随机游走定量分析的缺陷和细胞尺度上单分子动力学的映射
Pitfalls in the quantitative analysis of random walks and the mapping of single-molecule dynamics at the cellular scale
摘要：
近年来，贝叶斯推断已成为分析单分子轨道的有效工具。最近，高密度单分子标记、朗之万方程建模和贝叶斯推断[10]已被用于推断全细胞尺度的扩散、力场和势场。在这篇简短的评论中，我们指出了在单分子分析中要避免的陷阱[1，2]，以便在各种尺度上获得无偏的结果和可靠的领域。
英文摘要：
In recent years Bayesian Inference has become an efficient tool to analyse single molecule trajectories. Recently, high density single molecule tagging, Langevin Equation modelling and Bayesian Inference [10] have been used to infer diffusion, force and potential fields at the full cell scale. In this short comment, we point out pitfalls [1, 2] to avoid in single molecule analysis in order to get unbiased results and reliable fields at various scales.
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