Studying how biological and symptom networks can improve our understanding of mental health and cognition.

Methods for turning transcriptomic and multi-omic data into reproducible, interpretable biological networks.

Combining network medicine, machine learning and experimental evidence to identify therapeutic opportunities.

Connecting molecular interactions, disease mechanisms and clinical phenotypes to improve biomedical prediction.

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics.