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

Mohamed El beheiry Silvan Türkcan Maximilian u. Richly 1 Antoine Triller 2 Antigone Alexandrou 1 Maxime Dahan Jean-Baptiste Masson
1 LOB - Laboratoire d'optique et biosciences
2 IBENS - Institut de biologie de l'Ecole Normale Supérieure
Abstract : 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.
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Biophysical Journal, Biophysical Society, 2016, 110 (6), pp.1209 - 1215. 〈10.1016/j.bpj.2016.01.018〉
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Soumis le : jeudi 22 décembre 2016 - 15:35:07
Dernière modification le : jeudi 7 février 2019 - 16:05:53

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Mohamed El beheiry, Silvan Türkcan, Maximilian u. Richly, Antoine Triller, Antigone Alexandrou, et al.. A Primer on the Bayesian Approach to High-Density Single-Molecule Trajectories Analysis. Biophysical Journal, Biophysical Society, 2016, 110 (6), pp.1209 - 1215. 〈10.1016/j.bpj.2016.01.018〉. 〈hal-01421582〉

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