Fusion detection in time-lapse microscopy images : application to lipid droplets coalescence in plant seeds
| Autor: | Alain Trubuil, François Deslandes, Béatrice Laroche |
|---|---|
| Přispěvatelé: | Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE), Institut National de la Recherche Agronomique (INRA) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Coalescence (physics) Fusion [SDV]Life Sciences [q-bio] technology industry and agriculture Nanotechnology Biology complex mixtures Time-lapse microscopy Lipid Droplet Proteins 03 medical and health sciences 030104 developmental biology Control and Systems Engineering image analysis Lipid droplet Microscopy cell biology microscopy [INFO]Computer Science [cs] Event detection multitarget tracking Oleosin [MATH]Mathematics [math] Biological system |
| Zdroj: | IFAC-Papers IFAC-PapersOnLine, Elsevier, 2016, 49 (26), pp.239-244. ⟨10.1016/j.ifacol.2016.12.132⟩ 6th IFAC Conference on Foundations of Systems Biology in Engineering 6th IFAC Conference on Foundations of Systems Biology in Engineering, Oct 2016, Magdeburg, Germany. pp.6, ⟨10.1016/j.ifacol.2016.12.132⟩ |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2016.12.132⟩ |
| Popis: | International audience; Detecting fusion events between lipid droplets of Arabidopsis thaliana embryos is of significant interest to understand the role of lipid droplet proteins. Lipid droplet proteins, called oleosins, have been shown to influence the size of lipid droplets possibly by preventing coalescence. We propose to detect fusion events in timelapse microscopy images of several oleosin deficient A. thaliana embryos. To detect volume preserving fusion events in a dense environment, we propose a procedure based on particle tracking and statistical tests. Using synthetic data, we compare the performances of our method to heuristic decision rules adapted from tracking algorithms from the literature. |
| Databáze: | OpenAIRE |
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