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Related Experiment Video

Updated: Dec 8, 2025

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Published on: June 30, 2018

Co-localization analysis in fluorescence microscopy via maximum entropy copula.

Zahra Amini Farsani^1,2, Volker J Schmid²

¹Statistics Department, School of Science, Lorestan University, 68151-44316 Khorramabad, Islamic Republic of Iran.

The International Journal of Biostatistics

|September 18, 2020

Summary

This summary is machine-generated.

A new Maximum Entropy Copula (MEC) method robustly quantifies marker co-localization in fluorescence microscopy. This advanced technique overcomes limitations of traditional methods, even in high background noise.

Keywords:

Gaussian copula Kendall’s τ computational biology maximum entropy method nucleonic

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Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons

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Published on: October 31, 2020

Area of Science:

Cell Biology
Microscopy Imaging
Quantitative Analysis

Background:

Co-localization analysis in fluorescence microscopy is crucial for understanding protein localization within the cell nucleus.
Existing co-localization metrics often rely on subjective thresholding and assume linear signal relationships, limiting their accuracy.

Purpose of the Study:

To develop a robust and accurate method for quantifying marker co-localization in fluorescence microscopy images.
To address the limitations of current methods, particularly their dependence on subjective thresholding and linearity assumptions.

Main Methods:

Proposed a novel Maximum Entropy Copula (MEC) method combining the Maximum Entropy Method (MEM) and Gaussian Copula.
Estimated the bivariate distribution function of two color channels to quantify co- or anti-colocalization.
Assessed spatial and nonlinear signal correlations for marker colocalization.

Main Results:

The MEC method accurately quantifies co- and anti-colocalization, outperforming traditional MEM for bivariate distributions.
Validated the MEC method on both simulated and real fluorescence microscopy data.
Demonstrated robust performance of MEC even in environments with high background noise.

Conclusions:

The Maximum Entropy Copula (MEC) offers a robust and reliable tool for co-localization analysis in fluorescence microscopy.
MEC provides a significant advancement over existing methods by handling nonlinear correlations and high background settings effectively.
This method enhances the quantitative analysis of protein localization and biological processes within the cell nucleus.