Title :
Model-convolution approach to modeling fluorescent protein dynamics
Author :
Sprague, B.L. ; Gardner, M.K. ; Pearson, C.G. ; Maddox, P.S. ; Bloom, K. ; Salmon, E.D. ; Odde, D.J.
Author_Institution :
Lab. of Receptor Biol. & Gene Expression, National Cancer Inst., MD, USA
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.
Keywords :
biological techniques; biology computing; convolution; deconvolution; fluorescence; image colour analysis; image resolution; microscopy; proteins; fluorescence microscopy; fluorescent protein dynamics modeling; microscope system; model-convolution approach; multicolor imaging; protein dynamics; simulated image; Biological system modeling; Biology; Cells (biology); Cellular networks; Fluorescence; Mathematical model; Microscopy; Predictive models; Proteins; Spatial resolution;
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on
Print_ISBN :
0-7803-8622-1
DOI :
10.1109/ACSSC.2004.1399478