The main goal in DyHealthNet is to make cohort data more explorable.
In the first phase of the project, prototype platforms were developed, primarily for application to the Collaborative Health Research in South Tyrol (CHRIS) cohort (13,000+ individuals), but always with generalizability in mind.
In the second phase, the goal is to establish GNExT and DyHealthNet as mature and scalable data analysis platforms that provide low-effort access to state-of-the-art network medicine and machine learning methods for GWAS and population cohort studies. We plan is to extend the existing features by providing polygenic risk scores, context-specific evaluation, differential analysis of association networks, and similarity search across participants, variants, and traits.
To encourage community adoption of the platforms, the lab will also offer hands-on training workshops.
The project is a collaboration of the FAU Erlangen-Nürnberg (Prof. David B. Blumenthal, BIONETS Lab), the Technische Universität München (Prof. Markus List, DaiSyBio), Institute for Biomedicine – Eurac Research (Dr. Christian Fuchsberger), and the Freie Universität Bozen (Prof. Gamper Johann).
Want to learn more about the project and the Bionets Lab?