Tracing and tracking filamentous structures across scales: A systematic review
Filamentous structures are ubiquitous in nature, are studied in diverse scientific fields, and span vastly different spatial scales. Filamentous structures in biological systems fulfill different functions and often form dynamic networks that respond to perturbations. Therefore, characterizing the p...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037022005803 |
| _version_ | 1797384123728265216 |
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| author | Isabella Østerlund Staffan Persson Zoran Nikoloski |
| author_facet | Isabella Østerlund Staffan Persson Zoran Nikoloski |
| author_sort | Isabella Østerlund |
| collection | DOAJ |
| description | Filamentous structures are ubiquitous in nature, are studied in diverse scientific fields, and span vastly different spatial scales. Filamentous structures in biological systems fulfill different functions and often form dynamic networks that respond to perturbations. Therefore, characterizing the properties of filamentous structures and the networks they form is important to gain better understanding of systems level functions and dynamics. Filamentous structures are captured by various imaging technologies, and analysis of the resulting imaging data addresses two problems: (i) identification (tracing) of filamentous structures in a single snapshot and (ii) characterizing the dynamics (i.e., tracking) of filamentous structures over time. Therefore, considerable research efforts have been made in developing automated methods for tracing and tracking of filamentous structures. Here, we provide a systematic review in which we present, categorize, and discuss the state-of-the-art methods for tracing and tracking of filamentous structures in sparse and dense networks. We highlight the mathematical approaches, assumptions, and constraints particular for each method, allowing us to pinpoint outstanding challenges and offer perspectives for future research aimed at gaining better understanding of filamentous structures in biological systems. |
| first_indexed | 2024-03-08T21:30:57Z |
| format | Article |
| id | doaj.art-3975075cd3a349438c1ecd29fd7e7f97 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-08T21:30:57Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-3975075cd3a349438c1ecd29fd7e7f972023-12-21T07:30:30ZengElsevierComputational and Structural Biotechnology Journal2001-03702023-01-0121452462Tracing and tracking filamentous structures across scales: A systematic reviewIsabella Østerlund0Staffan Persson1Zoran Nikoloski2Department of Plant and Environmental Sciences, University of Copenhagen, 1871 Frederiksberg, Denmark,; Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, GermanyDepartment of Plant and Environmental Sciences, University of Copenhagen, 1871 Frederiksberg, Denmark,Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany; Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany; Corresponding author at: Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany.Filamentous structures are ubiquitous in nature, are studied in diverse scientific fields, and span vastly different spatial scales. Filamentous structures in biological systems fulfill different functions and often form dynamic networks that respond to perturbations. Therefore, characterizing the properties of filamentous structures and the networks they form is important to gain better understanding of systems level functions and dynamics. Filamentous structures are captured by various imaging technologies, and analysis of the resulting imaging data addresses two problems: (i) identification (tracing) of filamentous structures in a single snapshot and (ii) characterizing the dynamics (i.e., tracking) of filamentous structures over time. Therefore, considerable research efforts have been made in developing automated methods for tracing and tracking of filamentous structures. Here, we provide a systematic review in which we present, categorize, and discuss the state-of-the-art methods for tracing and tracking of filamentous structures in sparse and dense networks. We highlight the mathematical approaches, assumptions, and constraints particular for each method, allowing us to pinpoint outstanding challenges and offer perspectives for future research aimed at gaining better understanding of filamentous structures in biological systems.http://www.sciencedirect.com/science/article/pii/S2001037022005803CytoskeletonFilamentous StructuresImage processingTracingTrackingDeep learning |
| spellingShingle | Isabella Østerlund Staffan Persson Zoran Nikoloski Tracing and tracking filamentous structures across scales: A systematic review Computational and Structural Biotechnology Journal Cytoskeleton Filamentous Structures Image processing Tracing Tracking Deep learning |
| title | Tracing and tracking filamentous structures across scales: A systematic review |
| title_full | Tracing and tracking filamentous structures across scales: A systematic review |
| title_fullStr | Tracing and tracking filamentous structures across scales: A systematic review |
| title_full_unstemmed | Tracing and tracking filamentous structures across scales: A systematic review |
| title_short | Tracing and tracking filamentous structures across scales: A systematic review |
| title_sort | tracing and tracking filamentous structures across scales a systematic review |
| topic | Cytoskeleton Filamentous Structures Image processing Tracing Tracking Deep learning |
| url | http://www.sciencedirect.com/science/article/pii/S2001037022005803 |
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