dc.contributor.author | Grossfield, Alan | |
dc.contributor.author | Patrone, Paul N. | |
dc.contributor.author | Roe, Daniel R. | |
dc.contributor.author | Schultz, Andrew J. | |
dc.contributor.author | Siderius, Daniel W. | |
dc.contributor.author | Zuckerman, Daniel M. | |
dc.date.accessioned | 2019-09-24T19:28:44Z | |
dc.date.available | 2019-09-24T19:28:44Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | 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.1.1.5067 | en_US |
dc.identifier.issn | 2575-6524 | |
dc.identifier.uri | http://hdl.handle.net/11329/1048 | |
dc.identifier.uri | http://dx.doi.org/10.25607/OBP-576 | |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.subject.other | Statistical uncertainties | en_US |
dc.subject.other | Uncertainty quantification | en_US |
dc.subject.other | Model uncertainty | en_US |
dc.title | Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0]. | en_US |
dc.type | Journal Contribution | en_US |
dc.description.refereed | Refereed | en_US |
dc.format.pagerange | 24pp. | en_US |
dc.identifier.doi | https://doi.org/10.33011/livecoms.1.1.5067 | |
dc.subject.parameterDiscipline | Parameter Discipline::Cross-discipline | en_US |
dc.subject.dmProcesses | Data Management Practices::Data analysis | en_US |
dc.bibliographicCitation.title | Living Journal of Computational Molecular Science | en_US |
dc.bibliographicCitation.volume | 1 | en_US |
dc.bibliographicCitation.issue | 1, 5067 | en_US |
dc.description.bptype | Best Practice | en_US |
dc.description.bptype | Guide | en_US |
obps.contact.contactname | Alan Grossfield | |
obps.contact.contactemail | alan_grossfield@urmc.rochester.edu | |
obps.resourceurl.publisher | https://www.livecomsjournal.org/article/5067-best-practices-for-quantification-of-uncertainty-and-sampling-quality-in-molecular-simulations-article-v1-0 | en_US |
obps.resourceurl.publisher | https://github.com/dmzuckerman/Sampling-Uncertainty | |