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Updated: Jan 5, 2026

Mapping Absolute DNA Density in Cell Nuclei using Single-molecule Localization Microscopy

Mapping Absolute DNA Density in Cell Nuclei using Single-molecule Localization Microscopy

Published on: November 11, 2025

Topological data analysis quantifies biological nano-structure from single molecule localization microscopy.

Jeremy A Pike^1,2, Abdullah O Khan^1,2, Chiara Pallini^1,2

¹Centre of Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham, Midlands, UK.

Bioinformatics (Oxford, England)

|October 19, 2019

Summary

This summary is machine-generated.

This study introduces a new segmentation protocol using persistence-based clustering for analyzing localization microscopy data. The method enhances the quantification of complex molecular organization and nano-structure, outperforming existing techniques.

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Area of Science:

Biophysics
Computational Biology
Microscopy

Background:

Localization microscopy generates point cloud data representing molecular positions.
Current analysis methods like clustering have limitations in quantifying complex nano-structures.
There is a need for advanced analytical tools to probe densely packed molecular assemblies.

Purpose of the Study:

To develop and present a novel segmentation protocol for analyzing localization microscopy data.
To improve the quantification of complex molecular organization and nano-structure.
To provide a flexible R package (RSMLM) for pointillist-based analysis.

Main Methods:

Application of persistence-based clustering to point cloud data.
Utilizing persistent homology to quantify topological structures.
Development of the RSMLM R package for 2D and 3D data analysis.

Main Results:

The new protocol demonstrates increased segmentation performance over state-of-the-art methods.
Persistent homology provides novel insights into the topological shapes of molecular architecture.
The methods were successfully applied to diverse biological systems including platelets, nuclear pores, and microtubules.

Conclusions:

The developed persistence-based segmentation protocol offers a powerful approach for analyzing complex localization microscopy data.
RSMLM provides a flexible and robust tool for researchers studying molecular organization at the nanoscale.
This work advances the quantitative analysis of sub-diffraction resolution microscopy data.