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Updated: Jul 18, 2026
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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
AgBase: a unified resource for functional analysis in agriculture
Fiona M McCarthy1, Susan M Bridges, Nan Wang
1Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, PO Box 6100, Mississippi, MS 39762, USA. fmccarthy@cvm.msstate.edu
Nucleic Acids Research
|December 1, 2006
Summary
AgBase enhances agricultural systems biology by improving genome annotation and providing Gene Ontology (GO) data. This resource aids researchers in analyzing functional genomics and proteomics datasets for agriculturally important species.
Area of Science:
- Agricultural genomics
- Systems biology
- Functional genomics
Background:
- Agricultural genome annotation is often poor, hindering functional genomics analysis.
- Systems biology approaches require robust genomic and proteomic data.
- Existing resources lack comprehensive, curated data for agricultural species.
Purpose of the Study:
- To establish AgBase, a public resource for agricultural systems biology.
- To improve structural and functional annotation of agriculturally relevant genomes.
- To facilitate the analysis of transcriptomics and proteomics data.
Main Methods:
- Experimental confirmation of electronically predicted proteins.
- Proteogenomic mapping to improve genome annotation.
- Development of a two-tier Gene Ontology (GO) annotation system ('GO Consortium' and 'Community').
Main Results:
- AgBase provides curated, web-accessible data for agricultural species.
- Improved genome annotation through experimental validation and proteogenomic mapping.
- Two tiers of GO annotations are available, distinguishing experimental and community-based data.
Conclusions:
- AgBase significantly facilitates systems biology research in agricultural species.
- The resource offers improved genome annotation and comprehensive GO annotations.
- Tools and data within AgBase empower agricultural researchers to analyze functional genomics data.
