| Learning to make chemical predictions: the interplay of feature representation, data, and machine learning methods M Haghighatlari, J Li, F Heidar-Zadeh, Y Liu, X Guan, T Head-Gordon Chem 6 (7), 1527-1542, 2020 | 81 | 2020 |
| Newtonnet: A newtonian message passing network for deep learning of interatomic potentials and forces M Haghighatlari, J Li, X Guan, O Zhang, A Das, CJ Stein, F Heidar-Zadeh, ... Digital Discovery 1 (3), 333-343, 2022 | 72 | 2022 |
| AutoDetect-mNP: an unsupervised machine learning algorithm for automated analysis of transmission electron microscope images of metal nanoparticles X Wang, J Li, HD Ha, JC Dahl, JC Ondry, I Moreno-Hernandez, ... Jacs Au 1 (3), 316-327, 2021 | 60 | 2021 |
| Multiresolution 3D-DenseNet for Chemical Shift Prediction in NMR Crystallography S Liu, J Li, KC Bennett, B Ganoe, T Stauch, M Head-Gordon, A Hexemer, ... The journal of physical chemistry letters 10 (16), 4558-4565, 2019 | 49 | 2019 |
| Accurate prediction of chemical shifts for aqueous protein structure on “Real World” data J Li, KC Bennett, Y Liu, MV Martin, T Head-Gordon Chemical Science 11 (12), 3180-3191, 2020 | 29 | 2020 |
| IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States JMC Teixeira, ZH Liu, A Namini, J Li, RM Vernon, M Krzeminski, ... The Journal of Physical Chemistry A 126 (35), 5985-6003, 2022 | 17 | 2022 |
| Functionality proportion and corresponding stability study of multivariate metal-organic frameworks J Li, Y Wang, Y Yu, Q Li Chinese Chemical Letters 29 (6), 837-841, 2018 | 17 | 2018 |
| Learning to evolve structural ensembles of unfolded and disordered proteins using experimental solution data O Zhang, M Haghighatlari, J Li, ZH Liu, A Namini, J Teixeira, ... The Journal of Chemical Physics 158 (17), 2023 | 13 | 2023 |
| A benchmark dataset for Hydrogen Combustion X Guan, A Das, CJ Stein, F Heidar-Zadeh, L Bertels, M Liu, ... Scientific data 9 (1), 215, 2022 | 10 | 2022 |
| Protein Dynamics to Define and Refine Disordered Protein Ensembles PM Naullage, M Haghighatlari, A Namini, JMC Teixeira, J Li, O Zhang, ... The Journal of Physical Chemistry B 126 (9), 1885-1894, 2022 | 8 | 2022 |
| Efficient calculation of NMR shielding constants using composite method approximations and locally dense basis sets J Liang, Z Wang, J Li, J Wong, X Liu, B Ganoe, T Head-Gordon, ... Journal of Chemical Theory and Computation 19 (2), 514-523, 2023 | 7 | 2023 |
| Learning correlations between internal coordinates to improve 3d cartesian coordinates for proteins J Li, O Zhang, S Lee, A Namini, ZH Liu, JMC Teixeira, JD Forman-Kay, ... Journal of chemical theory and computation 19 (14), 4689-4700, 2023 | 6 | 2023 |
| Leak Proof PDBBind: A Reorganized Dataset of Protein-Ligand Complexes for More Generalizable Binding Affinity Prediction J Li, X Guan, O Zhang, K Sun, Y Wang, D Bagni, T Head-Gordon arXiv preprint arXiv:2308.09639, 2023 | 5 | 2023 |
| An in-silico NMR laboratory for nuclear magnetic shieldings computed via finite fields: Exploring nucleus-specific renormalizations of MP2 and MP3 J Wong, B Ganoe, X Liu, T Neudecker, J Lee, J Liang, Z Wang, J Li, ... The Journal of chemical physics 158 (16), 2023 | 3 | 2023 |
| Local disordered region sampling (LDRS) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments ZH Liu, JMC Teixeira, O Zhang, TE Tsangaris, J Li, CC Gradinaru, ... Bioinformatics 39 (12), btad739, 2023 | 2 | 2023 |
| Molecular magnetisabilities computed via finite fields: assessing alternatives to MP2 and revisiting magnetic exaltations in aromatic and antiaromatic species T Stauch, B Ganoe, J Wong, J Lee, A Rettig, J Liang, J Li, E Epifanovsky, ... Molecular Physics 119 (21-22), e1990426, 2021 | 2 | 2021 |
| SPyCi-PDB: A modular command-line interface for back-calculating experimental datatypes of protein structures. ZH Liu, O Zhang, JM Teixeira, J Li, T Head-Gordon, JD Forman-Kay Journal of Open Source Software 8 (85), 4861, 2023 | 1 | 2023 |
| Highly Accurate Prediction of NMR Chemical Shifts from Low-Level Quantum Mechanics Calculations Using Machine Learning J Li, J Liang, Z Wang, AL Ptaszek, X Liu, B Ganoe, M Head-Gordon, ... Journal of Chemical Theory and Computation, 2024 | | 2024 |
| Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design J Li, O Zhang, Y Wang, K Sun, X Guan, D Bagni, M Haghighatlari, ... arXiv preprint arXiv:2110.01806, 2021 | | 2021 |
| Reinforcement Learning with Real-time Docking of 3D Structures to Cover Chemical Space: Mining for Potent SARS-CoV-2 Main Protease Inhibitors J Li, O Zhang, FL Kearns, M Haghighatlari, C Parks, X Guan, I Leven, ... arXiv preprint arXiv:2110.01806, 2021 | | 2021 |
