Network Medicine




Network medicine is an interdisciplinary field that leverages network science to explore (and explain) the complex relationships characterizing biological systems. The core idea is to use the principles of network science to decipher the complex interplay of factors that contribute to life and diseases. Nodes can be genes, proteins, metabolites, or diseases, and edges represent interactions or correlations between these entities.

By mapping the interactions between different biological components, network medicine helps to quantify and understand how diseases can arise from disruptions in these networks. For example, a disease might be caused not by a single gene mutation but by the perturbation of an entire network of interacting genes and proteins.

To this aim, it largely overlaps with Systems Biology and Systems Medicine, which focus on understanding complex biological interactions at the system level, rather than in isolation, and on extending this approach to disease treatment and prevention.

We are especially interested in the integration of multiple, interdependent, layers of descriptions of biomolecular interactions, and how their response to external perturbations is related to the emergence of a disease. For instance, by using this framework, we have succesfully shown that COVID-19 is a systemic disease. Currently, we are exploring how to characterize the genetic basis of complex diseases, predict disease progression, and repurpose existing drugs.

By understanding the network dynamics of a patient's biological system, network medicine paves the way for personalized medicine, offering a paradigm shift from a reductionist viewpoint (focusing on individual components) to a holistic perspective, understanding health and disease through the complex interplay of distinct biological factors and their interactions.

We are an active part of the Padua Center for Network Medicine (Founding Director: Manlio De Domenico), recently established at the University of Padua and member of the Network Medicine Alliance.


Relevant publications

Multiscale statistical physics of the pan-viral interactome unravels the systemic nature of SARS-CoV-2 infections
A. Ghavasieh, S. Bontorin, O. Artime, N. Verstraete, M. De Domenico, Communications Physics 4, 83 (2021)
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CovMulNet19, Integrating Proteins, Diseases, Drugs, and Symptoms: A Network Medicine Approach to COVID-19
N. Verstraete, G. Jurman, G. Bertagnolli, A. Ghavasieh, V. Pancaldi, M. De Domenico, Network and Systems Medicine 3, 130 (2020)
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Assessment of network module identification across complex diseases
S. Choobdar et al, Nature Methods 16, 843 (2019)
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The multiplex network of human diseases
A. Halu*, M. De Domenico*, A. Arenas, A. Sharma, NPJ Systems Biology and Applications 5, 15 (2019)
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Multilayer network modeling of integrated biological systems
M. De Domenico, Physics of Life Reviews 24, 149-152 (2018)
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Multilayer flows in molecular networks identify biological modules in the human proteome
G. Mangioni, G. Jurman, M. De Domenico, IEEE Trans. on Network Science and Eng. 7, 411 (2018)
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Structural reducibility of multilayer networks
M. De Domenico, V. Nicosia, A. Arenas, V. Latora, Nature Communications 6, 6864 (2015)
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  ScienceDaily
   

MuxViz: a tool for multilayer analysis and visualization of networks
M. De Domenico, Mason A. Porter, A. Arenas, Journal of Complex Networks 3, 159 (2015)
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For a more comprehensive list of papers about this topic, click here.