Martens Marvin, Evelo Chris T, Willighagen Egon L
Department of Bioinformatics-BiGCaT, NUTRIM, and Maastricht University, Maastricht, The Netherlands.
Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands.
Appl In Vitro Toxicol. 2022 Mar 1;8(1):2-13. doi: 10.1089/aivt.2021.0010. Epub 2022 Mar 17.
The AOP-Wiki is the main platform for the development and storage of adverse outcome pathways (AOPs). These AOPs describe mechanistic information about toxicodynamic processes and can be used to develop effective risk assessment strategies. However, it is challenging to automatically and systematically parse, filter, and use its contents. We explored solutions to better structure the AOP-Wiki content, and to link it with chemical and biological resources. Together, this allows more detailed exploration, which can be automated.
We converted the complete AOP-Wiki content into resource description framework (RDF) triples. We used >20 ontologies for the semantic annotation of property-object relations, including the Chemical Information Ontology, Dublin Core, and the AOP Ontology.
The resulting RDF contains >122,000 triples describing 158 unique properties of >15,000 unique subjects. Furthermore, >3500 link-outs were added to 12 chemical databases, and >7500 link-outs to 4 gene and protein databases. The AOP-Wiki RDF has been made available at https://aopwiki.rdf.bigcat-bioinformatics.org.
SPARQL queries can be used to answer biological and toxicological questions, such as listing measurement methods for all Key Events leading to an Adverse Outcome of interest. The full power that the use of this new resource provides becomes apparent when combining the content with external databases using federated queries.
Overall, the AOP-Wiki RDF allows new ways to explore the rapidly growing AOP knowledge and makes the integration of this database in automated workflows possible, making the AOP-Wiki more FAIR.
AOP-Wiki是不良结局途径(AOP)开发与存储的主要平台。这些AOP描述了有关毒理动力学过程的机制信息,可用于制定有效的风险评估策略。然而,自动且系统地解析、筛选和利用其内容具有挑战性。我们探索了更好地构建AOP-Wiki内容并将其与化学和生物资源相链接的解决方案。这样一来,就能够进行更详细的探索,且可实现自动化。
我们将完整的AOP-Wiki内容转换为资源描述框架(RDF)三元组。我们使用了20多种本体对属性-对象关系进行语义标注,包括化学信息本体、都柏林核心元数据元素集和AOP本体。
生成的RDF包含超过122,000个三元组,描述了超过15,000个独特主题的158个独特属性。此外,还添加了3500多个链接到12个化学数据库,以及7500多个链接到4个基因和蛋白质数据库。AOP-Wiki RDF已在https://aopwiki.rdf.bigcat-bioinformatics.org上提供。
SPARQL查询可用于回答生物学和毒理学问题,例如列出导致感兴趣的不良结局的所有关键事件的测量方法。当使用联合查询将此新资源的内容与外部数据库相结合时,使用这一新资源所带来的全部优势就变得显而易见。
总体而言,AOP-Wiki RDF为探索快速增长的AOP知识提供了新途径,并使将该数据库集成到自动化工作流程中成为可能,从而使AOP-Wiki更符合FAIR原则。