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RCN: Phenotype Ontology Research Coordination Network

RCN: Phenotype Ontology Research Coordination Network
RCN:表型本体研究协调网络
批准号:
0956049
负责人:
Wasila Dahdul
金额:
$49.87万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-10-01 至 2016-09-30

项目摘要

项目成果

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中文摘要
翻译
了解生物体的外观、行为和功能,即其“表型”,是解释潜在基因和环境影响相互作用的核心。然而,以一种可以与数千个分子遗传和环境数据库相联系的方式表示表型仍然很困难。该项目的目标是建立一个植物和动物表型以及来自社区的计算机表示方法(本体)的专家网络,这些社区正在独立开发表示和共享表型数据的方法。通过这个研究协调网络,科学家们将被聚集在一起,他们的活动将被协调到:(1)为准确的表型表示制定标准和最佳实践;(2)建立植物、脊椎动物和节肢动物的关键参考本体;以及(3)交叉引用这些本体,以便可以轻松地共享和访问关键数据。协调科学工作,以便从一开始就将有效的联系纳入数据库,是发展数据网络的一种有效和经济的机制。植物和动物显示出跨基因、表型和环境的复杂整合,这些数据的网络将使快速的科学发现和进步成为可能。该项目还将接触到能够使用这些数据的科学家,帮助他们链接到这些数据,并教育他们的社区关于这些计算方法及其实用性。
英文摘要
Knowledge of how an organism looks, behaves and functions, i.e., its "phenotype", is central to interpreting the interaction of underlying genes and environmental effects. Representing phenotype in a way that can be linked to thousands of molecular genetic and environmental databases, however, remains difficult. The goal of this project is to establish a network of experts on plant and animal phenotypes and on computer representation methods (ontologies) from communities that are independently developing ways to represent and share phenotypic data. Through this Research Coordination Network, scientists will be brought together and their activities coordinated to: (1) develop standards and best practices for accurate phenotype representations; (2) build key reference ontologies for plants, vertebrates, and arthropods; and (3) cross reference these ontologies so that key data can be easily shared and accessed. Coordinating scientific efforts so that effective linkages are built into databases from the outset is an efficient and economical mechanism to develop a data network. Plants and animals show complex integration across genes, phenotype and environment, and a network of these data will enable rapid scientific discovery and progress. This project also will reach out to scientists who can use the data, help them link to it, and educate their communities about these computational methods and their utility.
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会议论文
Collaborative Research: ABI Innovation: Enabling machine-actionable semantics for comparative analyses of trait evolution
  • 批准号:
    2048296
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.35万
  • 财政年份:
    2020
  • 负责人:
    Wasila Dahdul
  • 依托单位:
Collaborative Research: ABI Innovation: Enabling machine-actionable semantics for comparative analyses of trait evolution
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