We establish advanced bioinformatics workflows to integrate heterogeneous multi-omics datasets into robust systems biology models. By applying explainable artificial intelligence across these multi-scale layers, we decode the complex molecular architecture of human disease. Driven by active collaborative initiatives, our computational analyses currently focus on data from Inflammatory Bowel Disease, Parkinsons disease, and oncology (such as colorectal cancer). Utilizing these conditions as primary model paradigms to translate high-dimensional biomedical data into actionable precision medicine.
Press release:
AI-assisted project investigating the connection between inflammatory bowel disease and Parkinsons dieaseOur group has been awarded funding for the project AI-PREDICT – AI-Driven Multimodal Data Integration for Predicting IBD–PD Comorbidity Progression (Project No. 01ZU2502).
The project will develop deep learning and multimodal data integration approaches to identify molecular mechanisms linking inflammatory bowel disease (IBD) and Parkinsons disease (PD), enabling improved patient stratification and disease progression prediction.
Shared last authorship publication investigating TNF-α–driven inflammatory reprogramming in iPSC-derived enteric neuronal systems from Parkinsons disease patients. Link
New projects in AI-based multi-omics integration and inflammatory mechanisms in neurodegenerative disorders have started in 2025–2026.
Development of predictive models for disease progression and patient stratification.
Integration of single-cell, spatial, transcriptomic and clinical data.
Computational analysis of Parkinsons disease and gut–brain interactions.
Mechanistic understanding of inflammatory bowel disease and chronic inflammation.
Analysis of tumour microenvironments, stromal interactions and therapy response.
Reproducible bioinformatics workflows, FAIR data principles and research data management.