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Updated: Sep 29, 2025

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Published on: December 9, 2013

Bayesian machine learning analysis of single-molecule fluorescence colocalization images.

Yerdos A Ordabayev¹, Larry J Friedman¹, Jeff Gelles¹

¹Department of Biochemistry, Brandeis University, Waltham, United States.

|March 23, 2022

Summary

Tapqir is a new unsupervised machine learning method for analyzing single-molecule fluorescence colocalization data. It objectively classifies molecular spots, improving the accuracy of biochemical reaction analysis.

Keywords:

CoSMoS TIRF Tapqir biochemistry chemical biology fluorescence microscopy molecular biophysics none probablistic programming pyro structural biology

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Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

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Area of Science:

Biophysics
Biochemistry
Data Science

Background:

Multi-wavelength single-molecule fluorescence colocalization (CoSMoS) is crucial for studying complex biochemical reactions.
CoSMoS data analysis faces challenges including low signal-to-noise ratios, non-specific binding, and subjective analysis methods.

Purpose of the Study:

To develop an objective and automated analysis method for CoSMoS data.
To improve the accuracy of analyzing molecular dynamics, thermodynamics, and kinetics from CoSMoS experiments.

Main Methods:

Implemented Tapqir, an unsupervised machine learning method using Bayesian probabilistic programming.
Developed a physics-based causal model to account for image analysis uncertainties (noise, binding, spot detection).

Main Results:

Tapqir objectively assigns spot classification probabilities, overcoming limitations of binary classifications.
Validated Tapqir performance against simulated data and demonstrated its effectiveness on diverse experimental datasets.
The method accurately handles varying signal, noise, and non-specific binding characteristics.

Conclusions:

Tapqir provides a robust, objective, and automated solution for CoSMoS data analysis.
This method enhances the reliability and accuracy of studying biochemical reaction mechanisms using single-molecule fluorescence techniques.