Data for: Optimal inference of molecular interaction dynamics in FRET microscopy

Intensity-based time-lapse fluorescence resonance energy transfer (FRET) microscopy has been a major tool for investigating cellular processes, converting otherwise unobservable molecular interactions into fluorescence time series. However, inferring the molecular interaction dynamics from the observables remains a challenging inverse problem, particularly when measurement noise and photobleaching are nonnegligible—a common situation in single-cell analysis. The conventional approach is to process the time-series data algebraically, but such methods inevitably accumulate the measurement noise and reduce the signal-to-noise ratio (SNR), limiting the scope of FRET microscopy. Here, we introduce an alternative probabilistic approach, B-FRET, generally applicable to standard 3-cube FRET-imaging data. Based on filtering theory, B-FRET implements a statistically optimal way to infer molecular interactions and thus drastically improves the SNR. We validate B-FRET using simulated data and then ..., Synthetic data were generated using MATLAB based on the photophysical model described in the article. Experimental data were taken under fluorescence microscopes. See the article for details.  , MATLAB is required to open the data files.Â基于强度的延时荧光共振能量转移（FRET）显微镜术一直是研究细胞过程的核心工具，可将原本无法观测的分子相互作用转化为荧光时间序列。然而，从观测数据中推断分子相互作用动力学始终是一项极具挑战性的逆问题，尤其当测量噪声与光漂白效应不可忽视时——这在单细胞分析中是极为常见的情况。传统方法通常通过代数方式处理时间序列数据，但这类方法不可避免地会累积测量噪声并降低信噪比（SNR），从而限制了FRET显微镜术的应用范围。本文提出了一种替代的概率方法B-FRET，其可普遍适用于标准三通道FRET成像数据。B-FRET基于滤波理论，实现了统计最优的分子相互作用推断方案，因此可大幅提升信噪比。我们首先通过模拟数据对B-FRET进行验证，随后……；合成数据基于本文所述的光物理模型，使用MATLAB生成。实验数据取自荧光显微镜观测结果，详细信息请参见原文。若需打开数据文件，需使用MATLAB。