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ORCIDStefan Doerr
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Journal Articles
- 2024
[j7]Mariona Torrens-Fontanals
, Panagiotis Tourlas, Stefan Doerr, Gianni De Fabritiis:
PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data. J. Chem. Inf. Model. 64(3): 584-589 (2024)- 2023
- [j6]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) - 2022
- [j5]Alejandro Varela-Rial, Iain Maryanow, Maciej Majewski, Stefan Doerr, Nikolai Schapin, José Jiménez-Luna, Gianni De Fabritiis:
PlayMolecule Glimpse: Understanding Protein-Ligand Property Predictions with Interpretable Neural Networks. J. Chem. Inf. Model. 62(2): 225-231 (2022) - 2019
- [j4]Raimondas Galvelis, Stefan Doerr, João M. Damas, Matt J. Harvey, Gianni De Fabritiis:
A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning. J. Chem. Inf. Model. 59(8): 3485-3493 (2019) - 2018
- [j3]Francisco José Romero-Ramírez, Rafael M. Navarro-Cerrillo, M. Ángeles Varo-Martínez, Jose Luis Quero, Stefan Doerr, Rocío Hernández-Clemente:
Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling. Int. J. Appl. Earth Obs. Geoinformation 68: 157-167 (2018) - 2017
- [j2]José Jiménez, Stefan Doerr, Gerard Martínez-Rosell, Alexander S. Rose, Gianni De Fabritiis:
DeepSite: protein-binding site predictor using 3D-convolutional neural networks. Bioinform. 33(19): 3036-3042 (2017) - 2014
- [j1]Paola Bisignano, Stefan Doerr, Matt J. Harvey, Angelo D. Favia, Andrea Cavalli, Gianni De Fabritiis:
Kinetic Characterization of Fragment Binding in AmpC β-Lactamase by High-Throughput Molecular Simulations. J. Chem. Inf. Model. 54(2): 362-366 (2014)
Informal and Other Publications
- 2024
- [i5]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) - 2022
- [i4]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) - [i3]Maciej Majewski, Adrià Pérez, Philipp Thölke, Stefan Doerr, Nicholas E. Charron, Toni Giorgino, Brooke E. Husic, Cecilia Clementi, Frank Noé, Gianni De Fabritiis:
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics. CoRR abs/2212.07492 (2022) - 2020
- [i2]Stefan Doerr, Maciej Majewski, Adrià Pérez, Andreas Krämer, Cecilia Clementi, Frank Noé, Toni Giorgino, Gianni De Fabritiis:
TorchMD: A deep learning framework for molecular simulations. CoRR abs/2012.12106 (2020) - 2017
- [i1]Stefan Doerr, Igor Ariz, Matthew J. Harvey, Gianni De Fabritiis:
Dimensionality reduction methods for molecular simulations. CoRR abs/1710.10629 (2017)
Coauthor Index
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