Gianni De Fabritiis
- Navigating protein landscapes with a machine-learned transferable coarse-grained model
2023/10/27 by Nicholas E. Charron, Charron, Nicholas E., Felix Musil +40 · 3 voices · 23 citations
Biochemistry, Genetics and Molecular Biology · Materials Science · Mathematics · Physics and Astronomy · #Biological Physics (physics.bio-ph) #Biomolecules (q-bio.BM) #Block Copolymer Self-Assembly #Chemical Physics (physics.chem-ph) #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (stat.ML) #Machine Learning in Materials Science #Protein Structure and Dynamics #physics.bio-ph #physics.chem-ph #q-bio.BM #stat.ML
- TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials
2022/02/05 by Philipp Thölke, Gianni De Fabritiis, Thölke, Philipp +1 · 20 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Artificial Intelligence (cs.AI) #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Protein Structure and Dynamics
- OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials
2023/10/04 by Peter Eastman, Raimondas Galvelis, Eastman, Peter +44 · 18 citations
Materials Science · Biochemistry, Genetics and Molecular Biology · Decision Sciences · #Machine Learning in Materials Science #Protein Structure and Dynamics #Scientific Computing and Data Management
- OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials
2023/12/28 by Peter Eastman, Raimondas Galvelis, Raúl P. Peláez +22 · 1 voice · 15 citations
Biochemistry, Genetics and Molecular Biology · Materials Science · #Enzyme Structure and Function #Machine Learning in Materials Science #Protein Structure and Dynamics
- TorchRL: A data-driven decision-making library for PyTorch
2023/06/01 by Albert Bou, Matteo Bettini, Bou, Albert +13 · 13 citations
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
- ACEMD: Accelerating bio-molecular dynamics in the microsecond time-scale
2009/02/05 by M J Harvey, Harvey, M. J., G. Giupponi +3 · 4 citations
Chemistry · #thermodynamics and calorimetric analyses
- NNP/MM: Accelerating molecular dynamics simulations with machine learning potentials and molecular mechanic
2022/01/20 by Raimondas Galvelis, Alejandro Varela‐Rial, Galvelis, Raimondas +13 · 5 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Materials Science · #Biological Physics (physics.bio-ph) #Biomolecules (q-bio.BM) #Computational Physics (physics.comp-ph) #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Fuel Cells and Related Materials #Machine Learning (cs.LG) #Machine Learning in Materials Science #Protein Structure and Dynamics
- ACEGEN: Reinforcement learning of generative chemical agents for drug discovery
2024/05/07 by Albert Bou, Bou, Albert, Morgan Thomas +23 · 7 citations
Computer Science · #Artificial Intelligence (cs.AI) #Biomolecules (q-bio.BM) #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Machine learning coarse-grained potentials of protein thermodynamics
2023/09/15 by Maciej Majewski, Adrià Pérez, Philipp Thölke +7 · 1 voice · 3 citations
Materials Science · Biochemistry, Genetics and Molecular Biology · #Machine Learning in Materials Science #Protein Structure and Dynamics #Enzyme Structure and Function
- Machine Learning Small Molecule Properties in Drug Discovery
2023/08/02 by Nikolai Schapin, Maciej Majewski, Schapin, Nikolai +7 · 2 citations
Computer Science · Environmental Science · Materials Science · #Biomolecules (q-bio.BM) #Chemistry and Chemical Engineering #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Quantitative Methods (q-bio.QM)
- Dimensionality reduction methods for molecular simulations
2017/10/29 by Stefan Doerr, Igor Ariz, Doerr, Stefan +4 · 1 citation
Biochemistry, Genetics and Molecular Biology · Materials Science · #Bioinformatics and Genomic Networks #Biomolecules (q-bio.BM) #Enzyme Structure and Function #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Protein Structure and Dynamics
- Enhancing Protein-Ligand Binding Affinity Predictions using Neural Network Potentials
2024/01/29 by Francesc Sabanés Zariquiey, Zariquiey, Francesc Sabanes, Raimondas Galvelis +9 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Physical sciences #Monoclonal and Polyclonal Antibodies Research #Quantitative Methods (q-bio.QM) #vaccines and immunoinformatics approaches
- Top-down machine learning of coarse-grained protein force-fields
2023/06/20 by Carles Navarro, Navarro, Carles, M. W. Majewski +3 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Biomolecules (q-bio.BM) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Protein Structure and Dynamics #Software Engineering Research
- Machine Learning Potentials: A Roadmap Toward Next-Generation Biomolecular Simulations
2024/08/17 by Gianni De Fabritiis, De Fabritiis, Gianni · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Genetics, Bioinformatics, and Biomedical Research #Bioinformatics and Genomic Networks #Computational Drug Discovery Methods
- Speak to a Protein: An Interactive Multimodal Co-Scientist for Protein Analysis
2025/10/01 by Carles Navarro, M. Torrens, Navarro, Carles +8 · 3 voices
Materials Science · Computer Science · Decision Sciences · #Machine Learning in Materials Science #Data Visualization and Analytics #Scientific Computing and Data Management