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Updated: Aug 2, 2025

A Protocol for Real-time 3D Single Particle Tracking
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BNP-Track: A framework for multi-particle superresolved tracking.

Lance W Q Xu1,2, Ioannis Sgouralis3, Zeliha Kilic4

  • 1Center for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287, USA.

Biorxiv : the Preprint Server for Biology
|April 17, 2023
PubMed
Summary
This summary is machine-generated.

We developed BNP-Track, a novel Bayesian nonparametric tracking tool that accurately tracks multiple fluorescent molecules by analyzing spatiotemporal correlations, outperforming conventional methods for dynamic targets.

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Area of Science:

  • Microscopy and biophysics
  • Computational biology and data analysis
  • Superresolution imaging

Background:

  • Tracking fluorescent molecules is challenging due to point spread function overlap, especially in crowded environments.
  • Existing superresolution methods struggle with dynamic targets due to temporal delays.
  • Neighboring molecule information is encoded in spatiotemporal intensity correlations.

Approach:

  • Developed BNP-Track, a Bayesian nonparametric tool for simultaneous inference of emitter number and tracks.
  • Utilized spatiotemporal correlations for superresolved tracking of dynamic targets.
  • Tested BNP-Track's robustness across parameter regimes and compared it to competing methods.

Key Points:

  • BNP-Track achieves superresolved tracking by leveraging all encoded spatiotemporal correlations.
  • Stochastic background treatment enhances emitter number determination accuracy.
  • BNP-Track corrects for point spread function blur and propagates various error sources.

Conclusions:

  • BNP-Track extends the superresolution paradigm to dynamic targets.
  • The tool can track multiple diffraction-limited emitters unresolved by conventional methods.
  • BNP-Track offers superior accuracy and robustness in complex molecular tracking scenarios.