@article {47410,
	title = {A primer on the Bayesian approach to high-density single-molecule trajectories analysis.},
	journal = {Biophysical Journal},
	volume = {110},
	year = {2016},
	month = {2016 Mar 29},
	pages = {1209-15},
	abstract = {<p>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.</p>
},
	issn = {1542-0086},
	doi = {10.1016/j.bpj.2016.01.018},
	author = {El Beheiry, Mohamed and T{\"u}rkcan, Silvan and Richly, Maximilian U and Triller, Antoine and Alexandrou, Antigone and Dahan, Maxime and Masson, Jean-Baptiste}
}
