Jones Andrew R, Miller Michael, Aebersold Ruedi, Apweiler Rolf, Ball Catherine A, Brazma Alvis, Degreef James, Hardy Nigel, Hermjakob Henning, Hubbard Simon J, Hussey Peter, Igra Mark, Jenkins Helen, Julian Randall K, Laursen Kent, Oliver Stephen G, Paton Norman W, Sansone Susanna-Assunta, Sarkans Ugis, Stoeckert Christian J, Taylor Chris F, Whetzel Patricia L, White Joseph A, Spellman Paul, Pizarro Angel
School of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Nat Biotechnol. 2007 Oct;25(10):1127-33. doi: 10.1038/nbt1347.
The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology.
功能基因组学实验数据模型（FuGE）的开发旨在促进生物学高通量综合分析数据标准的融合。FuGE对不同技术中常见的实验活动组件进行建模，包括实验方案、样本和数据。FuGE为描述整个实验室工作流程以及开发新的数据格式提供了基础。微阵列基因表达数据协会和蛋白质组学标准倡议组织已承诺将FuGE作为定义各自标准的基础，其他标准组织，包括代谢组学标准倡议组织，也在其开发工作中对FuGE进行评估。多个标准机构采用FuGE将能够统一报告功能基因组学工作流程的共同部分，简化数据整合工作，并减轻研究人员满足多个最低报告要求的负担。这些进展对于功能基因组学和系统生物学中的透明数据管理与挖掘非常重要。
