Title: Extracting the magnitude of the measurement error for fractional dynamics
Author: Michał Balcerek
Accurately characterizing the anomalous diffusion and anomalous kinetics for experimentshas become a central issue in biophysics. However, measurement errors raise difficulty inthe analysis of single particle trajectories. In this poster, we introduce a novel surfacecalibration method as an effective tool for extracting both the magnitude of themeasurement error and the anomalous exponent for autocorrelated processes of variousorigins.
For describing fractional dynamics data with apparent measurement errors we propose herea general toy model which combines a fractional Brownian motion and independent whitenoise. We approximate the toy model by a time series process. Using this approximation, weconstruct the calibration surface which enables to recover the magnitude of themeasurement noise and anomalous diffusion exponent from observed experimental data.We show that this approach is superior to a mean-squared displacement method that wasgeneralized to account for the present of the noise. The method is illustrated on bothsimulated and experimental biological data.