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数据蒸厂:用于语义整合和查询生物医学数据的图形框架

Taha Mohseni Ahooyi, Benjamin Stear, J Alan Simmons

bioRxiv : the preprint server for biology

|August 20, 2025

概括

数据蒸厂知识图 (DDKG) 将各种生物医学数据统一用于翻译研究. 它可以在临床和实验数据集中进行高级查询,促进变种分析和生物标志物识别等领域的发现.

科学领域:

生物医学信息学
翻译生物信息学
数据科学

背景情况:

生物医学数据往往在不同领域分离,阻碍了综合分析.
翻译性研究需要将临床和实验数据联系起来以获得全面的见解.
现有的数据集成框架可能缺乏适用于各种生物医学本体学的灵活性.

研究的目的:

开发一个用于查询异质生物医学数据的语义整合框架.
通过连接临床和实验数据集来支持翻译研究.
为NIH共同基金数据生态系统创建一个统一的图形模型.

主要方法:

使用基于UBKG基础架构的属性图架构.
通过UMLS进行综合临床标准 (ICD-10,SNOMED,DrugBank).
使用本体学 (HPO,GENCODE,Ensembl,STRING,ClinVar) 的综合基因组学和基础科学数据.
实现基于本体的摄入,标识符规范化和图形原生查询.

主要成果:

在8个信息化用例中展示了数据蒸知识图 (DDKG) 的实用性.
成功链接各种数据集,包括临床记录和实验结果.
实现了复杂的调控变异分析,组织特异表达和生物标志物发现查询.
展示了新数据和图表的模块化和扩展性.

结论:

DDKG为语义整合和生物医学数据查询提供了强大的解决方案.
它显著增强了翻译研究和数据驱动发现的能力.
该框架可以通过公共接口,API和可下载版本进行访问.

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