The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions
Open accessAbstract
Background: Genome-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. Description: We 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. Conclusions: BiGG 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.
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Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.308 · Cited by 1,835
Self-citationA protocol for generating a high-quality genome-scale metabolic reconstruction
Thiele, I., & Palsson, B. Ø. (2010) · Nature Protocols · doi:10.1038/nprot.2009.203 · Cited by 1,789
Self-citationE-CELL: software environment for whole-cell simulation
Tomita, M., Hashimoto, K., Takahashi, K., Shimizu, T. S., Matsuzaki, Y., Miyoshi, F., Saito, K., Tanida, S., Yugi, K., Venter, J. C., et al. (1999) · Bioinformatics · doi:10.1093/bioinformatics/15.1.72 · Cited by 764
Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., Blüthgen, N., Borger, S., Costenoble, R., Heinemann, M., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1492 · Cited by 588
Self-citationThe growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli
Feist, A. M., & Palsson, B. Ø. (2008) · Nature Biotechnology · doi:10.1038/nbt1401 · Cited by 545 · cited 1×
“Case studies have been reviewed in [10].”
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Cited by
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Schellenberger, J., Que, R., Fleming, R. M. T., Thiele, I., Orth, J. D., Feist, A. M., Zielinski, D. C., Bordbar, A., Lewis, N. E., Rahmanian, S., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.308 · Cited by 1,835
Self-citationKBase: The United States Department of Energy Systems Biology Knowledgebase
(2018) · doi:10.1038/nbt.4163 · Cited by 1,624
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
King, Z. A., Lu, J., Dräger, A., Miller, P., Federowicz, S., Lerman, J. A., Ebrahim, A., Palsson, B. O., & Lewis, N. E. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1049 · Cited by 938
Self-citationPopularity versus similarity in growing networks
Papadopoulos, F., Kitsak, M., Serrano, M. Á., Boguñá, M., & Krioukov, D. (2012) · Nature · doi:10.1038/nature11459 · Cited by 634
Metabolite concentrations, fluxes and free energies imply efficient enzyme usage
Park, J. O., Rubin, S. A., Xu, Y.-F., Amador-Noguez, D., Fan, J., Shlomi, T., & Rabinowitz, J. D. (2016) · Nature Chemical Biology · doi:10.1038/nchembio.2077 · Cited by 453
Metadata
- Authors
- Schellenberger, J., Park, J. O., Conrad, T. M., & Palsson, B. Ø.
- Venue
- BMC Bioinformatics
- Published
- 2010-04-29
- Volume
- 11
- Issue
- 1
- Pages
- 213-213
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W2075283200
- Cited by
- 583
- References
- 5
- FWCI
- 20.20
- Type
- journal article
- Language
- en
- Open access
- gold
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