King Zachary A, Lu Justin, Dräger Andreas, Miller Philip, Federowicz Stephen, Lerman Joshua A, Ebrahim Ali, Palsson Bernhard O, Lewis Nathan E
Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany.
Nucleic Acids Res. 2016 Jan 4;44(D1):D515-22. doi: 10.1093/nar/gkv1049. Epub 2015 Oct 17.
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.
基因组尺度代谢模型是数学结构化的知识库,可用于预测代谢途径的使用情况和生长表型。此外,当与实验数据整合时,它们可以生成并检验假设。为了使这些模型的价值最大化,必须建立高质量模型的集中式存储库,模型必须遵循既定标准,并且模型组件必须与相关数据库相链接。模型可视化工具进一步提高了它们的实用性。为满足这些需求,我们推出了BiGG模型(http://bigg.ucsd.edu),这是一个经过全面重新设计的生化、遗传和基因组知识库。BiGG模型包含75个以上高质量、经过人工整理的基因组尺度代谢模型。在该网站上,用户可以浏览、搜索和可视化模型。BiGG模型将基因组尺度模型与基因组注释及外部数据库相连接。反应和代谢物标识符已在各模型间实现标准化,以符合社区标准并实现跨模型的快速比较。此外,BiGG模型提供了一个全面的应用程序编程接口,以便使用建模和分析工具访问BiGG模型。作为一个提供高度整理、标准化且易于访问的代谢模型的资源,BiGG模型将促进各种系统生物学研究,并支持对各种实验数据进行基于知识的分析。