Assoc. Prof. Yordan Yordanov presented “Mechanistic Exploration of Parkinson’s Disease by Integrating Co-expression Networks with AOPs” during the Data Science and Informatics session of the OpenTox Virtual Conference 2025.
The work explores how transcriptomic datasets from dopaminergic neuronal models can be analysed using Weighted Gene Co-expression Network Analysis (WGCNA) and subsequently connected with curated mechanistic knowledge from Adverse Outcome Pathways.
Rather than treating differential gene expression as an endpoint, the proposed workflow searches for coordinated gene modules and asks how these molecular patterns correspond to established Molecular Initiating Events, Key Events and adverse outcomes relevant to neurodegeneration.
The project represents an ongoing MU OmicsLab research direction at the interface of network biology, computational toxicology and mechanism-based interpretation of omics data.
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