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Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images
The quantitative analysis of datasets achieved by single molecule localization microscopy is vital for studying the structure of subcellular organizations. Cluster analysis has emerged as a multi-faceted tool in the structural analysis of localization datasets. However, the results it produces great...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562870/ https://www.ncbi.nlm.nih.gov/pubmed/36231067 http://dx.doi.org/10.3390/cells11193105 |
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author | Kovács, Bálint Barna H. Varga, Dániel Sebők, Dániel Majoros, Hajnalka Polanek, Róbert Pankotai, Tibor Hideghéty, Katalin Kukovecz, Ákos Erdélyi, Miklós |
author_facet | Kovács, Bálint Barna H. Varga, Dániel Sebők, Dániel Majoros, Hajnalka Polanek, Róbert Pankotai, Tibor Hideghéty, Katalin Kukovecz, Ákos Erdélyi, Miklós |
author_sort | Kovács, Bálint Barna H. |
collection | PubMed |
description | The quantitative analysis of datasets achieved by single molecule localization microscopy is vital for studying the structure of subcellular organizations. Cluster analysis has emerged as a multi-faceted tool in the structural analysis of localization datasets. However, the results it produces greatly depend on the set parameters, and the process can be computationally intensive. Here we present a new approach for structural analysis using lacunarity. Unlike cluster analysis, lacunarity can be calculated quickly while providing definitive information about the structure of the localizations. Using simulated data, we demonstrate how lacunarity results can be interpreted. We use these interpretations to compare our lacunarity analysis with our previous cluster analysis-based results in the field of DNA repair, showing the new algorithm’s efficiency. |
format | Online Article Text |
id | pubmed-9562870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95628702022-10-15 Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images Kovács, Bálint Barna H. Varga, Dániel Sebők, Dániel Majoros, Hajnalka Polanek, Róbert Pankotai, Tibor Hideghéty, Katalin Kukovecz, Ákos Erdélyi, Miklós Cells Article The quantitative analysis of datasets achieved by single molecule localization microscopy is vital for studying the structure of subcellular organizations. Cluster analysis has emerged as a multi-faceted tool in the structural analysis of localization datasets. However, the results it produces greatly depend on the set parameters, and the process can be computationally intensive. Here we present a new approach for structural analysis using lacunarity. Unlike cluster analysis, lacunarity can be calculated quickly while providing definitive information about the structure of the localizations. Using simulated data, we demonstrate how lacunarity results can be interpreted. We use these interpretations to compare our lacunarity analysis with our previous cluster analysis-based results in the field of DNA repair, showing the new algorithm’s efficiency. MDPI 2022-10-02 /pmc/articles/PMC9562870/ /pubmed/36231067 http://dx.doi.org/10.3390/cells11193105 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kovács, Bálint Barna H. Varga, Dániel Sebők, Dániel Majoros, Hajnalka Polanek, Róbert Pankotai, Tibor Hideghéty, Katalin Kukovecz, Ákos Erdélyi, Miklós Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images |
title | Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images |
title_full | Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images |
title_fullStr | Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images |
title_full_unstemmed | Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images |
title_short | Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images |
title_sort | application of lacunarity for quantification of single molecule localization microscopy images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562870/ https://www.ncbi.nlm.nih.gov/pubmed/36231067 http://dx.doi.org/10.3390/cells11193105 |
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