Segmentation, 3D Reconstruction, and Analysis of PcG Proteins in Fluorescence Microscopy Images in Different Cell Culture Conditions.
Cellular and subcellular segmentation
Fluorescence microscopy
Image processing and analysis
Nuclear organization
PcG staining
Unsupervised classification algorithm
Variational segmentation model
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2023
2023
Historique:
medline:
24
5
2023
pubmed:
22
5
2023
entrez:
22
5
2023
Statut:
ppublish
Résumé
Polycomb-group (PcG) of proteins are evolutionarily conserved transcription factors necessary for the regulation of gene expression during the development and the safeguard of cell identity in adulthood. In the nucleus, they form aggregates whose positioning and dimension are fundamental for their function. We present an algorithm, and its MATLAB implementation, based on mathematical methods to detect and analyze PcG proteins in fluorescence cell image z-stacks. Our algorithm provides a method to measure the number, the size, and the relative positioning of the PcG bodies in the nucleus for a better understanding of their spatial distribution, and thus of their role for a correct genome conformation and function.
Identifiants
pubmed: 37212995
doi: 10.1007/978-1-0716-3143-0_12
doi:
Substances chimiques
Polycomb-Group Proteins
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
147-169Informations de copyright
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
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