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

By Jan Schellenberger, Junyoung O. Park, Tom M. Conrad, Bernhard O. Palsson. BMC Bioinformatics, 2010

608 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4e6b635d34d3281b72c6587cdd79df77bee663ca

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Citations in the corpus

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways (2015, methodology): “The maps in the BiGG database are being converted to the new Escher format [33].”
Yarrowia lipolytica as an Oleaginous Cell Factory Platform for Production of Fatty Acid-Based Biofuel and Bioproducts (2014, methodology): “org/), BIGG (Schellenberger et al., 2010), and other related in silico approaches.”
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015, unknown): “The first BiGG knowledge base was published in 2010, and it addressed some of these challenges for a specific set of 10 GEMs generated at the Systems Biology Research Group at the University of California, San Diego (18).”
Popularity versus similarity in growing networks (2011, methodology): “coli metabolism from [34], reconstructed from data in the BiGG database [35, 36], iAF1260 version of the K12 MG1655 [37] strain.”
Control Principles of Complex Networks (2015, background): “For a metabolic network or an arbitrary biochemical reaction system, the topology of the inference diagram is uniquely determined by the full reaction list, which is relatively accurately known for several model organisms (Schellenberger et al., 2010).”