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Eric Beyerle
Eric Beyerle
Postdoctoral Associate, IPST, University of Maryland
Verified email at umd.edu - Homepage
Title
Cited by
Cited by
Year
Driving and characterizing nucleation of urea and glycine polymorphs in water
Z Zou, ER Beyerle, ST Tsai, P Tiwary
Proceedings of the National Academy of Sciences 120 (7), e2216099120, 2023
162023
Large scale benchmark of materials design methods
K Choudhary, D Wines, K Li, KF Garrity, V Gupta, AH Romero, JT Krogel, ...
arXiv preprint arXiv:2306.11688, 2023
102023
Quantifying energetic and entropic pathways in molecular systems
ER Beyerle, S Mehdi, P Tiwary
The Journal of Physical Chemistry B 126 (21), 3950-3960, 2022
102022
Dinucleotides as simple models of the base stacking-unstacking component of DNA ‘breathing’mechanisms
ER Beyerle, M Dinpajooh, H Ji, PH von Hippel, AH Marcus, MG Guenza
Nucleic acids research 49 (4), 1872-1885, 2021
102021
Kinetics analysis of ubiquitin local fluctuations with Markov state modeling of the LE4PD normal modes
ER Beyerle, MG Guenza
The Journal of chemical physics 151 (16), 2019
92019
Universality and specificity in protein fluctuation dynamics
J Copperman, M Dinpajooh, ER Beyerle, MG Guenza
Physical Review Letters 119 (15), 158101, 2017
92017
Recent advances in describing and driving crystal nucleation using machine learning and artificial intelligence
ER Beyerle, Z Zou, P Tiwary
Current Opinion in Solid State and Materials Science 27 (4), 101093, 2023
62023
Identifying the leading dynamics of ubiquitin: A comparison between the tICA and the LE4PD slow fluctuations in amino acids’ position
ER Beyerle, MG Guenza
The Journal of Chemical Physics 155 (24), 2021
42021
Comparison between slow anisotropic LE4PD fluctuations and the principal component analysis modes of ubiquitin
ER Beyerle, MG Guenza
The Journal of Chemical Physics 154 (12), 124111, 2021
42021
Thermodynamically Optimized Machine-Learned Reaction Coordinates for Hydrophobic Ligand Dissociation
ER Beyerle, P Tiwary
The Journal of Physical Chemistry B 128 (3), 755-767, 2024
12024
Tyrosine hydroxylase-producing neurons in the human cerebral cortex do not colocalize with calcium-binding proteins or the serotonin 3A receptor
SE Asmus, MA Raghanti, ER Beyerle, JC Fleming-Beattie, SM Hawkins, ...
Journal of chemical neuroanatomy 78, 1-9, 2016
12016
An Information Bottleneck Approach for Markov Model Construction
D Wang, Y Qiu, E Beyerle, X Huang, P Tiwary
arXiv preprint arXiv:2404.02856, 2024
2024
Extensions of the Langevin Equation for Protein Dynamics for Modelling Equilibrium Fluctuations of Proteins
E Beyerle
University of Oregon, 2021
2021
A Comparison of the Slow Dynamics in the Protein Ubiquitin Predicted by the LE4PD, PCA, and tICA from a Long Equilibrium Molecular Dynamics Simulation
E Beyerle, M Guenza
APS March Meeting Abstracts 2021, E12. 005, 2021
2021
Fluctuations and binding of proteins in a multi scale model
M Guenza, E Beyerle
American Chemical Society SciMeetings 1 (2), 2020
2020
A kinetic analysis of local fluctuations in ubiquitin by combining the LE4PD normal modes and Markov state modeling
E Beyerle, M Guenza
Bulletin of the American Physical Society 65, 2020
2020
Combining LE4PD Normal Modes and Markov State Modeling to Elucidate the Fluctuation Dynamics of Ubiquitin
ER Beyerle, MG Guenza
Biophysical Journal 118 (3), 208a, 2020
2020
An Anisotropic Langevin Equation for Protein Dynamics
E Beyerle, M Guenza
APS March Meeting Abstracts 2019, B55. 012, 2019
2019
The Influence of Free-Energy Surfaces on Mode-Dependent Protein Dynamics
E Beyerle, M Guenza
Bulletin of the American Physical Society 63, 2018
2018
A Comparison of Collective Coordinates for Analyzing Protein Dynamics
ER Beyerle, M Guenza
Biophysical Journal 114 (3), 232a-233a, 2018
2018
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