Publications
Author [ Title
] Type Year
] Type Year Filters: First Letter Of Title is U and Author is Voth, GA [Clear All Filters]
. Ultra-Coarse-Grained Liquid State Models with Implicit Hydrogen Bonding. J. Chem. Theory Comput. 2018 ;14(12):6159–6174.
. Ultra-Coarse-Grained Models Allow for an Accurate and Transferable Treatment of Interfacial Systems. J. Chem. Theory Comput. 2018 ;14(4):2180–2197.
. Understanding Dynamics in Coarse-Grained Models: I. Universal Excess Entropy Scaling Relationship. J. Chem. Phys. 2023 ;158(3):034103.
. Understanding Dynamics in Coarse-Grained Models: II. Coarse-Grained Diffusion Modeled Using Hard Sphere Theory. J. Chem. Phys. 2023 ;158(3):034104.
. Understanding Dynamics in Coarse-Grained Models: III. Roles of Rotational Motion and Translation-Rotation Coupling in Coarse-Grained Dynamics. J. Chem. Phys. Submitted .
. Unraveling the Mystery of ATP Hydrolysis in Actin Filaments. J. Am. Chem. Soc. . 2014 ;136(37):13053–13058.
. Unusual Organization of I-BAR Proteins on Tubular and Vesicular Membranes. Biophys. J. 2019 ;117(3):553–562.
. Unveiling the catalytic mechanism of GTP hydrolysis in microtubules. Proc. Natl. Acad. Sci. U.S.A. 2023 ;120(27):e2305899120.
. Using classifiers to understand coarse-grained models and their fidelity with the underlying all-atom systems. J. Chem. Phys. 2023 ;158(23):234101.
. Using Constrained Density Functional Theory to Track Proton Transfers and to Sample Their Associated Free Energy Surface. J. Chem. Theory Comput. 2021 ;17(9):5759–5765.
. Using Machine Learning to Greatly Accelerate Path Integral Ab Initio Molecular Dynamics. J. Chem. Theory Comput. 2022 ;18(2):599–604.
. Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models through Virtual Particles. J. Chem. Theory Comput. 2023 ;19(14):4402–4413.