Abstracts Division 1
16. Semantic modelling of Adverse Outcome Pathways and the implementation in reproducible workflows
Martens M.1, Evelo C.T.1,2 and Willighagen E.L.1
1 Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The
Netherlands
2 Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The
Netherlands
The purpose of Adverse Outcome Pathways is to organize mechanistic knowledge on
toxicological processes upon exposure to a stressor leading to an Adverse
Outcome through a series of Key Events (KEs). The implementation of this
concept for risk assessments is aimed to facilitate the replacement, reduction,
refinement (3Rs) of animal testing. Qualitative descriptions of AOPs are
generally stored in the public AOP-Wiki. However, its content remains
relatively isolated and is only manually queryable or through downloading the
full dataset, limiting the capabilities of this rich resource of toxicological
knowledge.
We tackled this AOP-Wiki limitation by FAIRifying into the AOP-Wiki Resource Description
Framework (RDF) as triples. We used over twenty ontologies for the semantic
annotation of property-object relations, and we introduced over 10,000 database
descriptors for chemicals, genes and proteins..
The AOP-Wiki RDF has been made available at aopwiki.rdf.bigcat-bioinformatics.org where SPARQL
queries can be used to extract information and answer biological and toxicological questions, manually or computationally.
As a demonstration, we developed a notebook that adds information to an AOP of
interest and finds and extracts supporting experimental data from ToxCast and
TG-GATES based on the molecular targets and stressor chemicals, and perform
transcriptomics pathway enrichment analysis with WikiPathways.
Overall, the AOP-Wiki RDF improves the accessibility and interoperability of the database,
providing additional ways of querying the data and enabling the implementation
in automated workflows. By focusing on increasing the machine-readability of
AOPs and using consistent vocabularies and ontologies, AOPs become an
increasingly useful tool for integrating toxicological knowledge and data,
thereby increasing the effectiveness of the concept and addressing the 3Rs in
toxicological studies.
This project has received funding from the European Union’s Horizon 2020 (EU 2020) research
and innovation program under grant agreement no. 681002 (EU-ToxRisk) and
EINFRA-22-2016 program under grant agreement no. 731075 (OpenRiskNet).
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