Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Concept
Network medicine
Summary
Network medicine is the application of network science towards identifying, preventing, and treating diseases. This field focuses on using network topology and network dynamics towards identifying diseases and developing medical drugs. Biological networks, such as protein-protein interactions and metabolic pathways, are utilized by network medicine. Disease networks, which map relationships between diseases and biological factors, also play an important role in the field. Epidemiology is extensively studied using network science as well; social networks and transportation networks are used to model the spreading of disease across populations. Network medicine is a medically focused area of systems biology.
The term "network medicine" was coined and popularized in a scientific article by Albert-László Barabási called "Network Medicine – From Obesity to the "Diseasome", published in The New England Journal of Medicine, in 2007. Barabási states that biological systems, similarly to social and technological systems, contain many components that are connected in complicated relationships but are organized by simple principles. Using the recent development of network theory, the organizing principles can be comprehensively analyzed by representing systems as complex networks, which are collections of nodes linked together by a particular relationship. For networks pertaining to medicine, nodes represent biological factors (biomolecules, diseases, phenotypes, etc.) and links (edges) represent their relationships (physical interactions, shared metabolic pathway, shared gene, shared trait, etc.).
Three key networks for understanding human disease are the metabolic network, the disease network, and the social network. The network medicine is based on the idea that understanding complexity of gene regulation, metabolic reactions, and protein-protein interactions and that representing these as complex networks will shed light on the causes and mechanisms of diseases.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.