Classification of scale-free networks

By Kwang-Il Goh, E. Oh, Hawoong Jeong, Byungnam Kahng, Doochul Kim. Proceedings of the National Academy of Sciences of the United States of America, 2002

360 citations recorded by the source corpus.

While the emergence of a power-law degree distribution in complex networks is intriguing, the degree exponent is not universal. Here we show that the betweenness centrality displays a power-law distribution with an exponent η, which is robust, and use it to classify the scale-free networks. We have observed two universality classes with η ≈ 2.2(1) and 2.0, respectively. Real-world networks for the former are the protein-interaction networks, the metabolic networks for eukaryotes and bacteria, and the coauthorship network, and those for the latter one are the Internet, the World Wide Web, and the metabolic networks for Archaea. Distinct features of the mass-distance relation, generic topology of geodesics, and resilience under attack of the two classes are identified. Various model networks also belong to either of the two classes, while their degree exponents are tunable.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3447e235f5c291b65278033c8a8ce9453ce26fde

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Citations in the corpus

Evolving protein interaction networks through gene duplication. (2003, background): “cerevisiae share some unexpected features with other complex networks (Jeong et al., 2001a; Wagner, 2001; Goh et al., 2002).”
Characterization of complex networks: A survey of measurements (2005, background): “Assuming that the interactions follow the shortest paths between two vertices, it is possible to quantify the importance of a vertex or a edge in this sense by its betweenness centrality [45]:”
A decade and a half of protein intrinsic disorder: Biology still waits for physics (2013, background): “many connections, and ends, that have the only connection to just one neighbor.(170,171) Such scale-free”
Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain (2008, neutral): “Recent studies have also concluded scale-free properties for networks of exponents 2b y b3 (Goh et al., 2001, 2002; Grigorov, 2005) and realworld biological networks were classified with exponents around 2 (Goh et al., 2001).”
Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling (2005, background): “These networks have a few nodes with many connections, and ends, that are connected to the popular nodes via one or a small number of steps (Watts and Strogatz, 1998; Goh et al., 2002).”
Cache "less for more" in information-centric networks (extended version) (2012, methodology): “, used in the classification of network types [44,45]), our Betw caching scheme is dependent on the betweenness distribution.”
Content-rich biological network constructed by mining PubMed abstracts (2004, background): “hubs), which may be predicted by network connectivity [ 32 ], is likely to increase the power and efficiency of identifying potential experimental targets capable of modifying network function.”
High-Betweenness Proteins in the Yeast Protein Interaction Network (2005, background): “The betweenness distribution P(B) of the nodes in a scale-free network also follows a power law or has a scale-free distribution, P(B) ∼ B−ρ [14].”