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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Cells |
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| Online Access: | https://www.mdpi.com/2073-4409/11/19/3105 |
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| author | Bálint Barna H. Kovács Dániel Varga Dániel Sebők Hajnalka Majoros Róbert Polanek Tibor Pankotai Katalin Hideghéty Ákos Kukovecz Miklós Erdélyi |
| author_facet | Bálint Barna H. Kovács Dániel Varga Dániel Sebők Hajnalka Majoros Róbert Polanek Tibor Pankotai Katalin Hideghéty Ákos Kukovecz Miklós Erdélyi |
| author_sort | Bálint Barna H. Kovács |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T21:53:19Z |
| format | Article |
| id | doaj.art-f33b6d3b424440698a4879c2ca2a0d15 |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-09T21:53:19Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-f33b6d3b424440698a4879c2ca2a0d152023-11-23T20:02:53ZengMDPI AGCells2073-44092022-10-011119310510.3390/cells11193105Application of Lacunarity for Quantification of Single Molecule Localization Microscopy ImagesBálint Barna H. Kovács0Dániel Varga1Dániel Sebők2Hajnalka Majoros3Róbert Polanek4Tibor Pankotai5Katalin Hideghéty6Ákos Kukovecz7Miklós Erdélyi8Department of Optics and Quantum Electronics, University of Szeged, 6720 Szeged, HungaryDepartment of Optics and Quantum Electronics, University of Szeged, 6720 Szeged, HungaryDepartment of Applied and Environmental Chemistry, University of Szeged, 6720 Szeged, HungaryInstitute of Pathology, Albert Szent-Györgyi Medical School, University of Szeged, 6725 Szeged, HungaryBiomedical Applications Group, ELI-ALPS Research Institute, ELI-HU Non-Profit Ltd., 6728 Szeged, HungaryInstitute of Pathology, Albert Szent-Györgyi Medical School, University of Szeged, 6725 Szeged, HungaryBiomedical Applications Group, ELI-ALPS Research Institute, ELI-HU Non-Profit Ltd., 6728 Szeged, HungaryDepartment of Applied and Environmental Chemistry, University of Szeged, 6720 Szeged, HungaryDepartment of Optics and Quantum Electronics, University of Szeged, 6720 Szeged, HungaryThe 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.https://www.mdpi.com/2073-4409/11/19/3105lacunaritydSTORMquantitative analysis |
| spellingShingle | Bálint Barna H. Kovács Dániel Varga Dániel Sebők Hajnalka Majoros Róbert Polanek Tibor Pankotai Katalin Hideghéty Ákos Kukovecz Miklós Erdélyi Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images Cells lacunarity dSTORM quantitative analysis |
| 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 | lacunarity dSTORM quantitative analysis |
| url | https://www.mdpi.com/2073-4409/11/19/3105 |
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