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Computational Approaches to Revisiting Plant Cytoskeleton Organization and Dynamics.

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Τίτλος: Computational Approaches to Revisiting Plant Cytoskeleton Organization and Dynamics.
Συγγραφείς: Ono H; Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan., Higaki T; Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan.; Faculty of Advanced Science and Technology, Kumamoto University, Kumamoto, Japan.
Πηγή: Cytoskeleton (Hoboken, N.J.) [Cytoskeleton (Hoboken)] 2026 Jun; Vol. 83 (6), pp. 376-383. Date of Electronic Publication: 2025 Jun 06.
Τύπος έκδοσης: Journal Article; Review
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wiley-Liss Country of Publication: United States NLM ID: 101523844 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1949-3592 (Electronic) Linking ISSN: 19493592 NLM ISO Abbreviation: Cytoskeleton (Hoboken) Subsets: MEDLINE
Imprint Name(s): Original Publication: Hoboken, NJ : Wiley-Liss, 2010-
Ιατρικοί όροι (MeSH): Cytoskeleton*/metabolism , Image Processing, Computer-Assisted*/methods , Plants*/metabolism, Microtubules/metabolism
Περίληψη: Live-cell imaging has enabled the visualization of cytoskeletal dynamics with high spatiotemporal resolution, producing vast, and complex datasets. Recent advancements in live-cell imaging techniques have significantly increased data dimensionality and throughput, challenging conventional qualitative analysis methods. Computational approaches, including machine learning-based image processing, have emerged as powerful tools for extracting quantitative features from these datasets, facilitating systematic analysis of cytoskeletal organization and dynamics. In this review, we outline image analysis techniques for quantification of cytoskeletal structures, focusing on microscopic image transformation and feature extraction. We discuss classical image-processing methods, such as filtering and segmentation, as well as recent applications of deep learning in cytoskeletal analysis. Furthermore, we revisit classical studies on cortical microtubule reorganization after plant cytokinesis, and explore how modern computational techniques can provide new insights into traditional concepts.
(© 2025 Wiley Periodicals LLC.)
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Grant Information: Japan Science and Technology Agency
Contributed Indexing: Keywords: cell cycle; cortical microtubule; deep learning; image analysis; tobacco BY‐2 cells
Entry Date(s): Date Created: 20250606 Date Completed: 20260619 Latest Revision: 20260619
Update Code: 20260619
DOI: 10.1002/cm.22049
PMID: 40474669
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1949-3592
DOI:10.1002/cm.22049