BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions

BMC Bioinformatics

Database

Junyoung O Park¹  Bernhard Ø Palsson¹  Jan Schellenberger²  Tom M Conrad³ 

[1] Bioengineering Department, University of California San Diego, 9500 Gilman Dr, 92093-0412, La Jolla, California, USA;Bioinformatics Program, University of California San Diego, 9500 Gilman Dr, 92093-0419, La Jolla, California, USA;Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Dr, 92093-0332, La Jolla, California, USA;

关键词: System Biology Markup Language;    Metabolic Reconstruction;    Scalable Vector Graphic;    Glucose Minimal Medium;    Flux Variability Analysis;   

DOI  :  10.1186/1471-2105-11-213

 received in 2009-03-04, accepted in 2010-04-29,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundGenome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use.DescriptionWe describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.ConclusionsBiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu.

【 授权许可】

Unknown   
© Schellenberger et al; licensee BioMed Central Ltd. 2010. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.