Abstract
Hyperbolicity is a global property of graphs that measures how close their structures are to trees in terms of their distances. It embeds multiple properties that facilitate solving several problems that found to be hard in the general graph form. In this paper, we investigate the hyperbolicity of graphs not only by considering Gromov’s notion of δ-hyperbolicity but also by analyzing its relationship to other graph’s parameters. This new perspective allows us to classify graphs with respect to their hyperbolicity, and to show that many biological networks are hyperbolic. Then we introduce the eccentricity-based bending property which we exploit to identify the core vertices of a graph by proposing two models: the Maximum-Peak model and the Minimum Cover Set model.
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Alrasheed, H., Dragan, F.F. (2015). Core-Periphery Models for Graphs Based on their δ-Hyperbolicity: An Example Using Biological Networks. In: Mangioni, G., Simini, F., Uzzo, S., Wang, D. (eds) Complex Networks VI. Studies in Computational Intelligence, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-16112-9_7
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DOI: https://doi.org/10.1007/978-3-319-16112-9_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16111-2
Online ISBN: 978-3-319-16112-9
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