Department of Chemistry, University of Zurich, Zurich, Switzerland.
Department of Computer Science, Chemnitz University of Technology, Chemnitz, Germany.
PLoS One. 2018 Apr 13;13(4):e0195277. doi: 10.1371/journal.pone.0195277. eCollection 2018.
Single-molecule microscopy has become a widely used technique in (bio)physics and (bio)chemistry. A popular implementation is single-molecule Förster Resonance Energy Transfer (smFRET), for which total internal reflection fluorescence microscopy is frequently combined with camera-based detection of surface-immobilized molecules. Camera-based smFRET experiments generate large and complex datasets and several methods for video processing and analysis have been reported. As these algorithms often address similar aspects in video analysis, there is a growing need for standardized comparison. Here, we present a Matlab-based software (MASH-FRET) that allows for the simulation of camera-based smFRET videos, yielding standardized data sets suitable for benchmarking video processing algorithms. The software permits to vary parameters that are relevant in cameras-based smFRET, such as video quality, and the properties of the system under study. Experimental noise is modeled taking into account photon statistics and camera noise. Finally, we survey how video test sets should be designed to evaluate currently available data analysis strategies in camera-based sm fluorescence experiments. We complement our study by pre-optimizing and evaluating spot detection algorithms using our simulated video test sets.
单分子显微镜已成为（生物）物理学和（生物）化学领域广泛使用的技术。一种流行的实现方法是单分子Förster 共振能量转移（smFRET），通常将其与基于相机的表面固定分子的全内反射荧光显微镜结合使用。基于相机的 smFRET 实验会生成大量复杂的数据集，并且已经报道了几种视频处理和分析方法。由于这些算法通常在视频分析中涉及相似的方面，因此需要标准化比较。在这里，我们介绍了一个基于 Matlab 的软件（MASH-FRET），它允许模拟基于相机的 smFRET 视频，生成适合基准测试视频处理算法的标准化数据集。该软件允许改变与基于相机的 smFRET 相关的参数，例如视频质量和研究系统的特性。实验噪声考虑到光子统计和相机噪声进行建模。最后，我们调查了如何设计视频测试集，以评估当前可用的基于相机的 sm 荧光实验中的数据分析策略。我们通过使用模拟视频测试集对斑点检测算法进行预优化和评估来补充我们的研究。
