Epidemic spreading on evolving signed networks

Saeedian, Meghdad; Azimi-Tafreshi, N.; Jafari, G. R.; Kertész, János

doi:10.1103/physreve.95.022314

Cited by 53 publications

(38 citation statements)

References 27 publications

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“…Stability, in terms of Balance Theory corresponds to a lower energy level according to the proposed energy equation 56 – 59 . It implies less possibility of changing the configuration of the triangles and therefore, less change in gene regulation within the network.…”

Section: Network Construction From Real Data and The Results Of Balance Theory Analysis Of The Interaction Networkmentioning

confidence: 99%

Topological analysis of interaction patterns in cancer-specific gene regulatory network: persistent homology approach

Masoomy

Askari

Tajik

et al. 2021

Sci Rep

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In this study, we investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease. We aim to propose that the quest of understanding cancer takes us beyond pairwise interactions between genes to a higher-order construction. We characterize the most prominent network deviations in the gene interaction patterns between cancer and normal samples that contribute to the complexity of this disease. What we hope is that through understanding these interaction patterns we will notice a deeper structure in the cancer network. This study uncovers the significant deviations that topological features in cancerous cells show from the healthy one, where the last stage of filtration confirms the importance of one-dimensional holes (topological loops) in cancerous cells and two-dimensional holes (topological voids) in healthy cells. In the small threshold region, the drop in the number of connected components of the cancer network, along with the rise in the number of loops and voids, all occurring at some smaller weight values compared to the normal case, reveals the cancerous network tendency to certain pathways.

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Section: Network Construction From Real Data and The Results Of Balance Theory Analysis Of The Interaction Networkmentioning

confidence: 99%

Topological analysis of interaction patterns in cancer-specific gene regulatory network: persistent homology approach

Masoomy

Askari

Tajik

et al. 2021

Sci Rep

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show abstract

“…This theory exemplifies the principles that “ the friend (enemy) of my friend (enemy) is my friend ” and “ the friend (enemy) of my enemy (friend) is my enemy ”. Later, it was translated to the language of graphs 20 and has since been a scientific challenge in the study of social systems 2–4,9–12,17 . In particular Leskovec et al .…”

Section: Introductionmentioning

confidence: 99%

Absorbing phase transition in the coupled dynamics of node and link states in random networks

Saeedian

Miguel

Toral

2019

Sci Rep

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We present a stochastic dynamics model of coupled evolution for the binary states of nodes and links in a complex network. In the context of opinion formation node states represent two possible opinions and link states represent positive or negative relationships. Dynamics proceeds via node and link state update towards pairwise satisfactory relations in which nodes in the same state are connected by positive links or nodes in different states are connected by negative links. By a mean-field rate equations analysis and Monte Carlo simulations in random networks we find an absorbing phase transition from a dynamically active phase to an absorbing phase. The transition occurs for a critical value of the relative time scale for node and link state updates. In the absorbing phase the order parameter, measuring global order, approaches exponentially the final frozen configuration. Finite-size effects are such that in the absorbing phase the final configuration is reached in a characteristic time that scales logarithmically with system size, while in the active phase, finite-size fluctuations take the system to a frozen configuration in a characteristic time that grows exponentially with system size. There is also a class of finite-size topological transition associated with group splitting in the network of these final frozen configurations.

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“…Stability, in terms of Balance Theory corresponds to a lower energy level according to the proposed energy equation [57][58][59][60] . It implies less possibility of changing the configuration of the triangles and therefore, less change in gene regulation within the network.…”

Section: Network Construction From Real Data and The Results Of Balancmentioning

confidence: 99%

Topological Analysis of Interaction Patterns in Cancer-Specific Gene Regulatory Network: Persistent Homology Approach

Masoomy

Askari

Tajik

et al. 2021

Preprint

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In this study, we investigated cancer cellular networks in the context of gene interactions and their associated patterns in order to recognize the structural features underlying this disease. We aim to propose that the quest of understanding cancer takes us beyond pairwise interactions between genes to a higher-order construction. We characterize the most prominent network deviations in the gene interaction patterns between cancer and normal samples that contribute to the complexity of this disease. What we hope is that through understanding these interaction patterns we will notice a deeper structure in the cancer network. This study uncovers the significant deviations that topological features in cancerous cells show from the healthy one, where the last stage of filtration confirms the importance of 1-dimensional holes (topological loops) in cancerous cells and 2-dimensional holes (topological voids) in healthy cells. In the small threshold region, the drop in the number of connected components of the cancer network, along with the rise in the number of loops and voids, all occurring at some smaller weight values compared to the normal case, reveals the cancerous network tendency to certain pathways.

show abstract

Epidemic spreading on evolving signed networks

Cited by 53 publications

References 27 publications

Topological analysis of interaction patterns in cancer-specific gene regulatory network: persistent homology approach

Topological analysis of interaction patterns in cancer-specific gene regulatory network: persistent homology approach

Absorbing phase transition in the coupled dynamics of node and link states in random networks

Topological Analysis of Interaction Patterns in Cancer-Specific Gene Regulatory Network: Persistent Homology Approach

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