荧光相关光谱
生物系统
微秒
荧光互相关光谱
计算机科学
荧光
光谱学
显微镜
航程(航空)
共焦
光子
贝叶斯概率
信号(编程语言)
噪音(视频)
扩散
荧光光谱法
生物物理学
物理
材料科学
光学
人工智能
生物
图像(数学)
量子力学
复合材料
程序设计语言
热力学
作者
Sina Jazani,Ioannis Sgouralis,Omer Shafraz,Marcia Levitus,Sanjeevi Sivasankar,Steve Pressé
标识
DOI:10.1038/s41467-019-11574-2
摘要
Abstract Fluorescence correlation spectroscopy (FCS), is a widely used tool routinely exploited for in vivo and in vitro applications. While FCS provides estimates of dynamical quantities, such as diffusion coefficients, it demands high signal to noise ratios and long time traces, typically in the minute range. In principle, the same information can be extracted from microseconds to seconds long time traces; however, an appropriate analysis method is missing. To overcome these limitations, we adapt novel tools inspired by Bayesian non-parametrics, which starts from the direct analysis of the observed photon counts. With this approach, we are able to analyze time traces, which are too short to be analyzed by existing methods, including FCS. Our new analysis extends the capability of single molecule fluorescence confocal microscopy approaches to probe processes several orders of magnitude faster and permits a reduction of photo-toxic effects on living samples induced by long periods of light exposure.
科研通智能强力驱动
Strongly Powered by AbleSci AI