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Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.

ABSTRACT: Accurately characterizing the anomalous diffusion of a tracer particle has become a central issue in biophysics. However, measurement errors raise difficulty in the characterization of single trajectories, which is usually performed through the time-averaged mean square displacement (TAMSD). In this paper, we study a fractionally integrated moving average (FIMA) process as an appropriate model for anomalous diffusion data with measurement errors. We compare FIMA and traditional TAMSD estimators for the anomalous diffusion exponent. The ability of the FIMA framework to characterize dynamics in a wide range of anomalous exponents and noise levels through the simulation of a toy model (fractional Brownian motion disturbed by Gaussian white noise) is discussed. Comparison to the TAMSD technique, shows that FIMA estimation is superior in many scenarios. This is expected to enable new measurement regimes for single particle tracking (SPT) experiments even in the presence of high measurement errors.

SUBMITTER: Burnecki K

PROVIDER: S-EPMC4463942 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.

Burnecki Krzysztof K Kepten Eldad E Garini Yuval Y Sikora Grzegorz G Weron Aleksander A

Scientific reports 20150611

Accurately characterizing the anomalous diffusion of a tracer particle has become a central issue in biophysics. However, measurement errors raise difficulty in the characterization of single trajectories, which is usually performed through the time-averaged mean square displacement (TAMSD). In this paper, we study a fractionally integrated moving average (FIMA) process as an appropriate model for anomalous diffusion data with measurement errors. We compare FIMA and traditional TAMSD estimators ...[more]

PMID: 26065707

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Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.

Publications

Estimating the anomalous diffusion exponent for single particle tracking data with measurement errors - An alternative approach.

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