Case Study
AOPLink – Identification and Linking of Data related to AOPWiki


The Adverse Outcome Pathway (AOP) concept has been introduced to support risk assessment (Ankley et al., 2010). An AOP comprises a number of events and the adverse outcome: a molecular initiation event (MIE) is followed by one or more key events (KEs), leading to the adverse outcome (AO). The AOPWiki is a collaborative to exchange AOPs.

The use of AOPs for regulatory purposes requires detailed validation and linking to existing knowledge (Knapen et al., 2015; Burgdorf et al., 2017). Part of the development of AOPs is the search for data that supports the occurrence and biological plausibility of KEs and their relationships (KERs). This data can be found in literature and increasingly in databases.

This case study focuses on establishing links between AOPs and data that supports a particular AOP. This will allow finding AOPs related to experimental data, and finding data related to a particular AOP.


For this case study we aim to develop:

  • FAIR version of AOPWiki and WikiPathways;
  • Identifier mappings for MIEs, KEs, and biological and chemical entities (genes, proteins, metabolites);
  • Establish links between MIEs and KEs to biological assays;
  • Establish links between assays and biological and chemical entities;
  • Establish interoperable databases (see below).

Risk assessment framework

AOPLink will allow finding relevant experimental data for given compounds and nanomaterials and KEs (Tier 0, step 3), identify biological processes affected by exposure to those chemicals supporting hypothesis generation (Tier 1, step 6), and using these sources of information to determine if an AOP can be applied to that chemical and if not what information is missing (Tier 3, step 9).

With respect to the other case studies, AOPLink can take as input from SysGroup on similar chemicals (same group) in case no direct search results are found. Furthermore, TGX may provide predicted data to complement experimental data, to support searching. Because AOPLink may result in hypothesis and list KERs, these results can be passed to ModelRX for further prediction and read across.

Use Cases Associated

This case study is associated with UC3 - Search and Retrieve Assay Data based on Ontological Terms.

Databases and tools

  • AOPWiki, AOP knowledgebase (AOPKB);
  • WikiPathways, Reactome: biological pathway database;
  • BridgeDb: identifier mapping;
  • diXa, BioStudies, ArrayExpress, etc: experimental data;
  • Effectopedia, PathVisio: pathway analysis;
  • PubMed, ContentMine: literature for key events and their molecular processes.

Service integration

Services provided by SysGroup:

  • Grouping service that takes a compound or nanomaterial.

Services provided by TGX:

  • API to access predicted data.

Other services:

  • Search capability for the aforementioned databases;
  • Identifier mapping service;
  • PathVisioRPC;
  • Text mining services to find relevant literature.

Currently available services:

Related resources

Workflow: Access TG-GATEs data for seleted compounds, select differentially expressed genes and identifier relevant pathways
Thomas Exner
13 Sep 2018
Example workflow based on OpenRiskNet tools - Pathway identification workflow related to DataCure and AOPlink case studies. This notebook downloads TG-Gates data of 4 compounds and selects genes overexpressed in all sample. The Affymetrix probe sets are then translated into Ensembl gene identifiers using the BridgeDB service and pathways associated with the genes are identified using the WikiPathways service.

Publisher: OpenRiskNet
Target audience: Risk assessors, Researchers, Data modellers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: DC