Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0].

View/ Open
Average rating
votes
Date
2019Author
Grossfield, Alan
Patrone, Paul N.
Roe, Daniel R.
Schultz, Andrew J.
Siderius, Daniel W.
Zuckerman, Daniel M.
Metadata
Show full item recordAbstract
The quantitative assessment of uncertainty and sampling quality is essential in molecular
simulation. Many systems of interest are highly complex, often at the edge of current computational
capabilities. Modelers must therefore analyze and communicate statistical uncertainties so
that “consumers” of simulated data understand its significance and limitations. This article covers
key analyses appropriate for trajectory data generated by conventional simulation methods such as
molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing
some ‘enhanced’ sampling approaches. We do not discuss systematic errors arising, e.g., from
inaccuracy in the chosen model or force field......
Resource URL
https://www.livecomsjournal.org/article/5067-best-practices-for-quantification-of-uncertainty-and-sampling-quality-in-molecular-simulations-article-v1-0https://github.com/dmzuckerman/Sampling-Uncertainty
Journal
Living Journal of Computational Molecular ScienceVolume
1Issue
1, 5067Page Range
24pp.Document Language
enBest Practice Type
Best PracticeGuide
ISSN
2575-6524DOI Original
https://doi.org/10.33011/livecoms.1.1.5067Citation
Grossfield. A.; Patrone, P.N.; Roe, D.R.; Schultz, A.J.; Siderius, D.W. and Zuckerman. D.M. (2019) Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0]. Living Journal of Computational Molecular Science, 1(1), 5067, 24pp. DOI: https://doi.org/10.33011/livecoms.1.1.5067Collections