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Method for simultaneous localization and parameter estimation in particle tracking experiments.

Trevor T Ashley1, Sean B Andersson1,2

  • 1Department of Mechanical Engineering, Boston University, Boston, Massachusetts 02215, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 15, 2015
PubMed
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Small (Weinheim an der Bergstrasse, Germany)·2023

This study introduces a new numerical method for tracking fluorescent particles and estimating their parameters simultaneously. The technique accurately models particle motion and noise, improving localization accuracy.

Area of Science:

  • Biophysics
  • Computational Biology
  • Statistical Physics

Background:

  • Accurate tracking of fluorescent particles is crucial for understanding cellular processes.
  • Existing methods often struggle with complex noise and motion models.
  • Simultaneous localization and parameter estimation remain a challenge.

Purpose of the Study:

  • To develop a novel numerical method for simultaneous localization and parameter estimation of fluorescent particles.
  • To create a method capable of handling complex noise and motion models.
  • To provide an approximation to the posterior density of particle positions over time.

Main Methods:

  • Sequential Monte Carlo (SMC) methods are employed.
  • The method accommodates nonlinear noise models (shot noise, readout noise).

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  • It supports diverse motion and observation models, including engineered point spread functions.

    • Main Results:

    • The method successfully performs simultaneous localization and parameter estimation.
    • It provides accurate approximations of particle position posterior densities.
    • Demonstrated effectiveness across free, confined, and tethered diffusion scenarios.

    Conclusions:

    • The presented numerical method offers a robust approach for analyzing fluorescent particle dynamics.
    • It enhances the capability to study complex biological systems with high precision.
    • This technique advances particle tracking and parameter estimation in biophysical research.