Literature DB >> 24092884

The Plant Organelles Database 3 (PODB3) update 2014: integrating electron micrographs and new options for plant organelle research.

Shoji Mano1, Takanori Nakamura, Maki Kondo, Tomoki Miwa, Shuh-ichi Nishikawa, Tetsuro Mimura, Akira Nagatani, Mikio Nishimura.   

Abstract

The Plant Organelles Database 2 (PODB2), which was first launched in 2006 as PODB, provides static image and movie data of plant organelles, protocols for plant organelle research and external links to relevant websites. PODB2 has facilitated plant organellar research and the understanding of plant organelle dynamics. To provide comprehensive information on plant organelles in more detail, PODB2 was updated to PODB3 (http://podb.nibb.ac.jp/Organellome/). PODB3 contains two additional components: the electron micrograph database and the perceptive organelles database. Through the electron micrograph database, users can examine the subcellular and/or suborganellar structures in various organs of wild-type and mutant plants. The perceptive organelles database provides information on organelle dynamics in response to external stimuli. In addition to the extra components, the user interface for access has been enhanced in PODB3. The data in PODB3 are directly submitted by plant researchers and can be freely downloaded for use in further analysis. PODB3 contains all the information included in PODB2, and the volume of data and protocols deposited in PODB3 continue to grow steadily. We welcome contributions of data from all plant researchers to enhance the utility and comprehensiveness of PODB3.

Keywords:  Database; Electron micrograph; Organelle dynamics; PODB; Perception

Mesh:

Year:  2013        PMID: 24092884     DOI: 10.1093/pcp/pct140

Source DB:  PubMed          Journal:  Plant Cell Physiol        ISSN: 0032-0781            Impact factor:   4.927


  4 in total

1.  Use of diffusion magnetic resonance imaging to correlate the developmental changes in grape berry tissue structure with water diffusion patterns.

Authors:  Ryan J Dean; Timothy Stait-Gardner; Simon J Clarke; Suzy Y Rogiers; Gabriele Bobek; William S Price
Journal:  Plant Methods       Date:  2014-11-04       Impact factor: 4.993

2.  Semi-automatic organelle detection on transmission electron microscopic images.

Authors:  Takumi Higaki; Natsumaro Kutsuna; Kae Akita; Mayuko Sato; Fumie Sawaki; Megumi Kobayashi; Noriko Nagata; Kiminori Toyooka; Seiichiro Hasezawa
Journal:  Sci Rep       Date:  2015-01-15       Impact factor: 4.379

3.  Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity.

Authors:  Joanna M Chustecki; Daniel J Gibbs; George W Bassel; Iain G Johnston
Journal:  Cell Syst       Date:  2021-05-10       Impact factor: 10.304

4.  RARGE II: an integrated phenotype database of Arabidopsis mutant traits using a controlled vocabulary.

Authors:  Kenji Akiyama; Atsushi Kurotani; Kei Iida; Takashi Kuromori; Kazuo Shinozaki; Tetsuya Sakurai
Journal:  Plant Cell Physiol       Date:  2013-11-21       Impact factor: 4.927

  4 in total

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