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Latest revision as of 13:00, 18 March 2025

Network Medicine is an emerging field that uses network science to understand the human body at a systemic level. It is a multidisciplinary approach that integrates biology, medicine, physics, mathematics, computer science and statistics to create a comprehensive map of interactions within the human body.

Overview[edit]

Network Medicine aims to understand the complex interactions between genes, proteins, metabolites, cells, and organs that contribute to health and disease. It uses network theory to analyze these interactions, identifying patterns and relationships that can provide insights into disease mechanisms, potential treatments, and preventive measures.

Principles[edit]

The principles of Network Medicine are based on the concept of biological networks, which are complex systems of interactions between various biological entities. These networks can be visualized as graphs, with nodes representing the entities (such as genes or proteins) and edges representing the interactions between them.

Applications[edit]

Network Medicine has been applied in various areas of medical research, including genomics, proteomics, metabolomics, epidemiology, and pharmacology. It has been used to identify disease genes, predict drug targets, understand disease mechanisms, and develop personalized treatments.

Challenges[edit]

Despite its potential, Network Medicine faces several challenges. These include the complexity of biological networks, the lack of comprehensive and accurate data, and the need for advanced computational tools and methods.

See also[edit]

References[edit]

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