The physics of complex diseases

What is it about?

Traditional approaches for disease research are based on the principle that biological systems can be best understood through their components. However, such top-down or reductionist approaches ignore the fact that biological entities encompass “systems” in which interdependence and interconnections among entities shape disease formation and progression. We have developed a statistical mechanics model to combine all entities related to a disease into informative, dynamic, omnidirectional, and personalized networks (idopNetworks), in which nodes represent entities and edges describes the interaction and independence among entities. We implement Prof. Yau's GLMY homology theory to dissect the topological architecture of idopNetworks, which enables us to identify key metabolites and their reaction pathways shaping inflammatory bowel disease (IBD) and its two types, ulcerative colitis and Crohn's disease.

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Photo by JJ Ying on Unsplash

Photo by JJ Ying on Unsplash

Why is it important?

The model combines elements of different disciplines into a unified framework, creating a new form of statistical mechanics for complex systems. It can disentangle the mechanistic secrets of what cause diseases from a systems perspective. Results obtained by the model could potentially open up a new avenue for designing drugs to block key metabolic pathways towards diseases.

Perspectives