Counting fluorescence photobleaching steps is commonly used to infer the number n0 of monomeric units of individual oligomeric protein complexes or misfolded protein aggregates. We present a principled Bayesian approach for counting that incorporates the statistics of photobleaching. Our physics-based prior leads to a simple and efficient numerical scheme for maximum a posteriori probability (MAP) estimates of the initial fluorophore number n^0. Our focus here is on using a calibration to precisely estimate n^0, though our approach can also be used to calibrate the photophysics. Imaging noise increases with n^0, while bias is often introduced by temporal averaging. We examine the effects of fluorophore number n^0 of the oligomer or aggregate, lifetime photon yield μeff of an individual fluorophore, and exposure time Δt of each image frame in a time-lapse experiment. We find that, in comparison with standard ratiometric approaches or with a "change-point" step-counting algorithm, our MAP approach is both more precise and less biased.

中文翻译：

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贝叶斯计数与物理先验光漂白步骤。

计数荧光光漂白步骤通常用于推断单个寡聚蛋白复合物或错误折叠的蛋白聚集体的单体单元数量n0。我们提出了一种有原则的贝叶斯计数方法，其中包含了光漂白的统计信息。我们基于物理学的先验结果导致了一种简单有效的数值方案，可以使初始荧光团数n ^ 0的最大后验概率（MAP）估计值最大化。尽管我们的方法也可以用于校准光物理，但我们的重点是使用校准来精确估计n ^ 0。成像噪声随n ^ 0的增加而增加，而偏差通常是通过时间平均引入的。我们研究了低聚物或聚集体的荧光团数n ^ 0，单个荧光团的寿命光子产量μeff的影响，延时实验中的每个图像帧的曝光时间Δt。我们发现，与标准比率方法或“变化点”步数计数算法相比，我们的MAP方法更加精确且偏差较小。