AOP-Wiki SPARQL Endpoint

This service is a Virtuoso SPARQL endpoint that is loaded with RDF of the Adverse Outcome Pathway (AOP)-Wiki database (https://aopwiki.org/), based on the quarterly XML dumps that are provided. The AOP-Wiki serves as the primary repository of qualitative information for AOPs and is a central component in the AOP development effort coordinated by the Organisation for Economic Co-operation and Development (OECD). The database contains AOP which are described in terms of key events (KEs). An AOP is initiated by a stressor (e.g. a chemical) that causes a Molecular Initiating Event, which is followed by KEs (measurable, essential steps) along a pathway towards an adverse outcome for an organism or population. KEs are connected through Key Event Relationships (KERs), which capture the evidence supporting the AOP in a structured way. The AOP-Wiki website provides access to the AOP information via a web interface to look up AOPs, KEs, KERs, and stressors.

For end-users
For developers
Type:
Database / data source
Categories:
Knowledge bases
Applicability domain:
Toxicology, Bioinformatics
Topic:
Information extraction, Risk assessment
Targeted industry:
Chemicals, Nanotechnology, Drugs, Cosmetics, Food, Other consumer products
Targeted users:
Risk assessors, Researchers, Software Developers, Data managers, Regulators
Relevant OpenRiskNet case study:
AOPLink - Identification and Linking of Data related to AOPWiki

Provided by:
Maastricht University
Login required:
No
Integration status:
Integration in progress

Resources & Training

Poster
Expanding Adverse Outcome Pathway knowledge by creating AOP-Wiki RDF with semantic annotations to facilitate risk assessment of chemicals.
Marvin Martens, Chris Evelo, Egon Willighagen
19 Feb 2019
Abstract:
1. Introduction With the ever-growing number of chemicals that require toxicological risk assessment, there is a need for faster, more efficient use of existing data to assemble effective assessment strategies [1]. Therefore, the concept of Adverse Outcome Pathways (AOPs) was introduced [2], a framework to organize existing mechanistic information about toxicological processes into a chain of smaller pieces of knowledge, called Key Events (KEs). These allow the structuring of toxicological knowledge and reduce the effort needed to capture all information before performing risk assessment [2, 3]. In order to facilitate a community effort in gathering toxicological knowledge, the AOP-Wiki was created by the European Commission JRC and the US EPA. To integrate this knowledge base more easily with other resources, we explored the use of semantic web technologies to link AOP-Wiki with other chemical and biological databases. 2. Approach The AOP-Wiki provides quarterly permanent downloads for the full database XML (https://aopwiki.org/downloads/). We parsed the AOP-Wiki knowledge with Python 3.5 and the ElementTree XML API and converted it into a semantic web RDF format, which allows for accurate description with ontological annotations, including the AOPO, CHEMINF, and Dublin Core. Chemical compounds are identified in the AOP-Wiki with CAS numbers and biological processes with a variety of ontologies, e.g. GO, Mammalian Phenotype Ontology, and Molecular Interactions ontology. These annotations are used to create Internationalized Resource Identifiers. To integrate and test the RDF, a variety of federated SPARQL queries were written and executed in Blazegraph (build version 2.1.4). 3. Results We created an AOP-Wiki RDF scheme and converted the XML into Turtle syntax. The RDF was tested with a variety of SPARQL queries to answer biological question relevant to risk assessment, such as: - What measurement / test-method information is available for a given AOP? - Which of the stressor chemicals on the AOP-Wiki can be linked molecular pathways on WikiPathways? 4. Discussion The RDF transformation of AOP-Wiki content can assist in the accessibility and expansion of toxicological knowledge by allowing semantic interoperability. The created RDF of the AOP-Wiki allows the querying and providing of additional information for stressor chemicals, genes, and proteins involved in KEs, the underlying molecular pathways, but also for the applicability of AOPs by cell types or species. This semantic approach allows novel ways to explore the rapidly growing AOP knowledge with every new publication related to toxicological studies. There is work in progress on a Virtuoso SPARQL endpoint Docker image to simplify the use of the data, and integrate the database in the OpenRiskNet e-infrastructure to provide AOP knowledge useful for automated risk assessment workflows. Funding 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).
Related services:
AOP-Wiki SPARQL Endpoint

Target audience: Risk assessors, Researchers, Data managers, Data owners, OpenRiskNet stakeholders, Regulators, Bioinformaticians, Software developers, Data providers
Open access: yes
Licence: Attribution 4.0 International (CC BY 4.0)
Organisations involved: UM
Poster