Huffman Anthony, Yeh Feng-Yu, Hur Junguk, Zheng Jie, Masci Anna Maria, Wu Guanming, Tao Cui, Athey Brian, He Yongqun
bioRxiv. 2025 Aug 28:2025.08.26.671804. doi: 10.1101/2025.08.26.671804.
With the increasing volume of biomedical experimental data, standardizing, sharing, and integrating heterogeneous experimental data across domains has become a major challenge. To address this challenge, we have developed an ontology-supported Study-Experiment-Assay (SEA) common data model (CDM), which includes 10 core and 3 auxiliary classes based on object-oriented modeling. SEA CDM uses interoperable ontologies for data standardization and knowledge inference. Building on the SEA CDM, we developed the Ontology-based SEA Network (OSEAN) relational database and knowledge graph, along with a set of ETL (Extract, Transform, Load) and query tools, and further applied them to represent 1,278 immune studies with over two million samples from three resources: VIGET, ImmPort, and CELLxGENE. Using simple, robust queries and analyses, our research identified multiple scientific insights into sex- specific immune responses, such as neutrophil degranulation and TNF binding to physiological receptors, following live attenuated and trivalent inactivated influenza vaccination. The novel SEA CDM system lays a foundation for establishing an integrative biodata ecosystem across biological and biomedical domains.
随着生物医学实验数据量的不断增加,跨领域对异构实验数据进行标准化、共享和整合已成为一项重大挑战。为应对这一挑战,我们开发了一种由本体支持的研究-实验-分析(SEA)通用数据模型(CDM),该模型基于面向对象建模,包括10个核心类和3个辅助类。SEA CDM使用可互操作的本体进行数据标准化和知识推理。在SEA CDM的基础上,我们开发了基于本体的SEA网络(OSEAN)关系数据库和知识图谱,以及一套ETL(提取、转换、加载)和查询工具,并进一步将它们应用于表示来自VIGET、ImmPort和CELLxGENE这三个资源的1278项免疫研究,这些研究包含超过两百万个样本。通过简单、可靠的查询和分析,我们的研究发现了关于性别特异性免疫反应的多个科学见解,例如在减毒活流感疫苗和三价灭活流感疫苗接种后,中性粒细胞脱颗粒以及肿瘤坏死因子与生理受体的结合情况。新颖的SEA CDM系统为跨生物和生物医学领域建立综合生物数据生态系统奠定了基础。