Providing Adverse Outcome Pathways from the AOP-Wiki in Semantic Web Format to Increase Usability and Accessibility of the Content

06 January 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


The AOP-Wiki is the main environment for the development and storage of Adverse Outcome Pathways. These Adverse Outcome Pathways 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. We used over twenty ontologies for the semantic annotation of property-object relations, including the ChemInformatics Ontology, Dublin Core, and the Adverse Outcome Pathway Ontology. The latter was used over 8,000 times. Furthermore, over 3,500 link-outs were added to twelve chemical databases and over 6,500 link-outs to four gene and protein databases.

SPARQL queries can be used against the Resource Description Framework 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. For example, we can link genes related to Key Events with molecular pathway on WikiPathways in which they occur and find all Adverse Outcome Pathways caused by stressors that are part of a particular chemical group. Overall, the AOP-Wiki Resource Description Framework allows new ways to explore the rapidly growing Adverse Outcome Pathway knowledge and makes the integration of this database in automated workflows possible.


Adverse Outcomes Pathways
Resource Description Framework
risk assessment
Linked Data


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