DEMETER：通过实验数据和精细的基因注释，高效地同时进行基因组规模重建的调控。
DEMETER: efficient simultaneous curation of genome-scale reconstructions guided by experimental data and refined gene annotations.
机构信息
School of Medicine, National University of Galway, H91 TK33 Galway, Ireland.
Ryan Institute, National University of Galway, H91 TK33 Galway, Ireland.
出版信息
Bioinformatics. 2021 Nov 5;37(21):3974-3975. doi: 10.1093/bioinformatics/btab622.
MOTIVATION
Manual curation of genome-scale reconstructions is laborious, yet existing automated curation tools do not typically take species-specific experimental and curated genomic data into account.
RESULTS
We developed Data-drivEn METabolic nEtwork Refinement (DEMETER), a Constraint-Based Reconstruction and Analysis (COBRA) Toolbox extension, which enables the efficient, simultaneous refinement of thousands of draft genome-scale reconstructions, while ensuring adherence to the quality standards in the field, agreement with available experimental data and refinement of pathways based on manually refined genome annotations.
AVAILABILITY AND IMPLEMENTATION
DEMETER and tutorials are freely available at https://github.com/opencobra.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
动机
基因组规模重建的手动注释非常繁琐，而现有的自动化注释工具通常没有考虑到特定物种的实验和已注释基因组数据。
结果
我们开发了 Data-drivEn METabolic nEtwork Refinement（DEMETER），这是 Constraint-Based Reconstruction and Analysis（COBRA）工具箱的扩展，它能够高效、同时对数千个草案基因组规模重建进行精细调整，同时确保符合该领域的质量标准、与现有实验数据一致，并根据手动精细注释的基因组注释来精细调整途径。
可用性和实现
DEMETER 和教程可在 https://github.com/opencobra 上免费获得。
补充信息
补充数据可在《Bioinformatics》在线获得。
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