CUED Publications database

Bayesian inference for improved single molecule fluorescence tracking.

Yoon, JW and Bruckbauer, A and Fitzgerald, WJ and Klenerman, D (2008) Bayesian inference for improved single molecule fluorescence tracking. Biophys J, 94. pp. 4932-4947.

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Single molecule tracking is widely used to monitor the change in position of lipids and proteins in living cells. In many experiments in which molecules are tagged with a single or small number of fluorophores, the signal/noise ratio may be limiting, the number of molecules is not known, and fluorophore blinking and photobleaching can occur. All these factors make accurate tracking over long trajectories difficult and hence there is still a pressing need to develop better algorithms to extract the maximum information from a sequence of fluorescence images. We describe here a Bayesian-based inference approach, based on a trans-dimensional sequential Monte Carlo method that utilizes both the spatial and temporal information present in the image sequences. We show, using model data, where the real trajectory of the molecule is known, that our method allows accurate tracking of molecules over long trajectories even with low signal/noise ratio and in the presence of fluorescence blinking and photobleaching. The method is then applied to real experimental data.

Item Type: Article
Uncontrolled Keywords: Algorithms Artificial Intelligence Bayes Theorem Biopolymers Image Enhancement Image Interpretation, Computer-Assisted Microscopy, Fluorescence Microscopy, Video Motion Pattern Recognition, Automated
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:17
Last Modified: 23 Jun 2018 20:13