A Primer on the Bayesian Approach to High-Density Single-Molecule Trajectories Analysis

Tracking single molecules in living cells provides invaluable information on their environment and on the interactions that underlie their motion. New experimental techniques now permit the recording of large amounts of individual trajectories, enabling the implementation of advanced statistical too...

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Bibliographic Details
Published in:Biophysical journal 2016-03, Vol.110 (6), p.1209-1215
Main Authors: El Beheiry, Mohamed, Türkcan, Silvan, Richly, Maximilian U., Triller, Antoine, Alexandrou, Antigone, Dahan, Maxime, Masson, Jean-Baptiste
Format: Article
Language:English
Subjects:
Bayes Theorem
Bayesian analysis
Biological Physics
Biophysical
Carrier Proteins - chemistry
Cells
Data analysis
Experiments
HeLa Cells
Humans
Likelihood Functions
Membrane Proteins - chemistry
Molecules
Physics
Protein Structure, Secondary
Statistics
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Summary:Tracking single molecules in living cells provides invaluable information on their environment and on the interactions that underlie their motion. New experimental techniques now permit the recording of large amounts of individual trajectories, enabling the implementation of advanced statistical tools for data analysis. In this primer, we present a Bayesian approach toward treating these data, and we discuss how it can be fruitfully employed to infer physical and biochemical parameters from single-molecule trajectories.
ISSN:0006-3495
1542-0086
DOI:10.1016/j.bpj.2016.01.018