Network Medicine

Summary

Diseases are rarely caused by isolated genes. They emerge from perturbations that spread through interconnected molecular, cellular and physiological systems. Network medicine provides a framework for representing those systems and testing how their structure relates to disease mechanisms, comorbidities, diagnosis and treatment.

Our work expands the molecular maps used by network medicine and develops quantitative approaches for finding disease modules, comparing conditions and generating clinically relevant predictions. We are particularly interested in interactions mediated by non-coding RNAs and in integrating molecular evidence with clinical and population-level data.

Research directions

• Disease modules and the human interactome
• Non-coding RNA interactions in disease prediction
• Biomarker and target discovery
• Disease-disease relationships and comorbidity
• Integration of molecular, clinical and population data

Selected publications

• Morselli Gysi D, Barabási AL. Non-coding RNAs improve the predictive power of network medicine. Proceedings of the National Academy of Sciences (2023). doi:10.1073/pnas.2301342120

• Gysi DM, do Valle I, Zitnik M, et al. Network medicine framework for identifying drug-repurposing opportunities for COVID-19. Proceedings of the National Academy of Sciences (2021). doi:10.1073/pnas.2025581118