Statistical Methodology in Single-Molecule Experiments
Statistical Methodology in Single-Molecule Experiments
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DOI：
10.1214/19-sts752
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发表时间：
2020-02-01
影响因子：
5.7
通讯作者：
Kou, S. C.
中科院分区：
文献类型：
--
作者：
Du, Chao;Kou, S. C.
在20世纪的最后25年，单分子实验的出现使科学家能够实时跟踪和研究单个分子的动态性质。与宏观系统的动力学不同，单分子的动力学即使在没有外部噪声的情况下，也只能用随机模型来恰当地描述。因此，统计方法在从通过单分子实验获得的数据中提取关于分子动力学的隐藏信息方面发挥了关键作用。在本文中，我们综述了用于分析单分子实验数据的主要统计方法。我们的讨论是按照用于描述单分子系统的随机模型的类型以及主要的实验数据收集技术来组织的。我们还强调了在将统计方法应用于单分子实验方面的挑战和未来方向。
Toward the last quarter of the 20th century, the emergence of single-molecule experiments enabled scientists to track and study individual molecules' dynamic properties in real time. Unlike macroscopic systems' dynamics, those of single molecules can only be properly described by stochastic models even in the absence of external noise. Consequently, statistical methods have played a key role in extracting hidden information about molecular dynamics from data obtained through single-molecule experiments. In this article, we survey the major statistical methodologies used to analyze single-molecule experimental data. Our discussion is organized according to the types of stochastic models used to describe single-molecule systems as well as major experimental data collection techniques. We also highlight challenges and future directions in the application of statistical methodologies to single-molecule experiments.