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Recent advances in network medicine: From disease mechanisms to new treatment strategies

Conventional reductionist approaches have guided most of our understanding in disease diagnostic and treatment. However, most diseases are not consequence of perturbations in a single protein or metabolite, but rather of the effect that these perturbations have in their cellular context. The emergin...

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Published in:Multiple sclerosis 2020-04, Vol.26 (5), p.609-615
Main Author: Faria do Valle, Ítalo
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Language:English
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description Conventional reductionist approaches have guided most of our understanding in disease diagnostic and treatment. However, most diseases are not consequence of perturbations in a single protein or metabolite, but rather of the effect that these perturbations have in their cellular context. The emerging field of network medicine offers a set of tools to explore molecular networks and to retrieve insights about mechanisms of different diseases. The study of the protein interactome, the map of physical interactions among human proteins, revealed that disease proteins tend to interact with each other, linking diseases to well-defined interactome neighborhoods. These disease-associated neighborhoods have been defined as disease modules, and they can uncover the biological significance of genes identified by genetic studies, reveal molecular mechanisms that connect different phenotypes, and help identify new pharmacological strategies for disease treatment. Therefore, network medicine offers a framework in which the complexity of different aspects of multiple sclerosis can be explored in an integrative fashion, which can ultimately provide insights about disease mechanisms and treatment.
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subjects Disease
Humans
Medical treatment
Metabolites
Molecular modelling
Multiple sclerosis
Multiple Sclerosis - diagnosis
Multiple Sclerosis - drug therapy
Multiple Sclerosis - metabolism
Phenotypes
Precision Medicine
Protein Interaction Maps
title Recent advances in network medicine: From disease mechanisms to new treatment strategies
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