Abstract
The BiGG Models knowledge base (http://bigg.ucsd.edu) is a centralized repository for high-quality genome-scale metabolic models. For the past 12 years, the website has allowed users to browse and search metabolic models. Within this update, we detail new content and features in the repository, continuing the original effort to connect each model to genome annotations and external databases as well as standardization of reactions and metabolites. We describe the addition of 31 new models that expand the portion of the phylogenetic tree covered by BiGG Models. We also describe new functionality for hosting multi-strain models, which have proven to be insightful in a variety of studies centered on comparisons of related strains. Finally, the models in the knowledge base have been benchmarked using Memote, a new community-developed validator for genome-scale models to demonstrate the improving quality and transparency of model content in BiGG Models.
Highlights
BiGG Models was initially released in 2010 as a knowledge base of biochemically, genetically and genomically structured genome-scale metabolic network reconstructions, and the first release was followed by a complete redesign in 2016 [1,2]
We describe the addition of 31 new models that expand the portion of the phylogenetic tree covered by BiGG Models
We demonstrate that the new genome-scale metabolic models (GEMs) valuably expand the portion of the reactome encapsulated by the knowledge base
Summary
BiGG Models (http://bigg.ucsd.edu) was initially released in 2010 as a knowledge base of biochemically, genetically and genomically structured genome-scale metabolic network reconstructions, and the first release was followed by a complete redesign in 2016 [1,2]. The coalescence of genome annotation information, with external database links, and reaction, metabolite, and gene information from peer-reviewed models drives the quality of the knowledge base. This standardized approach to model validation ensures the quality of BiGG Models content and provides a benchmark for continued improvement Both the original 77 GEMs included in the 2016 release of BiGG and the 31 GEMs included in this update were evaluated with Memote (Figure 2). A new ‘universal’ model was added for download on the Data Access page; this model provides all reactions and metabolites from BiGG in a single COBRA-compatible JSON file, so users can rapidly add BiGG content to their own computational workflows using COBRA tools. Bugs and suggestions are collected on GitHub (https://github.com/ SBRG/bigg models), and this has led to continuous and transparent improvements to the site by the BiGG Models team
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