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ORCIDThomas E. Markland
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2020 – today
- 2024
[j2]Francesc Sabanés Zariquiey
, Raimondas Galvelis, Emilio Gallicchio, John D. Chodera, Thomas E. Markland, Gianni De Fabritiis:
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. J. Chem. Inf. Model. 64(5): 1481-1485 (2024)- [i6]Raúl P. Peláez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter K. Eastman, Stefan Doerr, Philipp Thölke, Thomas E. Markland, Gianni De Fabritiis:
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. CoRR abs/2402.17660 (2024) - [i5]Peter K. Eastman, Benjamin P. Pritchard, John D. Chodera, Thomas E. Markland:
Nutmeg and SPICE: Models and Data for Biomolecular Machine Learning. CoRR abs/2406.13112 (2024) - [i4]Frank Hu, Michael S. Chen, Grant M. Rotskoff, Matthew W. Kanan, Thomas E. Markland:
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning. CoRR abs/2408.08284 (2024) - 2023
- [j1]Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis:
NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics. J. Chem. Inf. Model. 63(18): 5701-5708 (2023) - [i3]Peter K. Eastman, Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. Abreu, Stephen E. Farr, Emilio Gallicchio, Anton Gorenko, Michael M. Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A. Mitchell, Vijay S. Pande, João P. G. L. M. Rodrigues, Jaime Rodríguez-Guerra, Andrew C. Simmonett, Jason M. Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland:
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. CoRR abs/2310.03121 (2023) - 2022
- [i2]Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis:
NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics. CoRR abs/2201.08110 (2022) - [i1]Peter K. Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton, Yuezhi Mao, John D. Chodera, Benjamin P. Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E. Markland:
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. CoRR abs/2209.10702 (2022)
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