Artem B. Mamonov, Ph.D.
Affiliations: | 2006 | University of Pittsburgh, Pittsburgh, PA, United States |
Area:
General BiophysicsGoogle:
"Artem Mamonov"Parents
Sign in to add mentorRob D. Coalson | grad student | 2006 | University of Pittsburgh | |
(Modeling ion and water permeation through narrow biological channels.) |
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Publications
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Mamonov AB, Lettieri S, Ding Y, et al. (2012) Tunable, mixed-resolution modeling using library-based Monte Carlo and graphics processing units. Journal of Chemical Theory and Computation. 8: 2921-2929 |
Lettieri S, Mamonov AB, Zuckerman DM. (2011) Extending fragment-based free energy calculations with library Monte Carlo simulation: annealing in interaction space. Journal of Computational Chemistry. 32: 1135-43 |
Cashman DJ, Mamonov AB, Bhatt D, et al. (2011) Thermal motions of the E. coli glucose-galactose binding protein studied using well-sampled semi-atomistic simulations Current Topics in Medicinal Chemistry. 11: 211-220 |
Mamonov AB, Zhang X, Zuckerman DM. (2011) Rapid sampling of all-atom peptides using a library-based polymer-growth approach. Journal of Computational Chemistry. 32: 396-405 |
Ding Y, Mamonov AB, Zuckerman DM. (2011) Improved Library-Based Monte Carlo, Applied to Multi-Level Sampling Biophysical Journal. 100: 155a |
Ding Y, Mamonov AB, Zuckerman DM. (2010) Efficient equilibrium sampling of all-atom peptides using library-based Monte Carlo. The Journal of Physical Chemistry. B. 114: 5870-7 |
Mamonov AB, Zuckerman DM. (2010) Library-Based Monte Carlo as a Convenient Platform for Variable-Resolution Protein Models Biophysical Journal. 98: 571a |
Mamonov AB, Bhatt D, Cashman DJ, et al. (2009) General library-based Monte Carlo technique enables equilibrium sampling of semi-atomistic protein models. The Journal of Physical Chemistry. B. 113: 10891-904 |
Zhang X, Mamonov AB, Zuckerman DM. (2009) Absolute free energies estimated by combining precalculated molecular fragment libraries. Journal of Computational Chemistry. 30: 1680-91 |
Mamonov AB, Zuckerman DM. (2009) Improving The Computational Efficiency Of Non-Dynamical Approaches For Equilibrium Sampling Of All-Atom Protein Models Biophysical Journal. 96: 407a |