Database Commons

a catalog of biological databases

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Database Profile

General information

URL: http://suba.plantenergy.uwa.edu.au/
Full name: The SUBcellular localisation Database for Arabidopsis Proteins
Description: A database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis
Year founded: 2012
Last update: 2016-06-30
Version: v4.0
Accessibility:
Manual:
Accessible
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Country/Region: Australia
Data type:
Data object:
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Contact information

University/Institution: The University of Western Australia
Address: Perth,WA 6009,Australia
City: Perth
Province/State: WA
Country/Region: Australia
Contact name (PI/Team): Harvey A. Millar
Contact email (PI/Helpdesk): harvey.millar@uwa.edu.au

Publications

27899614
SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations. [PMID: 27899614]
Hooper CM, Castleden IR, Tanz SK, Aryamanesh N, Millar AH.

The SUBcellular location database for Arabidopsis proteins (SUBA4, http://suba.live) is a comprehensive collection of manually curated published data sets of large-scale subcellular proteomics, fluorescent protein visualization, protein-protein interaction (PPI) as well as subcellular targeting calls from 22 prediction programs. SUBA4 contains an additional 35 568 localizations totalling more than 60 000 experimental protein location claims as well as 37 new suborganellar localization categories. The experimental PPI data has been expanded to 26 327 PPI pairs including 856 PPI localizations from experimental fluorescent visualizations. The new SUBA4 user interface enables users to choose quickly from the filter categories: 'subcellular location', 'protein properties', 'protein-protein interaction' and 'affiliations' to build complex queries. This allows substantial expansion of search parameters into 80 annotation types comprising 1 150 204 new annotations to study metadata associated with subcellular localization. The 'BLAST' tab contains a sequence alignment tool to enable a sequence fragment from any species to find the closest match in Arabidopsis and retrieve data on subcellular location. Using the location consensus SUBAcon, the SUBA4 toolbox delivers three novel data services allowing interactive analysis of user data to provide relative compartmental protein abundances and proximity relationship analysis of PPI and coexpression partners from a submitted list of Arabidopsis gene identifiers. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2017:45(D1) | 84 Citations (from Europe PMC, 2021-06-19)
23180787
SUBA3: a database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis. [PMID: 23180787]
Tanz SK, Castleden I, Hooper CM, Vacher M, Small I, Millar HA.

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.

Nucleic Acids Res. 2013:41(Database issue) | 156 Citations (from Europe PMC, 2021-06-19)
17071959
SUBA: the Arabidopsis Subcellular Database. [PMID: 17071959]
Heazlewood JL, Verboom RE, Tonti-Filippini J, Small I, Millar AH.

Knowledge of protein localisation contributes towards our understanding of protein function and of biological inter-relationships. A variety of experimental methods are currently being used to produce localisation data that need to be made accessible in an integrated manner. Chimeric fluorescent fusion proteins have been used to define subcellular localisations with at least 1100 related experiments completed in Arabidopsis. More recently, many studies have employed mass spectrometry to undertake proteomic surveys of subcellular components in Arabidopsis yielding localisation information for approximately 2600 proteins. Further protein localisation information may be obtained from other literature references to analysis of locations (AmiGO: approximately 900 proteins), location information from Swiss-Prot annotations (approximately 2000 proteins); and location inferred from gene descriptions (approximately 2700 proteins). Additionally, an increasing volume of available software provides location prediction information for proteins based on amino acid sequence. We have undertaken to bring these various data sources together to build SUBA, a SUBcellular location database for Arabidopsis proteins. The localisation data in SUBA encompasses 10 distinct subcellular locations, >6743 non-redundant proteins and represents the proteins encoded in the transcripts responsible for 51% of Arabidopsis expressed sequence tags. The SUBA database provides a powerful means by which to assess protein subcellular localisation in Arabidopsis (http://www.suba.bcs.uwa.edu.au).

Nucleic Acids Res. 2007:35(Database issue) | 267 Citations (from Europe PMC, 2021-06-19)

Ranking

All databases:
253/5061 (95.021%)
Expression:
31/924 (96.753%)
Interaction:
37/771 (95.331%)
Literature:
28/384 (92.969%)
253
Total Rank
507
Citations
36.214
z-index

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Record metadata

Created on: 2015-06-20
Curated by:
Lina Ma [2018-06-06]
Shixiang Sun [2017-02-20]
Lin Xia [2016-03-28]
Lin Xia [2015-06-26]