity: a new measure to assist decision making in chemical toxicology TEH Allen, AJ Wedlake, E Gelžinytė, C Gong, JM Goodman, S Gutsell, ... Chemical Science 11 (28), 7335-7348, 2020 | 18 | 2020 |
| ACEpotentials. jl: A Julia implementation of the atomic cluster expansion WC Witt, C van der Oord, E Gelžinytė, T Järvinen, A Ross, JP Darby, ... The Journal of Chemical Physics 159 (16), 2023 | 2 | 2023 |
| wfl Python Toolkit for Creating Machine Learning Interatomic Potentials and Related Atomistic Simulation Workflows E Gelžinytė, S Wengert, TK Stenczel, HH Heenen, K Reuter, G Csányi, ... arXiv preprint arXiv:2306.11421, 2023 | 2 | 2023 |
| Transferable machine learning interatomic potential for bond dissociation energy prediction of drug-like molecule E Gelžinytė, M Öeren, MD Segall, G Csányi | 1 | 2023 |
