Analysis of single particle trajectories: when things go wrong

TL;DR

This paper discusses the challenges and pitfalls in analyzing single particle trajectories using stochastic models, emphasizing the importance of optimal estimators for accurate long-term behavior recovery.

Contribution

It introduces the analysis of potential errors in trajectory analysis and highlights the importance of proper estimators in recovering biophysical properties.

Findings

Optimal estimators improve trajectory analysis accuracy

Misapplication of models can lead to incorrect biophysical interpretations

The study emphasizes careful data analysis in super-resolution single molecule experiments

Abstract

To recover the long-time behavior and the statistics of molecular trajectories from the large number (tens of thousands) of their short fragments, obtained by super-resolution methods at the single molecule level, data analysis based on a stochastic model of their non-equilibrium motion is required. Recently, we characterized the local biophysical properties underlying receptor motion based on coarse-grained long-range interactions, corresponding to attracting potential wells of large sizes. The purpose of this letter is to discuss optimal estimators and show what happens when thing goes wrong.