Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Arsham Ghavasieh"'
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-10 (2021)
The dynamics of information within complex networks can be captured by a set of operators where the effect of detachment of a node defines the node-networks entanglement, which can be used as a multiscale centrality measure. Here, the authors show th
Externí odkaz:
https://doaj.org/article/6d1408f43f6042f495fc9f8a7075347a
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-13 (2021)
Characterizing the interactions between viral and human proteins is key to understand the function and structure of viruses such as SARS-CoV-2 and for informing drug design and repurposing strategies. Here, the authors use statistical physics techniq
Externí odkaz:
https://doaj.org/article/6c3ec879512740d28f17babc13acf0d4
Publikováno v:
Physical Review Research, Vol 5, Iss 1, p 013084 (2023)
Microscopic structural damage, such as lesions in neural systems or disruptions in urban transportation networks, can impair the dynamics crucial for systems' functionality, such as electrochemical signals or human flows, or any other type of informa
Externí odkaz:
https://doaj.org/article/85834a038bad4c149e0eba400187a0e1
Publikováno v:
Network Neuroscience, Vol 5, Iss 3, Pp 831-850 (2021)
AbstractInformation exchange in the human brain is crucial for vital tasks and to drive diseases. Neuroimaging techniques allow for the indirect measurement of information flows among brain areas and, consequently, for reconstructing connectomes anal
Externí odkaz:
https://doaj.org/article/d7ec413e071d4cebbfc5fdadfe856948
Autor:
Arsham Ghavasieh, Manlio De Domenico
Publikováno v:
Entropy, Vol 23, Iss 10, p 1369 (2021)
Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these propert
Externí odkaz:
https://doaj.org/article/9790e1c7cb244ca1bb9dc7bd5056e6cc
Autor:
Arsham Ghavasieh, Manlio De Domenico
Publikováno v:
Physical Review Research, Vol 2, Iss 1, p 013155 (2020)
Units of complex systems—such as neurons in the brain or individuals in societies—must communicate efficiently to function properly: e.g., allowing electrochemical signals to travel quickly among functionally connected neuronal areas in the human
Externí odkaz:
https://doaj.org/article/84a1f6a602bf4b94a816fbffd8289301
Autor:
Arsham Ghavasieh, Manlio De Domenico
The network density matrix formalism allows for describing the dynamics of information on top of complex structures and it has been successfully used to analyze from system's robustness to perturbations to coarse graining multilayer networks from cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::804ebb2c431fb0a62670863b338da5ee
http://arxiv.org/abs/2210.16701
http://arxiv.org/abs/2210.16701
Autor:
Oriol Artime, Barbara Benigni, Giulia Bertagnolli, Valeria d'Andrea, Riccardo Gallotti, Arsham Ghavasieh, Sebastian Raimondo, Manlio De Domenico
Networks are convenient mathematical models to represent the structure of complex systems, from cells to societies. In the last decade, multilayer network science – the branch of the field dealing with units interacting in multiple distinct ways, s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54e192b23c673b99a98a2176fd5604da
https://doi.org/10.1017/9781009085809
https://doi.org/10.1017/9781009085809
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-13 (2021)
Protein–protein interaction networks have been used to investigate the influence of SARS-CoV-2 viral proteins on the function of human cells, laying out a deeper understanding of COVID–19 and providing ground for applications, such as drug repurp
Publikováno v:
Network Neuroscience, Vol 5, Iss 3, Pp 831-850 (2021)
Network Neuroscience
Network Neuroscience
Information exchange in the human brain is crucial for vital tasks and to drive diseases. Neuroimaging techniques allow for the indirect measurement of information flows among brain areas and, consequently, for reconstructing connectomes analyzed thr