Montiel D, Cang H, Yang H
Department of Chemistry, University of California at Berkeley, Physical Biosciences Division, Lawrence Berkeley National Laboratories, Berkeley, California 94720, USA.
J Phys Chem B. 2006 Oct 12;110(40):19763-70. doi: 10.1021/jp062024j.
Single-particle tracking experiments have been used widely to study the heterogeneity of a sample. Segments with dissimilar diffusive behaviors are associated with different intermediate states, usually by visual inspection of the tracking trace. A likelihood-based, systematic approach is presented to remove this incertitude. Maximum likelihood estimators are derived for the determination of diffusion coefficients. A likelihood ratio test is applied to the localization of the changes in them. Simulations suggest that the proposed procedure is statistically robust and is able to quantitatively recover time-dependent changes in diffusion coefficients even in the presence of large measurement noise.
单粒子追踪实验已被广泛用于研究样本的异质性。通常通过对追踪轨迹的目视检查，将具有不同扩散行为的片段与不同的中间状态相关联。本文提出了一种基于似然性的系统方法来消除这种不确定性。推导了用于确定扩散系数的最大似然估计量。应用似然比检验来定位扩散系数的变化。模拟结果表明，所提出的方法在统计上是稳健的，即使在存在大量测量噪声的情况下，也能够定量恢复扩散系数随时间的变化。
