Journal Article

SUBA3: a database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis

Sandra K. Tanz, Ian Castleden, Cornelia M. Hooper, Michael Vacher, Ian Small and Harvey A. Millar

in Nucleic Acids Research

Volume 41, issue D1, pages D1185-D1191
Published in print January 2013 | ISSN: 0305-1048
Published online November 2012 | e-ISSN: 1362-4962 | DOI: http://dx.doi.org/10.1093/nar/gks1151

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The subcellular location database for Arabidopsis proteins (SUBA3, http://suba.plantenergy.uwa.edu.au) combines manual literature curation of large-scale subcellular proteomics, fluorescent protein visualization and protein–protein interaction (PPI) datasets with subcellular targeting calls from 22 prediction programs. More than 14 500 new experimental locations have been added since its first release in 2007. Overall, nearly 650 000 new calls of subcellular location for 35 388 non-redundant Arabidopsis proteins are included (almost six times the information in the previous SUBA version). A re-designed interface makes the SUBA3 site more intuitive and easier to use than earlier versions and provides powerful options to search for PPIs within the context of cell compartmentation. SUBA3 also includes detailed localization information for reference organelle datasets and incorporates green fluorescent protein (GFP) images for many proteins. To determine as objectively as possible where a particular protein is located, we have developed SUBAcon, a Bayesian approach that incorporates experimental localization and targeting prediction data to best estimate a protein’s location in the cell. The probabilities of subcellular location for each protein are provided and displayed as a pictographic heat map of a plant cell in SUBA3.

Journal Article.  3405 words.  Illustrated.

Subjects: Chemistry ; Biochemistry ; Bioinformatics and Computational Biology ; Genetics and Genomics ; Molecular and Cell Biology

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