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machine learning potentials  (Molecular Dynamics Inc)

 
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    Molecular Dynamics Inc machine learning potentials
    Machine Learning Potentials, supplied by Molecular Dynamics Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/machine+learning+potentials/learning+machine/pm42277131-331-10-6
    Average 86 stars, based on 1 article reviews
    machine learning potentials - by Bioz Stars, 2026-10
    86/100 stars

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    Article Title: Multiscale Machine Learning Prediction of Infrared Spectra of Solvated Molecules.
    Article Snippet: A.; Pande, V. S.; Rodrigues, J. P.; Rodriguez-Guerra, J.; Simmonett, A. C.; Singh, S.; Swails, J.; Turner, P.; Wang, Y.; Zhang, I.; Chodera, J. D.; De Fabritiis, G.; Markland, T. E. OpenMM 8: molecular dynamics simulation with machine learning potentials.

    Article Title: Cohesin cofactor dosage sets the rate of loop extrusion, rendering genome folding tunable yet vulnerable to genetic disruption.
    Article Snippet: Article PDS5 proteins control genome architecture by limiting the lifetime of cohesin-NIPBL complexes

    Article Title: Making PLUMED Fly: A Tutorial on Optimizing Performance.
    Article Snippet: 2022, 271, 108171. (40) Eastman, P.; et al. OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

    Article Title: plotXVG: Batch Generation of Publication-Quality Graphs from GROMACS Output.
    Article Snippet: 2010, 12, 34− 39. (13) Eastman, P.; et al. OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

    Article Title: Molecular origins of opalescence and phase separation in mAb formulations and their relation to aggregation.
    Article Snippet: Eastman, P. et al. OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

    Article Title: Multipolar electric and magnetic contributions to sum-frequency generation spectra reveal biaxial interfacial water structure.
    Article Snippet: A. Mitchell, V. S. Pande, J. P. Rodrigues, J. Rodriguez-Guerra, A. C. Simmonett, S. Singh, J. Swails, P. Turner, Y. Wang, I. Zhang, J. D. Chodera, G. De Fabritiis, and T. E. Markland, OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials, The Journal of Physical Chemistry B 128, 109 (2024).

    Article Title: CHARMM-GUI Hybrid ML/MM Builder for Hybrid Machine Learning and Molecular Mechanical Modeling and Simulations.
    Article Snippet: A.; Pande, V. S.; Rodrigues, J. P.; Rodriguez-Guerra, J.; Simmonett, A. C.; Singh, S.; Swails, J.; Turner, P.; Wang, Y.; Zhang, I.; Chodera, J. D.; De Fabritiis, G.; Markland, T. E. OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.



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