BiGG

BiGG: A biochemical genetic and genomic knowledgebase of large scale metabolic reconstructions. 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.


References in zbMATH (referenced in 10 articles )

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  1. Su, Yansen; Zhu, Huole; Zhang, Lei; Zhang, Xingyi: Identifying disease modules based on connectivity and semantic similarities (2020)
  2. Xu, Zixiang; Guo, Jing; Yue, Yunxia; Meng, Jing; Sun, Xiao: \textitInsilico genome-scale reconstruction and analysis of the \textitShewanellaloihica PV-4 metabolic network (2018)
  3. De Martino, Daniele; Masoero, Davide: Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth (2016)
  4. Harwood, Stuart M.; Höffner, Kai; Barton, Paul I.: Efficient solution of ordinary differential equations with a parametric lexicographic linear program embedded (2016)
  5. Höffner, Kai; Khan, Kamil A.; Barton, Paul I.: Generalized derivatives of dynamic systems with a linear program embedded (2016)
  6. Reimers, Arne C.; Goldstein, Yaron; Bockmayr, Alexander: Generic flux coupling analysis (2015)
  7. Kasabov, Nikola (ed.): Springer handbook of bio-/neuro-informatics (2014)
  8. Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel: Parallelization of nullspace algorithm for the computation of metabolic pathways (2011)
  9. Van Beek, Johannes H. G. M.; Supandi, Farahaniza; Gavai, Anand K.; De Graaf, Albert A.; Binsl, Thomas W.; Hettling, Hannes: Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism (2011)
  10. Schellenberger, Jan; Park, Junyoung O.; Conrad, Tom M.; Palsson, Bernhard O.: Bigg: a biochemical genetic and genomic knowledgebase of large scale metabolic reconstructions (2010) ioport