BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

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ID: 300918
2015
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Abstract
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.
Reference Key
openalex_W2202347610 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zachary A. King, Justin S. Lu, Andreas Dräger, Philip Miller, Stephen Federowicz, Joshua A. Lerman, Ali Ebrahim, Bernhard Ø. Palsson, Nathan E. Lewis
Journal Nucleic Acids Research
Year 2015
DOI
10.1093/nar/gkv1049
URL
https://academic.oup.com/nar/article-pdf/44/D1/D515/16661243/gkv1049.pdf
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