Nucleic Acids Research Advance Access originally published online on November 29, 2006
Nucleic Acids Research 2007 35(Database issue):D599-D603; doi:10.1093/nar/gkl936
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Nucleic Acids Research, 2007, Vol. 35, Database issue D599-D603
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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AgBase: a unified resource for functional analysis in agriculture
1 Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University PO Box 6100, Mississippi, MS 39762, USA 2 Institute for Digital Biology, Mississippi State University MS 39762, USA 3 Department of Computer Science and Engineering, Bagley College of Engineering PO Box 9637, Mississippi, MS 39762, USA 4 USDA ARS Corn Host Plant Resistance Research Unit Box 5367, Mississippi, MS 39762, USA 5 Department of Crop and Soil Sciences, The Pennsylvania State University University Park, PA 16802, USA 6 Mississippi Agricultural and Forestry Experiment Station, Mississippi State University MS 39762, USA
*To whom correspondence should be addressed. Tel: +1 662 325 5859; Fax: +1 662 325 1031; Email: fmccarthy{at}cvm.msstate.edu
Received August 15, 2006. Revised October 11, 2006. Accepted October 12, 2006.
Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource ‘AgBase’ (www.agbase.msstate.edu). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
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