Mapping Personalized Disease Signatures with Dynamic Network Biomarkers
This project pioneers the development of Individual-Specific Networks (ISNs)—AI- powered biological maps that reflect how each person’s molecular profile evolves over time. By integrating multi-omics data (like genomics and proteomics) with clinical records and lifestyle information, the PhD researcher will design tools that detect dynamic network biomarkers: early-warning signals of disease onset or progression unique to each individual.
The work will push beyond current limitations by introducing time-aware ISNs, capturing how molecular systems shift across different health states. Novel methods will be developed to identify critical subnetworks—personalized “hot spots” of disease activity—using graph-based learning and community detection algorithms.
These models will support data-driven, individualized interventions, helping clinicians move from reactive treatment to proactive care in complex diseases like obesity or cancer.
Supervisors: Dr. Kristel Van Steen (ULG), Dr. Marieke Pierik (UM)
