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

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.

SUBMITTER: Grossfield A

PROVIDER: S-EPMC6286151 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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

Grossfield Alan A Patrone Paul N PN Roe Daniel R DR Schultz Andrew J AJ Siderius Daniel W DW Zuckerman Daniel M DM

Living journal of computational molecular science 20181027 1

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 an ...[more]

PMID: 30533602

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Best practices for eCLIP experiments and analysis

Project description:This SuperSeries is composed of the SubSeries listed below.

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