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.
Original language | English (US) |
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Pages (from-to) | 1821-1825 |
Number of pages | 5 |
Journal | Conference Record - Asilomar Conference on Signals, Systems and Computers |
Volume | 2 |
State | Published - 2004 |
Event | Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 7 2004 → Nov 10 2004 |