Global analysis of autocorrelation functions and photon counting distributions in fluorescence fluctuation spectroscopy.

In fluorescence correlation spectroscopy (FCS) and photon counting histogram (PCH) analysis, the same experimental fluorescence intensity fluctuations are used, but each analytical method focuses on a different property of the signal. The time-dependent decay of the correlation of fluorescence fluctuations is measured in FCS yielding molecular diffusion coefficients and triplet-state parameters such as fraction and decay time. The amplitude distribution of these fluctuations is calculated by PCH analysis yielding the molecular brightness.

Global analysis of time-resolved fluorescence data.

In this chapter, we describe the global analysis approach for processing time-resolved fluorescence spectroscopy data of molecules in the condensed phase. Combining simultaneous analysis of data measured under different experimental conditions (spatial coordinates, temperature, concentration, emission wavelength, excitation intensity, etc.) with the fitting strategy, enabling parameter linkage and thus decreasing the total amount of estimated variables, makes global analysis more robust and more consistent compared to a sequential fit of single experimental data.

Global analysis of autocorrelation functions and photon counting distributions.

In fluorescence correlation spectroscopy (FCS) and photon counting histogram (PCH) analysis the same experimental fluorescence intensity fluctuations are used, but each analytical method focuses on a different property of the signal. The time-dependent decay of the correlation of fluorescence fluctuations is measured in FCS yielding, for instance, molecular diffusion coefficients. The amplitude distribution of these fluctuations is calculated by PCH yielding the molecular brightness.

Global analysis of fluorescence fluctuation data.

Over the last decade the number of applications of fluorescence correlation spectroscopy (FCS) has grown rapidly. Here we describe the development and application of a software package, FCS Data Processor, to analyse the acquired correlation curves. The algorithms combine strong analytical power with flexibility in use.