开发一个集成和可推断的RDF数据库的糖,病原体和疾病资源的发展
Koichi Arakawa1, Tamiko Ono1, Kiyoko F Aoki-Kinoshita2,3
1Faculty of Science and Engineering, Soka University, 1-236 Tangi-machi, Hachioji City, Tokyo, 192-8577, Japan.
Scientific data
|September 6, 2023
概括
这项研究使用语义网络技术整合了多样化的甘氨酸和病毒数据. 一个新的本体学和RDF数据使得病毒-甘氨酸相互作用的统一发现成为可能,有助于传染病研究.
科学领域:
- 生物化学 生物化学
- 病毒学 病毒学
- 生物信息学是一种生物信息学.
- 数据科学数据科学数据科学
背景情况:
- 甘氨酸在病毒和病原体感染中起着关键作用,SARS-CoV-2的演变与糖化变化有关.
- 关于甘氨酸,病原体和疾病的现有数据资源是分散的,组织不良.
- 综合数据的需要对于理解病毒-甘氨酸相互作用及其对疾病的影响至关重要.
研究的目的:
- 建立一个发现甘氨酸-病毒相互作用数据的基础.
- 使用语义网络技术,从各种来源的异质数据进行语义整合.
- 为研究病毒-甘氨酸关系的研究人员创建一个统一的资源.
主要方法:
- 开发了一种新的本体学来定义病毒-甘氨酸相互作用的语义.
- 使用资源描述框架 (RDF) 来表示来自不同来源的数据.
- 来自PubChem,SugarBind和PSICQUIC等数据库的综合数据,连接到UniProt和GlyTouCan.Can等资源.
主要成果:
- 创建了一个关于病毒-糖甘相互作用的语义整合数据集.
- 将综合数据作为开放数据向公众提供.
- 开发了一个使用SPARQL查询进行免费数据探索的服务.
结论:
- 开发的本体学和RDF数据为病毒-甘氨酸相互作用发现提供了强大的框架.
- 格莱科斯莫斯门户为研究人员提供了一个有价值的,可访问的资源.
- 语义网络技术促进了复杂的生物数据的整合,以提高科学洞察力.
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