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单粒子追踪实验中反常扩散均方位移图拟合指南。

Guidelines for the fitting of anomalous diffusion mean square displacement graphs from single particle tracking experiments.

作者信息

Kepten Eldad, Weron Aleksander, Sikora Grzegorz, Burnecki Krzysztof, Garini Yuval

机构信息

Physics Department & Institute of Nanotechnology, Bar Ilan University, Ramat Gan, Israel.

Hugo Steinhaus Center, Institute of Mathematics and Computer Science, Wroclaw University of Technology, Wroclaw, Poland.

出版信息

PLoS One. 2015 Feb 13;10(2):e0117722. doi: 10.1371/journal.pone.0117722. eCollection 2015.

Abstract

Single particle tracking is an essential tool in the study of complex systems and biophysics and it is commonly analyzed by the time-averaged mean square displacement (MSD) of the diffusive trajectories. However, past work has shown that MSDs are susceptible to significant errors and biases, preventing the comparison and assessment of experimental studies. Here, we attempt to extract practical guidelines for the estimation of anomalous time averaged MSDs through the simulation of multiple scenarios with fractional Brownian motion as a representative of a large class of fractional ergodic processes. We extract the precision and accuracy of the fitted MSD for various anomalous exponents and measurement errors with respect to measurement length and maximum time lags. Based on the calculated precision maps, we present guidelines to improve accuracy in single particle studies. Importantly, we find that in some experimental conditions, the time averaged MSD should not be used as an estimator.

摘要

单粒子追踪是研究复杂系统和生物物理学的一项重要工具,通常通过扩散轨迹的时间平均平方位移(MSD)进行分析。然而,过去的研究表明,MSD容易受到重大误差和偏差的影响,阻碍了实验研究的比较和评估。在这里,我们试图通过模拟多种情况,以分数布朗运动作为一大类分数遍历过程的代表,来提取用于估计反常时间平均MSD的实用指南。我们针对各种反常指数以及测量长度和最大时间滞后方面的测量误差,提取了拟合MSD的精度和准确性。基于计算出的精度图,我们提出了提高单粒子研究准确性的指南。重要的是,我们发现在某些实验条件下,不应将时间平均MSD用作估计器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b0e/4334513/67a932f2ca7b/pone.0117722.g001.jpg

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