Model-convolution approach to modeling fluorescent protein dynamics

B. L. Sprague, M. K. Gardner, C. G. Pearson, P. S. Maddox, K. Bloom, E. D. Salmon, D. J. Odde

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

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 languageEnglish (US)
Pages (from-to)1821-1825
Number of pages5
JournalConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2
StatePublished - Dec 1 2004
EventConference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 7 2004Nov 10 2004

Fingerprint

Dive into the research topics of 'Model-convolution approach to modeling fluorescent protein dynamics'. Together they form a unique fingerprint.

Cite this