Optimal diffusion coefficient estimation in single-particle tracking.
Optimal diffusion coefficient estimation in single-particle tracking.
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DOI：
10.1103/physreve.85.061916
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发表时间：
2012-06
期刊：
影响因子：
--
通讯作者：
Berglund AJ
中科院分区：
文献类型：
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作者：
Michalet X;Berglund AJ
单粒子跟踪被越来越多地用于提取单分子及其环境的定量参数，而跟踪技术在空间和时间分辨率上的进步引发了新的问题和研究途径。相应地，不断发展复杂的分析方法，以从测量的轨迹中获得更精细的信息。在这里，我们指出了这些方法的一些基本的局限性，由于轨迹的有限长度，局部化误差的存在，以及运动模糊的存在，重点关注各向同性介质中自由扩散的最简单运动机制(布朗运动)。我们证明了最近提出的两个算法接近扩散系数不确定性的理论极限。我们讨论了这些算法的实际性能，以及这些结果对单粒子跟踪的一些重要意义。
Single-particle tracking is increasingly used to extract quantitative parameters on single molecules and their environment, while advances in spatial and temporal resolution of tracking techniques inspire new questions and avenues of investigation. Correspondingly, sophisticated analytical methods are constantly developed to obtain more refined information from measured trajectories. Here we point out some fundamental limitations of these approaches due to the finite length of trajectories, the presence of localization error, and motion blur, focusing on the simplest motion regime of free diffusion in an isotropic medium (Brownian motion). We show that two recently proposed algorithms approach the theoretical limit of diffusion coefficient uncertainty. We discuss the practical performance of the algorithms as well as some important implications of these results for single-particle tracking.