Microarray Data Standards and Supporting Applications

微阵列数据标准和支持应用程序

• 批准号: 7504323
• 负责人: CATHERINE A BALL
• 金额: $ 60万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-23 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7504323
• 关键词: Area; Award; Bioconductor; Biological; Boston; Communities; Complement; Computer software; Computers; Critiques; Data; Data Analyses; Databases; Development; Education and Outreach; Educational process of instructing; Educational workshop; Ensure; Fostering; Funding; Gene Expression; Hand; Imagery; Incentives; Investigation; Java; Knowledge; Language; Microarray Analysis; Molecular Profiling; Occupations; Ontology; Philadelphia; Positioning Attribute; Purpose; Research; Research Infrastructure; Research Personnel; Resources; Running; San Francisco; Societies; Software Tools; Standards of Weights and Measures; Techniques; Technology; Work; experience; high throughput technology; information gathering; interest; interoperability; next generation; research study; symposium; tool

DESCRIPTION (provided by applicant): Our previous funding round of this project was devoted to creating the underlying data standards and infrastructure to support sharing microarray data. The availability of the MGED (Microarray and Gene Expression Data Society; www.mged.org) standards and infrastructure and our accumulated experience using and evaluating them puts us in an excellent position to deliver tools and resources directly to the bench biologists who are generating high-throughput gene expression data: We now propose to shift our main efforts away from building computational infrastructure - the over-arching purpose of this new proposal is to facilitate scientific discovery by providing bench biologists with the tools they need to effectively share gene expression data and to take advantage of well-annotated gene expression data in their research. Our work to create and promote data sharing standards and resources will have greatest impact when those standards and resources are in common use by biomedical researchers. The need for and potential benefits of standards for microarray and other high-throughput technologies is clear, yet the positive impact of the standards thus far developed has not yet been fully realized. This is in large part because the standards and tools we have developed still require expert knowledge, yet the targeted users are bench biologists who are not experts in this domain, and should not be expected to become so. In this application, in addition to building the next generation of data exchange standards, we are proposing to use the infrastructure we have built in the previous round of funding as the basis for data exchange resources that are useful and usable by bench biologists. Therefore, our aims are to: 1. Develop tools to help researchers easily annotate microarray experiments. 2. Extend popular data analysis and visualization tools (BioConductor, MeV, GenePattern, Java TreeView) to use MAGE-TAB-encoded experimental annotations. 3. Generalize the MAGE-TAB data exchange standard to work with other high-throughput biomedical data, such as ultra-high-throughput sequencing. 4. Provide biologist-friendly ontology terms that can be used to annotate microarray data as well as serve as meaningful terms in computational analyses. 5. Participate in outreach, education and information gathering efforts to engage the community in the development of standards and to ensure widespread use and critiques.

描述（由申请人提供）：我们该项目的上一轮融资致力于创建底层数据标准和基础设施以支持共享微阵列数据。 MGED（微阵列和基因表达数据协会；www.mged.org）标准和基础设施的可用性以及我们使用和评估它们所积累的经验使我们处于有利地位，可以直接向正在产生高水平的实验室生物学家提供工具和资源。 -吞吐量基因表达数据：我们现在建议将我们的主要工作从构建计算基础设施上转移出来 - 这项新提案的首要目的是通过为实验室生物学家提供有效共享基因表达数据和所需的工具来促进科学发现利用他们的研究中注释良好的基因表达数据。当生物医学研究人员普遍使用这些标准和资源时，我们创建和推广数据共享标准和资源的工作将产生最大的影响。 微阵列和其他高通量技术标准的需求和潜在好处是显而易见的，但迄今为止制定的标准的积极影响尚未完全实现。这在很大程度上是因为我们开发的标准和工具仍然需要专业知识，但目标用户是实验室生物学家，他们不是该领域的专家，也不应该期望成为该领域的专家。在此应用中，除了构建下一代数据交换标准外，我们还建议使用我们在上一轮融资中构建的基础设施作为对实验室生物学家有用且可用的数据交换资源的基础。因此，我们的目标是： 1. 开发工具帮助研究人员轻松注释微阵列实验。 2. 扩展流行的数据分析和可视化工具（BioConductor、MeV、GenePattern、Java TreeView）以使用 MAGE-TAB 编码的实验注释。 3.推广MAGE-TAB数据交换标准，以与其他高通量生物医学数据一起使用，例如超高通量测序。 4. 提供生物学家友好的本体术语，可用于注释微阵列数据并在计算分析中充当有意义的术语。 5. 参与外展、教育和信息收集工作，让社区参与标准的制定并确保广泛使用和批评。