Quantifying uncertainty and sampling quality in biomolecular simulations.
Quantifying uncertainty and sampling quality in biomolecular simulations.
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DOI：
10.1016/s1574-1400(09)00502-7
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发表时间：
2009-01-01
期刊：
影响因子：
--
通讯作者：
Zuckerman DM
中科院分区：
文献类型：
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作者：
Grossfield A;Zuckerman DM
不断增长的计算能力和算法的进步促进了在更长的时间尺度上对越来越大的生物分子系统的研究。然而，随着这些更大、更复杂的系统出现了关于采样质量和统计收敛的问题。多大的系统可以完全抽样？如果系统没有完全采样，那么某些“快速变量”是否可以被认为是良好收敛的？如何确定观察结果的统计显著性？本文介绍了解决这些问题所必需的统计工具和基本的物理思想。提供了基本定义和现成的分析，以及明确的建议。在任何给定的研究中，这种统计分析对于建立模拟数据的可靠性至关重要。
Growing computing capacity and algorithmic advances have facilitated the study of increasingly large biomolecular systems at longer timescales. However, with these larger, more complex systems come questions about the quality of sampling and statistical convergence. What size systems can be sampled fully? If a system is not fully sampled, can certain “fast variables” be considered well-converged? How can one determine the statistical significance of observed results? The present review describes statistical tools and the underlying physical ideas necessary to address these questions. Basic definitions and ready-to-use analyses are provided, along with explicit recommendations. Such statistical analyses are of paramount importance in establishing the reliability of simulation data in any given study.