AOPGraphExplorer 2.0: An Interactive Graph-Based Platform for Multi-Domain Mechanistic Annotation and Exploration of Adverse Outcome Pathways
Abstract
The Adverse Outcome Pathway (AOP) framework is a cornerstone of modern mechanistic toxicology, providing a structured representation of causal biological events linking molecular initiating events to adverse health outcomes. However, the practical exploration and interpretation of AOPs remain challenging due to the fragmentation of mechanistic knowledge across heterogeneous biological databases and the limited availability of integrated, interactive tools. Here, we present AOPGraphExplorer 2.0, an interactive graph-based platform for the visualization, annotation, and analysis of AOP networks derived from AOP-Wiki. This new version introduces a scalable, modular architecture that integrates multi-domain mechanistic annotations, including biological processes, molecular entities, anatomical context, diseases, and stressors, directly into AOP graphs. AOPGraphExplorer 2.0 enables dynamic filtering of AOP networks based on weight-of-evidence and quantitative understanding scores, supports AOP-, Key Event-, and keyword-centric queries, and generates exportable interactive HTML and machine-readable JSON representations for documentation, sharing, and computational reuse. In addition, the platform provides automated network statistics and annotation coverage summaries, supporting transparent and reproducible analysis. By bridging AOP-Wiki with external biomedical knowledge resources in a unified graph framework, AOPGraphExplorer 2.0 transforms AOP exploration into a multi-domain systems-level analysis workflow. The platform supports hypothesis generation, mechanistic interpretation, and evidence-based decision-making in toxicology, pharmacology, and risk assessment.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 0
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- AOP Net: An AI-Enhanced Software Platform for the Visualization and Analysis of Complex Toxicological Pathways
Abhik Seal·bioRxiv·Aug 25, 2025
- AOP-helpFinder 3.0: from text mining to network visualization of key event relationships, and knowledge integration from multi-sources.
Thomas Jaylet, Florence Jornod, … Karine Audouze·BioinformaticsPeer-reviewed·Jun 28, 2025
- AOPWIKI-EXPLORER: An Interactive Graph-based Query Engine leveraging Large Language Models
Saurav Kumar, Deepika Deepika, … Vikas Kumar·Computational ToxicologyPeer-reviewed·Mar 21, 2024
- Molecular annotation of AOPs guides the development of the next generation mechanistic chemical safety assessment and new approach methods
L. A. Saarimaki, J. Morikka, … D. Greco·bioRxiv·Jul 8, 2022
- Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations
J. Ravichandran, B. S. Karthikeyan, A. Samal·bioRxiv·Sep 14, 2021
- Ontology-Driven Annotation of Key Events Enables Transcriptomics-Based Assessment of Adverse Outcome Pathway Networks
Sidra Adil, Theo M. C. M. de Kok, … Marvin Martens·bioRxiv·Oct 13, 2026