Gianni De Fabritiis

Orcid: 0000-0003-3913-4877

According to our database1, Gianni De Fabritiis authored at least 50 papers between 1999 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials.
J. Chem. Inf. Model., March, 2024

PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data.
J. Chem. Inf. Model., 2024

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations.
CoRR, 2024

2023
NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics.
J. Chem. Inf. Model., September, 2023

Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series.
J. Chem. Inf. Model., April, 2023

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.
CoRR, 2023

Machine Learning Small Molecule Properties in Drug Discovery.
CoRR, 2023

Top-down machine learning of coarse-grained protein force-fields.
CoRR, 2023

TorchRL: A data-driven decision-making library for PyTorch.
CoRR, 2023

Binding-and-folding recognition of an intrinsically disordered protein using online learning molecular dynamics.
CoRR, 2023

TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
PlayMolecule Glimpse: Understanding Protein-Ligand Property Predictions with Interpretable Neural Networks.
J. Chem. Inf. Model., 2022

Machine Learning Coarse-Grained Potentials of Protein Thermodynamics.
CoRR, 2022

SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials.
CoRR, 2022

TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials.
CoRR, 2022

NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics.
CoRR, 2022

Equivariant Transformers for Neural Network based Molecular Potentials.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Guided Exploration with Proximal Policy Optimization using a Single Demonstration.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
SkeleDock: A Web Application for Scaffold Docking in PlayMolecule.
J. Chem. Inf. Model., 2020

Generative Models for Molecular Design.
J. Chem. Inf. Model., 2020

JCIM Special Issue on Generative Models for Molecular Design.
J. Chem. Inf. Model., 2020

PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulations.
J. Chem. Inf. Model., 2020

Small Molecule Modulation of Intrinsically Disordered Proteins Using Molecular Dynamics Simulations.
J. Chem. Inf. Model., 2020

TorchMD: A deep learning framework for molecular simulations.
CoRR, 2020

Guided Exploration with Proximal Policy Optimization using a Single Demonstration.
CoRR, 2020

NAPPO: Modular and scalable reinforcement learning in pytorch.
CoRR, 2020

2019
Shape-Based Generative Modeling for de Novo Drug Design.
J. Chem. Inf. Model., 2019

PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks.
J. Chem. Inf. Model., 2019

A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning.
J. Chem. Inf. Model., 2019

LigVoxel: inpainting binding pockets using 3D-convolutional neural networks.
Bioinform., 2019

PlayMolecule BindScope: large scale CNN-based virtual screening on the web.
Bioinform., 2019

2018
Molecular-Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors.
J. Chem. Inf. Model., 2018

KDEEP: Protein-Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks.
J. Chem. Inf. Model., 2018

2017
PlayMolecule ProteinPrepare: A Web Application for Protein Preparation for Molecular Dynamics Simulations.
J. Chem. Inf. Model., July, 2017

Dimensionality reduction methods for molecular simulations.
CoRR, 2017

DeepSite: protein-binding site predictor using 3D-convolutional neural networks.
Bioinform., 2017

2015
AceCloud: Molecular Dynamics Simulations in the Cloud.
J. Chem. Inf. Model., 2015

Insights from Fragment Hit Binding Assays by Molecular Simulations.
J. Chem. Inf. Model., 2015

2014
Reranking Docking Poses Using Molecular Simulations and Approximate Free Energy Methods.
J. Chem. Inf. Model., 2014

Kinetic Characterization of Fragment Binding in AmpC β-Lactamase by High-Throughput Molecular Simulations.
J. Chem. Inf. Model., 2014

2013
Computational Modeling of an Epidermal Growth Factor Receptor Single-Mutation Resistance to Cetuximab in Colorectal Cancer Treatment.
J. Chem. Inf. Model., 2013

2011
Swan: A tool for porting CUDA programs to OpenCL.
Comput. Phys. Commun., 2011

2010
Induced Effects of Sodium Ions on Dopaminergic G-Protein Coupled Receptors.
PLoS Comput. Biol., 2010

High-Throughput All-Atom Molecular Dynamics Simulations Using Distributed Computing.
J. Chem. Inf. Model., 2010

Statistical Analysis of Global Connectivity and Activity Distributions in Cellular Networks.
J. Comput. Biol., 2010

Distributed computing as a virtual supercomputer: Tools to run and manage large-scale BOINC simulations.
Comput. Phys. Commun., 2010

2007
Performance of the Cell processor for biomolecular simulations.
Comput. Phys. Commun., 2007

2006
A stochastic Trotter integration scheme for dissipative particle dynamics.
Math. Comput. Simul., 2006

Coupled applications on distributed resources.
Comput. Phys. Commun., 2006

1999
Performance evaluation of a FD-TD parallel code for microwave ovens design.
Proceedings of the Parallel Computing: Fundamentals & Applications, 1999


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