Bayesian mixed-effects model for the analysis of a series of FRAP images

Improved FRAP Measurements on Biofilms

We expand the standard fluorescence recovery after photobleaching (FRAP) model introduced by Axelrod et al. in 1976. Our goal is to capture some of the following common artifacts observed in the fluorescence measurements obtained with a confocal laser scanning microscope in biofilms: 1) linear drift, 2) exponential decrease (due to bleaching during the measurements), 3) stochastic Gaussian noise, and 4) uncertainty in the exact time point of the onset of fluorescence recovery. To fit the resulting stochastic model to data from FRAP measurements and to estimate all unknown model parameters, we apply a suitably adapted Metropolis-Hastings algorithm. In this way, a more accurate estimation of the diffusion coefficient of the fluorophore is achieved. The method was tested on data obtained from FRAP measurements on a cultivated biofilm.