Journal Article

Seeing Is Believing: On the Use of Image Databases for Visually Exploring Plant Organelle Dynamics

Shoji Mano, Tomoki Miwa, Shuh-ichi Nishikawa, Tetsuro Mimura and Mikio Nishimura

in Plant and Cell Physiology

Published on behalf of Japanese Society of Plant Physiologists

Volume 50, issue 12, pages 2000-2014
Published in print December 2009 | ISSN: 0032-0781
Published online September 2009 | e-ISSN: 1471-9053 | DOI: https://dx.doi.org/10.1093/pcp/pcp128
Seeing Is Believing: On the Use of Image Databases for Visually Exploring Plant Organelle Dynamics

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  • Biochemistry
  • Molecular and Cell Biology
  • Plant Sciences and Forestry

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Organelle dynamics vary dramatically depending on cell type, developmental stage and environmental stimuli, so that various parameters, such as size, number and behavior, are required for the description of the dynamics of each organelle. Imaging techniques are superior to other techniques for describing organelle dynamics because these parameters are visually exhibited. Therefore, as the results can be seen immediately, investigators can more easily grasp organelle dynamics. At present, imaging techniques are emerging as fundamental tools in plant organelle research, and the development of new methodologies to visualize organelles and the improvement of analytical tools and equipment have allowed the large-scale generation of image and movie data. Accordingly, image databases that accumulate information on organelle dynamics are an increasingly indispensable part of modern plant organelle research. In addition, image databases are potentially rich data sources for computational analyses, as image and movie data reposited in the databases contain valuable and significant information, such as size, number, length and velocity. Computational analytical tools support image-based data mining, such as segmentation, quantification and statistical analyses, to extract biologically meaningful information from each database and combine them to construct models. In this review, we outline the image databases that are dedicated to plant organelle research and present their potential as resources for image-based computational analyses.

Keywords: Arabidopsis thaliana; Image database; Imaging; Organelle dynamics; Quantification; Systems biology

Journal Article.  7091 words.  Illustrated.

Subjects: Biochemistry ; Molecular and Cell Biology ; Plant Sciences and Forestry

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