Kinetic Characterization of Fragment Binding in AmpC β-Lactamase by High-Throughput Molecular Simulations. - Paola Bisignano; Stefan Doerr; Matt J. Harvey; Angelo D. Favia; Andrea Cavalli; Gianni De Fabritiis (J. Chem. Inf. Model., 2014)

DeepSite: protein-binding site predictor using 3D-convolutional neural networks. - José Jiménez; Stefan Doerr; Gerard Martínez-Rosell; Alexander S. Rose; Gianni De Fabritiis (Bioinform., 2017)

Dimensionality reduction methods for molecular simulations. - Stefan Doerr; Igor Ariz; Matthew J. Harvey; Gianni De Fabritiis (CoRR, 2017)

Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling. - Francisco José Romero-Ramírez; Rafael M. Navarro-Cerrillo; M. Ángeles Varo-Martínez; Jose Luis Quero; Stefan Doerr; Rocío Hernández-Clemente (Int. J. Appl. Earth Obs. Geoinformation, 2018)

A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning. - Raimondas Galvelis; Stefan Doerr; João M. Damas; Matt J. Harvey; Gianni De Fabritiis (J. Chem. Inf. Model., 2019)

TorchMD: A deep learning framework for molecular simulations. - Stefan Doerr; Maciej Majewski; Adrià Pérez; Andreas Krämer; Cecilia Clementi; Frank Noé; Toni Giorgino; Gianni De Fabritiis (CoRR, 2020)

NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics. - Raimondas Galvelis; Alejandro Varela-Rial; Stefan Doerr; Roberto Fino; Peter K. Eastman; Thomas E. Markland; John D. Chodera; Gianni De Fabritiis (CoRR, 2022)

Machine Learning Coarse-Grained Potentials of Protein Thermodynamics. - Maciej Majewski; Adrià Pérez; Philipp Thölke; Stefan Doerr; Nicholas E. Charron; Toni Giorgino; Brooke E. Husic; Cecilia Clementi; Frank Noé; Gianni De Fabritiis (CoRR, 2022)

PlayMolecule Glimpse: Understanding Protein-Ligand Property Predictions with Interpretable Neural Networks. - Alejandro Varela-Rial; Iain Maryanow; Maciej Majewski; Stefan Doerr; Nikolai Schapin; José Jiménez-Luna; Gianni De Fabritiis (J. Chem. Inf. Model., 2022)

NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics. - Raimondas Galvelis; Alejandro Varela-Rial; Stefan Doerr; Roberto Fino; Peter K. Eastman; Thomas E. Markland; John D. Chodera; Gianni De Fabritiis (J. Chem. Inf. Model., 2023)

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations. - Raúl P. Peláez; Guillem Simeon; Raimondas Galvelis; Antonio Mirarchi; Peter K. Eastman; Stefan Doerr; Philipp Thölke; Thomas E. Markland; Gianni De Fabritiis (CoRR, 2024)

PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data. - Mariona Torrens-Fontanals; Panagiotis Tourlas; Stefan Doerr; Gianni De Fabritiis (J. Chem. Inf. Model., 2024)

QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials. - Francesc Sabanés Zariquiey; Stephen E. Farr; Stefan Doerr; Gianni De Fabritiis (J. Chem. Inf. Model., 2025)