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

Zachary A King1, Justin Lu1, Andreas Dräger2

  • 1Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.

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|October 18, 2015
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Summary
This summary is machine-generated.

BiGG Models is a new knowledge base offering over 75 curated genome-scale metabolic models. This resource enhances systems biology research by providing standardized, accessible metabolic models and tools for analysis.

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Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Bioinformatics

Background:

  • Genome-scale metabolic models are crucial for predicting cellular functions and testing hypotheses.
  • High-quality, standardized, and accessible model repositories are needed to maximize their utility.
  • Existing resources often lack comprehensive curation, standardization, and integration with external databases.

Purpose of the Study:

  • To present BiGG Models, a redesigned Biochemical, Genetic and Genomic knowledge base.
  • To provide a centralized repository of high-quality, manually-curated genome-scale metabolic models.
  • To enhance accessibility and utility of metabolic models for systems biology research.

Main Methods:

  • Developed a redesigned Biochemical, Genetic and Genomic knowledge base (BiGG Models).
  • Manually curated over 75 genome-scale metabolic models.
  • Standardized reaction and metabolite identifiers across models.
  • Integrated genome annotations and external databases.
  • Developed a comprehensive application programming interface (API).

Main Results:

  • BiGG Models hosts over 75 high-quality, manually-curated genome-scale metabolic models.
  • The platform offers browsing, searching, and visualization tools for models.
  • Models are linked to genome annotations and external databases.
  • Standardized identifiers facilitate cross-model comparisons.
  • An API enables programmatic access for modeling and analysis tools.

Conclusions:

  • BiGG Models provides a valuable resource for systems biology research.
  • Standardized and accessible metabolic models facilitate knowledge-based analysis of experimental data.
  • The platform supports diverse research applications in metabolic engineering and beyond.