Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
Institute for Systems Biology, Seattle, WA 98109, USA.
Nucleic Acids Res. 2020 Jan 8;48(D1):D402-D406. doi: 10.1093/nar/gkz1054.
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.
BiGG 模型知识库(http://bigg.ucsd.edu)是一个集中的基因组规模代谢模型知识库。在过去的 12 年中,该网站允许用户浏览和搜索代谢模型。在本次更新中,我们详细介绍了知识库中的新内容和新功能,继续致力于将每个模型与基因组注释和外部数据库连接起来,并实现反应和代谢物的标准化。我们描述了 31 个新模型的添加,这些模型扩展了 BiGG 模型所涵盖的系统发育树部分。我们还描述了用于托管多菌株模型的新功能,这些模型在各种以比较相关菌株为中心的研究中被证明具有洞察力。最后,使用新开发的基因组规模模型验证器 Memote 对知识库中的模型进行了基准测试,以展示 BiGG 模型中模型内容质量和透明度的提高。