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Status: Bibliographieeintrag

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Verfasst von:Weidner, Jonas [VerfasserIn]   i
 Neitzel, Charlotte [VerfasserIn]   i
 Gote, Martin [VerfasserIn]   i
 Deck, Jeanette [VerfasserIn]   i
 Küntzelmann, Kim [VerfasserIn]   i
 Pilarczyk, Götz [VerfasserIn]   i
 Falk, Martin [VerfasserIn]   i
 Hausmann, Michael [VerfasserIn]   i
Titel:Advanced image-free analysis of the nano-organization of chromatin and other biomolecules by Single Molecule Localization Microscopy (SMLM)
Verf.angabe:Jonas Weidner, Charlotte Neitzel, Martin Gote, Jeanette Deck, Kim Küntzelmann, Götz Pilarczyk, Martin Falk, Michael Hausmann
E-Jahr:2023
Jahr:16 March 2023
Umfang:17 S.
Fussnoten:Online verfügbar 9. März 2023, Artikelversion 16. März 2023 ; Gesehen am 21.04.2023
Titel Quelle:Enthalten in: Computational and structural biotechnology journal
Ort Quelle:Gotenburg : Research Network of Computational and Structural Biotechnology (RNCSB), 2012
Jahr Quelle:2023
Band/Heft Quelle:21(2023) vom: März, Seite 2018-2034
ISSN Quelle:2001-0370
Abstract:The cell as a system of many components, governed by the laws of physics and chemistry drives molecular functions having an impact on the spatial organization of these systems and vice versa. Since the relationship between structure and function is an almost universal rule not only in biology, appropriate methods are required to parameterize the relationship between the structure and function of biomolecules and their networks, the mechanisms of the processes in which they are involved, and the mechanisms of regulation of these processes. Single molecule localization microscopy (SMLM), which we focus on here, offers a significant advantage for the quantitative parametrization of molecular organization: it provides matrices of coordinates of fluorescently labeled biomolecules that can be directly subjected to advanced mathematical analytical procedures without the need for laborious and sometimes misleading image processing. Here, we propose mathematical tools for comprehensive quantitative computer data analysis of SMLM point patterns that include Ripley distance frequency analysis, persistent homology analysis, persistent ‘imaging’, principal component analysis and co-localization analysis. The application of these methods is explained using artificial datasets simulating different, potentially possible and interpretatively important situations. Illustrative analyses of real complex biological SMLM data are presented to emphasize the applicability of the proposed algorithms. This manuscript demonstrated the extraction of features and parameters quantifying the influence of chromatin (re)organization on genome function, offering a novel approach to study chromatin architecture at the nanoscale. However, the ability to adapt the proposed algorithms to analyze essentially any molecular organizations, e.g., membrane receptors or protein trafficking in the cytosol, offers broad flexibility of use.
DOI:doi:10.1016/j.csbj.2023.03.009
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1016/j.csbj.2023.03.009
 Volltext: https://www.sciencedirect.com/science/article/pii/S2001037023001083
 DOI: https://doi.org/10.1016/j.csbj.2023.03.009
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Application of mathematical analysis tools to chromatin organization and DNA repair processes
 Persistent homology
 Persistent image
 Principal component analysis
 Ripley distance frequency histograms
 Single molecule localization microscopy (SMLM)
K10plus-PPN:1843333414
Verknüpfungen:→ Zeitschrift

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