Pitfalls in the quantitative analysis of random walks and the mapping of single-molecule dynamics at the cellular scale
Biological Physics
2015-02-26 v1 Quantitative Methods
Abstract
In recent years Bayesian Inference has become an efficient tool to analyse single molecule trajectories. Recently, high density single molecule tagging, Langevin Equation modelling and Bayesian Inference [10] have been used to infer diffusion, force and potential fields at the full cell scale. In this short comment, we point out pitfalls [1, 2] to avoid in single molecule analysis in order to get unbiased results and reliable fields at various scales.
Keywords
Cite
@article{arxiv.1502.07285,
title = {Pitfalls in the quantitative analysis of random walks and the mapping of single-molecule dynamics at the cellular scale},
author = {Jean-Baptiste Masson and Maxime Dahan and Antoine Triller},
journal= {arXiv preprint arXiv:1502.07285},
year = {2015}
}
Comments
5 pages, 1 figure