ArticleApplied network science2017
Robustness and efficiency in interconnected networks with changes in network assortativity.
Article in Applied network science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
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- Longitudinal network changes and phenoconversion risk in isolated REM sleep behavior disorder.Nature communications · 2024Article
- Brain network topology and its cognitive impact in adult glioma survivors.Scientific reports · 2024Article
- Longitudinal Network Changes and Phenoconversion Risk in Isolated REM Sleep Behavior Disorder.Research square · 2024Article
- Topological alterations in white matter anatomical networks in cervical dystonia.BMC neurology · 2024Article
- Adaptive and pathological connectivity responses in Parkinson's disease brain networks.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI.NeuroImage · 2022Article
- Topological Abnormalities of Pallido-Thalamo-Cortical Circuit in Functional Brain Network of Patients With Nonchemotherapy With Non-small Cell Lung Cancer.Frontiers in neurology · 2022Article
- Structural filtering of functional data offered discriminative features for autism spectrum disorder.PloS one · 2022Article
- Automated exploration of DNA-based structure self-assembly networks.Royal Society open science · 2021Article
- A Transcriptome Community-and-Module Approach of the Human Mesoconnectome.Entropy (Basel, Switzerland) · 2021Article
- Dopamine Transporter Is a Master Regulator of Dopaminergic Neural Network Connectivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks.Sensors (Basel, Switzerland) · 2018Article
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Authors and funding
5 authors.
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Abstract
In this study, the effect of assortativity on the robustness and efficiency of interconnected networks was investigated. This involved constructing a network that possessed the desired degree of assortativity. Additionally, an interconnected network was constructed wherein the assortativity between component networks possessed the desired value. With respect to single networks, the results indicated that a decrease in assortativity provided low hop length, high information diffusion efficiency, and distribution of communication load on edges. The study also revealed that excessive assortativity led to poor network performance. In the study, the assortativity between networks was defined and the following results were demonstrated: assortative connections between networks lowered the average hop length and enhanced information diffusion efficiency, whereas disassortative connections between networks distributed the communication loads of internetwork links and enhanced robustness. Furthermore, it is necessary to carefully adjust assortativity based on the node degree distribution of networks. Finally, the application of the results to the design of robust and efficient information networks was discussed.
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