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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Uncertainties of Predictions from Temperature Replica Exchange Simulations

Authors: Spiwok, Vojtech; Kriz, Pavel; Beránek, Jan;

Uncertainties of Predictions from Temperature Replica Exchange Simulations

Abstract

Parallel tempering molecular dynamics simulation, also known as temperature replica exchange simulation, is a popular enhanced sampling method used to study biomolecular systems. This method makes it possible to calculate the free energy differences between states of the system for a series of temperatures. We developed a method to easily calculate errors (standard errors or confidence intervals) of these predictions using a modified version of our recently introduced JumpCount method. The number of transitions between states (e.g. protein folding events) is counted for each temperature. This number of transitions, together with the temperature, fully determines the value of standard error or the confidence interval of the free energy difference. We also address the issue of convergence in the situation where all replicas start from one state by developing an estimator of the equilibrium constant from simulations that are not fully equilibrated. The prerequisite of the method is the Markovianity of the process studied.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average