CC
Cecilia Clementi
Protein FoldingMolecular Dynamics Simulationphysics.chem-phphysics.comp-phcond-mat.stat-mechModels, Molecularphysics.bio-phstat.MLq-bio.BMcs.LG
On Valency
published · living versionsW_z7bzktsf·v1 · currentpublished
Exploring the World of Lipids with Machine-Learned Coarse-Grained Models
with Aldo S. Pasos-Trejo, Daniel P. Ramirez-Echemendia, Daniel Conde-Torres, D. Peter Tieleman
1 version
W_zkn5w8bg·v1published
Preprints & journals
125 papers in the corpus · 1996–2026A strategic roadmap for an atomistic machine-learning ecosystem2609.39090v2 · Jorg Behler, Michele Ceriotti, Cecilia Clementi et al.2026 · 0 citationsarXiv
Integrative structural modelling reveals the human Mic60-Mic19 subcomplex as a diffusion barrier in mitochondria.42800801 · Nathanail, Evangelia, Rolando, Edoardo, Ruwolt, Max et al.2026 · 0 citationsNature communications. 2026;17(1)
Dynamic states of an MHC class I molecule during peptide exchange.42722689 · Mitlehner, Alexandra, Pasos-Trejo, Aldo S, Becker, Moritz et al.2026 · 0 citationsNature communications. 2026;17(1)
Temperature transferable Machine Learned Coarse Grained model for proteins2606.14111v1 · Jacopo Venturin, Cecilia Clementi2026 · 1 citationarXiv
Introduction to Markov State Modeling of Conformational Dynamics.41873224 · Bowman, Gregory R, Clementi, Cecilia, Huang, Xuhui2026 · 2 citationsJournal of chemical theory and computation. 2026;22(6):2665-2667
Learning data-efficient coarse-grained molecular dynamics from forces and noise.41833980 · Durumeric, Aleksander E P, Chen, Yaoyi, Pasos-Trejo, Aldo S et al.2026 · 6 citationsNature communications. 2026;17(1)
Non-equilibrium generalized Langevin equation for multi-dimensional observables2603.09850v1 · Benjamin J. A. H'ery, Lucas Tepper, Andrea Guljas et al.2026 · 0 citationsarXiv
Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models2602.16634v2 · Yu Xie, Ludwig Winkler, Lixin Sun et al.2026 · 0 citationsarXiv
Extending the range of graph neural networks with global encodings.41708620 · Caruso, Alessandro, Venturin, Jacopo, Giambagli, Lorenzo et al.2026 · 6 citationsNature communications. 2026;17(1):1855
Integrative modelling reveals the structure of the human Mic60-Mic19 subcomplex and its role as a diffusion barrier in mitochondria10.64898/2026.01.30.702776v1 · Nathanail, E., Rolando, E., Ruwolt, M. et al.2026 · 1 citationbioRxiv
Cut or bind? Antigen-specific processing mechanisms define CD4+ T cell immunodominant epitopes for SARS-CoV-2 S and N proteins.41291785 · Álvaro-Benito, Miguel, Abualrous, Esam T, Lingel, Holger et al.2025 · 1 citationGenome medicine. 2025;17(1):147
Peering inside the black box by learning the relevance of many-body functions in neural network potentials.41214002 · Bonneau, Klara, Lederer, Jonas, Templeton, Clark et al.2025 · 9 citationsNature communications. 2025;16(1):9898
Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes.41065153 · Chen, Michael S, Robledo, Alan, Schäfer, Christian et al.2025 · 3 citationsThe Journal of chemical physics. 2025;163(14)
Operator forces for coarse-grained molecular dynamics.40923543 · Klein, Leon, Kelkar, Atharva, Durumeric, Aleksander et al.2025 · 5 citationsThe Journal of chemical physics. 2025;163(10)
Scalable emulation of protein equilibrium ensembles with generative deep learning.40638710 · Lewis, Sarah, Hempel, Tim, Jiménez-Luna, José et al.2025 · 346 citationsScience (New York, N.Y.). 2025;389(6761):eadv9817
Navigating protein landscapes with a machine-learned transferable coarse-grained model.40681718 · Charron, Nicholas E, Bonneau, Klara, Pasos-Trejo, Aldo S et al.2025 · 70 citationsNature chemistry. 2025;17(8):1284-1292
The need to implement FAIR principles in biomolecular simulations.40175561 · Amaro, Rommie E, Åqvist, Johan, Bahar, Ivet et al.2026 · 76 citationsNature methods. 2025;22(4):641-645
Extending the RANGE of Graph Neural Networks: Relaying Attention Nodes for Global Encoding2502.13797v2 · Alessandro Caruso, Jacopo Venturin, Lorenzo Giambagli et al.2025 · 6 citationsarXiv
Accurate nuclear quantum statistics on machine-learned classical effective potentials.39352405 · Zaporozhets, Iryna, Musil, Félix, Kapil, Venkat et al.2024 · 9 citationsThe Journal of chemical physics. 2024;161(13)
Peering inside the black box: Learning the relevance of many-body functions in Neural Network potentials2407.04526v1 · Klara Bonneau, Jonas Lederer, Clark Templeton et al.2024 · 7 citationsarXiv
Structure prediction of protein-ligand complexes from sequence information with Umol.38806453 · Bryant, Patrick, Kelkar, Atharva, Guljas, Andrea et al.2024 · 85 citationsNature communications. 2024;15(1):4536
Lattice matched heterogeneous nucleation eliminate defective buried interface in halide perovskites2405.11599v1 · Paramvir Ahlawat, Cecilia Clementi, Felix Musil et al.2024 · 1 citationarXiv
T cell interaction partners of DHHC2010.1101/2024.02.14.580290v1 · Haxhiraj, D., Kuropka, B., Brencher, E. et al.2024 · 0 citationsbioRxiv
Decoding of T cell immunodominance patterns by an integrated mechanistic approach10.1101/2024.01.10.574975v2 · Alvaro-Benito, M., Abualrous, E. T., Lingel, H. et al.2024 · 1 citationbioRxiv
The role of an amphiphilic helix and transmembrane region in the efficient acylation of the M2 protein from influenza virus.37919373 · Meng, Xiaorong, Templeton, Clark, Clementi, Cecilia et al.2023 · 5 citationsScientific reports. 2023;13(1):18928
Machine learning coarse-grained potentials of protein thermodynamics.37714883 · Majewski, Maciej, Pérez, Adrià, Thölke, Philipp et al.2023 · 122 citationsNature communications. 2023;14(1):5739
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics.37688551 · Arts, Marloes, Garcia Satorras, Victor, Huang, Chin-Wei et al.2023 · 92 citationsJournal of chemical theory and computation. 2023;19(18):6151-6159
Multibody Terms in Protein Coarse-Grained Models: A Top-Down Perspective.37499123 · Zaporozhets, Iryna, Clementi, Cecilia2023 · 8 citationsThe journal of physical chemistry. B. 2023;127(31):6920-6927
EnGens: a computational framework for generation and analysis of representative protein conformational ensembles.37163076 · Conev, Anja, Rigo, Mauricio Menagatti, Devaurs, Didier et al.2026 · 28 citationsbioRxiv : the preprint server for biology. 2023
Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics.37079800 · Krämer, Andreas, Durumeric, Aleksander E P, Charron, Nicholas E et al.2023 · 37 citationsThe journal of physical chemistry letters. 2023;14(17):3970-3979
Machine learned coarse-grained protein force-fields: Are we there yet?36731338 · Durumeric, Aleksander E P, Charron, Nicholas E, Templeton, Clark et al.2023 · 81 citationsCurrent opinion in structural biology. 2023;79:102533
Flow-Matching: Efficient Coarse-Graining of Molecular Dynamics without Forces.36668906 · Köhler, Jonas, Chen, Yaoyi, Krämer, Andreas et al.2023 · 66 citationsJournal of chemical theory and computation. 2023;19(3):942-952
Slicing and Dicing: Optimal Coarse-Grained Representation to Preserve Molecular Kinetics.36844497 · Yang, Wangfei, Templeton, Clark, Rosenberger, David et al.2023 · 24 citationsACS central science. 2023;9(2):186-196
Skipping the Replica Exchange Ladder with Normalizing Flows.36484770 · Invernizzi, Michele, Krämer, Andreas, Clementi, Cecilia et al.2022 · 32 citationsThe journal of physical chemistry letters. 2022;13(50):11643-11649
Deep learning to decompose macromolecules into independent Markovian domains.36402768 · Mardt, Andreas, Hempel, Tim, Clementi, Cecilia et al.2022 · 26 citationsNature communications. 2022;13(1):7101
Quantum dynamics using path integral coarse-graining.36379765 · Musil, Félix, Zaporozhets, Iryna, Noé, Frank et al.2022 · 47 citationsThe Journal of chemical physics. 2022;157(18):181102
Fast track to structural biology.34707232 · Clementi, Cecilia2021 · 6 citationsNature chemistry. 2021;13(11):1032-1034
Introduction: Machine Learning at the Atomic Scale.34428897 · Ceriotti, Michele, Clementi, Cecilia, Anatole von Lilienfeld, O2022 · 63 citationsChemical reviews. 2021;121(16):9719-9721
Machine Learning Implicit Solvation for Molecular Dynamics2106.07492v2 · Yaoyi Chen, Andreas Kramer, Nicholas E. Charron et al.2021 · 76 citationsJ. Chem. Phys. 155, 084101 (2021)
Unsupervised Learning Methods for Molecular Simulation Data.33945269 · Glielmo, Aldo, Husic, Brooke E, Rodriguez, Alex et al.2022 · 403 citationsChemical reviews. 2021;121(16):9722-9758
Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire.36090450 · Lin, Xingcheng, George, Jason T, Schafer, Nicholas P et al.2022 · 55 citationsNature computational science. 2021;1(5):362-373
Machine learning meets chemical physics.33940847 · Ceriotti, Michele, Clementi, Cecilia, Anatole von Lilienfeld, O2021 · 53 citationsThe Journal of chemical physics. 2021;154(16):160401
Multi-body effects in a coarse-grained protein force field.33940848 · Wang, Jiang, Charron, Nicholas, Husic, Brooke et al.2021 · 62 citationsThe Journal of chemical physics. 2021;154(16):164113
TorchMD: A Deep Learning Framework for Molecular Simulations.33729795 · Doerr, Stefan, Majewski, Maciej, Pérez, Adrià et al.2021 · 230 citationsJournal of chemical theory and computation. 2021;17(4):2355-2363
Spectral Properties of Effective Dynamics from Conditional Expectations.33494443 · Nüske, Feliks, Koltai, Péter, Boninsegna, Lorenzo et al.2021 · 10 citationsEntropy (Basel, Switzerland). 2021;23(2)
Surveying biomolecular frustration at atomic resolution.33230150 · Chen, Mingchen, Chen, Xun, Schafer, Nicholas P et al.2020 · 84 citationsNature communications. 2020;11(1):5944
Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes.33184174 · Abella, Jayvee R, Antunes, Dinler, Jackson, Kyle et al.2020 · 28 citationsProceedings of the National Academy of Sciences of the United States of America. 2020;117(48):30610-30618
Extensible and Scalable Adaptive Sampling on Supercomputers.33170696 · Hruska, Eugen, Balasubramanian, Vivekanandan, Lee, Hyungro et al.2021 · 20 citationsJournal of chemical theory and computation. 2020;16(12):7915-7925
Coarse Graining Molecular Dynamics with Graph Neural Networks2007.11412v3 · Brooke E. Husic, Nicholas E. Charron, Dominik Lemm et al.2020 · 202 citationsarXiv
Large-Scale Structure-Based Prediction of Stable Peptide Binding to Class I HLAs Using Random Forests.32793224 · Abella, Jayvee R, Antunes, Dinler A, Clementi, Cecilia et al.2021 · 15 citationsFrontiers in immunology. 2020;11:1583
Career total: at least 196 works. 125 are in this corpus.Showing the 50 most recent.
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