ArticlePloS one2016
Analysis of the Effect of Degree Correlation on the Size of Minimum Dominating Sets in Complex Networks.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Parkinson's disease: Individual placebo responses are predicted by baseline expression of a striato-limbic network.Research square · 2026Article
- Constraint-based models for dominating protein interaction networks.IET systems biology · 2021Article
- Finding and analysing the minimum set of driver nodes required to control multilayer networks.Scientific reports · 2019Article
- Article
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Authors and funding
2 authors.
Funding
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Abstract
Network controllability is an important topic in wide-ranging research fields. However, the relationship between controllability and network structure is poorly understood, although degree heterogeneity is known to determine the controllability. We focus on the size of a minimum dominating set (MDS), a measure of network controllability, and investigate the effect of degree-degree correlation, which is universally observed in real-world networks, on the size of an MDS. We show that disassortativity or negative degree-degree correlation reduces the size of an MDS using analytical treatments and numerical simulation, whereas positive correlations hardly affect the size of an MDS. This result suggests that disassortativity enhances network controllability. Furthermore, apart from the controllability issue, the developed techniques provide new ways of analyzing complex networks with degree-degree correlations.
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