Quantitative data analysis in single-molecule localization microscopy
Super-resolution microscopy, and specifically single-molecule localization microscopy (SMLM), is becoming a transformative technology for cell biology, as it allows the study of cellular structures with nanometer resolution. Here, we review a wide range of data analyses approaches for SMLM that extr...
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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
20 August 2020
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| In: |
Trends in cell biology
Year: 2020, Jahrgang: 30, Heft: 11, Pages: 837-851 |
| ISSN: | 1879-3088 |
| DOI: | 10.1016/j.tcb.2020.07.005 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.tcb.2020.07.005 Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S096289242030146X 
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| Verfasserangaben: | Yu-Le Wu, Aline Tschanz, Leonard Krupnik, and Jonas Ries |
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| 520 | |a Super-resolution microscopy, and specifically single-molecule localization microscopy (SMLM), is becoming a transformative technology for cell biology, as it allows the study of cellular structures with nanometer resolution. Here, we review a wide range of data analyses approaches for SMLM that extract quantitative information about the distribution, size, shape, spatial organization, and stoichiometry of macromolecular complexes to guide biological interpretation. We present a case study using the nuclear pore complex as an example that highlights the power of combining complementary approaches by identifying its symmetry, ringlike structure, and protein copy number. In face of recent technical and computational advances, this review serves as a guideline for selecting appropriate analysis tools and controls to exploit the potential of SMLM for a wide range of biological questions. | ||
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