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The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction comparison and analysis of metabolic models for plants fungi and microbes

机译:用于集成代谢注释的型号生物化学数据库以及植物真菌和微生物代谢模型的重建比较和分析

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摘要

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.
机译:超过10年,模型是基于带注释的微生物或植物基因组构建基因组级代谢模型的主要资源。现在被释放,生物化学数据库是模型和KBase的生化数据的基础。生物化学数据库体现了几个属性,其中包括:(i)包括分区化,运输反应,带电分子和质子对反应的综合性; (ii)用户社区可扩展,所有数据存储在GitHub中; (iii)设计为生物化学的“Rosetta Stone”,以方便与许多不同工具和数据库的注释的比较和集成。通过将化学数据与许多资源组合,应用标准转换,识别冗余和计算热力学性质来构建数据库。使用Flux平衡分析不断测试型号的生物化学,以确保生化网络正在建模,并能够模拟各种表型。可以设计在本体中以帮助进行比较和调整它们如何代表各种代谢途径的代谢重建。型号现在包括33,978个化合物和36,645个反应,可作为GitHub上的一组可扩展文件提供,可用于搜索https://modelseed.org/biochem和kbase。

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