Introduction

MOTIVATION: Knowing the subcellular location of proteins is critical for understanding their function and developing accurate networks representing eukaryotic biological processes. Many computational tools have been developed to predict proteome-wide subcellular location, and abundant experimental data from green fluorescent protein (GFP) tagging or mass spectrometry (MS) are available in the model plant, Arabidopsis. None of these approaches is error-free, and thus, results are often contradictory. RESULTS: To help unify these multiple data sources, we have developed the SUBcellular Arabidopsis consensus (SUBAcon) algorithm, a naive Bayes classifier that integrates 22 computational prediction algorithms, experimental GFP and MS localizations, protein-protein interaction and co-expression data to derive a consensus call and probability. SUBAcon classifies protein location in Arabidopsis more accurately than single predictors. AVAILABILITY: SUBAcon is a useful tool for recovering proteome-wide subcellular locations of Arabidopsis proteins and is displayed in the SUBA3 database (http://suba.plantenergy.uwa.edu.au). The source code and input data is available through the SUBA3 server (http://suba.plantenergy.uwa.edu.au//SUBAcon.html) and the Arabidopsis SUbproteome REference (ASURE) training set can be accessed using the ASURE web portal (http://suba.plantenergy.uwa.edu.au/ASURE).

Publications

  1. SUBAcon: a consensus algorithm for unifying the subcellular localization data of the Arabidopsis proteome.
    Cite this
    Hooper CM, Tanz SK, Castleden IR, Vacher MA, Small ID, Millar AH, 2014-12-01 - Bioinformatics (Oxford, England)

Credits

  1. Cornelia M Hooper
    Developer

    Centre of Excellence in Computational Systems Biology, The University of Western Australia, Australia

  2. Sandra K Tanz
    Developer

    Centre of Excellence in Computational Systems Biology, The University of Western Australia, Australia

  3. Ian R Castleden
    Developer

    Centre of Excellence in Computational Systems Biology, The University of Western Australia, Australia

  4. Michael A Vacher
    Developer

    Centre of Excellence in Computational Systems Biology, The University of Western Australia, Australia

  5. Ian D Small
    Developer

    Centre of Excellence in Computational Systems Biology, The University of Western Australia, Australia

  6. A Harvey Millar
    Investigator

    Centre of Excellence in Computational Systems Biology, The University of Western Australia, Australia

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Summary
AccessionBT000017
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Country/RegionAustralia
Submitted ByA Harvey Millar