![]() ![]() The first hypothesis of network medicine is that most known disease genes, which are non-essential, lie in the periphery of these networks and are far from hubs. Determining such links would help identify the molecular relationships between phenotypes and the reasons for certain comorbidities and would positively affect diagnosis, treatment, and drug multi-purposing.Ĭertain kinds of biological networks share the feature of having a few relatively highly connected nodes, often called “hubs," suggesting that the molecules represented by hubs should play special biological roles. The diseasome is, in fact, a network where diseases are nodes and links represent relationships between the disease-associated cellular components. The general aim is that of reverse-engineering the mechanisms of pathogenesis of complex disorders and traits, whereby the etiology is notoriously convoluted. ![]() ![]() Network medicine is a relatively new discipline that exploits graph theory to identify key molecules in the human diseasome, together with their hidden molecular relationships. These, together with several other kinds of networks, such as RNA, signaling, neuronal, trophic, and co-expression networks, are the concrete signs of an exceptional growth of molecular interaction data and, hence, of an intense research activity in the field of network medicine. Thus, a link exists between 2 molecules if there is evidence either of regulatory activity by a transcription factor onto a gene or of post-translational modifications. Protein interaction networks, for example, represent physical interactions as edges and proteins as nodes metabolic networks wire metabolites whenever these participate in the same biochemical reactions regulatory networks are directed graphs, where the directionality of relationships matters. The semantics of relationships is specific for each graph and completely defines its expressiveness. Interactive systems are commonly represented as graphs (or networks), which are mathematical representations of “elements" (nodes) and their relationships (edges). ![]()
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January 2023
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