Pitfalls in the quantitative analysis of random walks and the mapping of single-molecule dynamics at the cellular scale
arXiv:1502.07285
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.
5 pages, 1 figure
References in corpus (3)
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