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提高生物医学知识图的质量:一个社区方法

Katherina G Cortes, Shilpa Sundar, Sarah Gehrke

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    此摘要是机器生成的。

    生物医学知识图 (KG) 需要更好的创建和共享标准. 目前的KG缺乏透明度,阻碍了生物医学研究中的重复使用和可比性.

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    科学领域:

    • 生物医学信息学
    • 数据科学
    • 知识表示

    背景情况:

    • 生物医学知识图 (KG) 是研究和翻译的关键工具.
    • 现有的KG通常缺乏一致的设计,文档和传播实践,与本体论不同.
    • 这种不透明性限制了它们的外部重复使用和可比性.

    研究的目的:

    • 制定和应用一套生物医学知识产权的评估标准.
    • 评估现有的生物医学知识产权的透明度和可重复使用性.
    • 确定标准化和改进的领域.

    主要方法:

    • 根据相关领域的数据标准和原则制定评估标准.
    • 将这些标准应用于16种生物医学基因组.
    • 分析了KG模型的变化,源集成和术语.

    主要成果:

    • 许多生物医学基因组,即使是那些似乎遵循最佳实践的基因组,也隐藏了重复使用的重要信息.
    • 在KG模型,数据集成和节点类型术语中存在显著的差异.
    • 缺乏透明度是一个常见的问题,阻碍了外部使用.

    结论:

    • 必须在整个社区采用共同的标准和标准 (例如,BioLink,KGX).
    • 提高透明度和标准化将提高KG的可重复使用性和可比性.
    • 对于最大限度地提高KG标准在生物医学研究中的用处至关重要.