Model-convolution approach to modeling fluorescent protein dynamics

Abstract

Fluorescence microscopy is a popular technique for visualizing protein dynamics in living cells. However, the precise distribution of fluorophores underlying the observed fluorescence is not always obvious, even after deconvolution, particularly when features on a scale of 250 nm or less are of interest In contrast, quantitative models of protein dynamics predict an actual fluorophore distribution. "Model-convolution" is a method that bridges this gap by convolving model-predicted fluorophore location data with the point spread function of the microscope system so that simulated images can be generated and directly compared to experimental images. This article offers a practical guide to model-convolution.