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Automatic Network Fingerprinting through Single-Node Motifs

Lookup NU author(s): Professor Marcus Kaiser



Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Publication metadata

Author(s): Echtermeyer C, Costa LD, Rodrigues FA, Kaiser M

Publication type: Article

Publication status: Published

Journal: PLoS ONE

Year: 2011

Volume: 6

Issue: 1

Print publication date: 01/01/2011

Date deposited: 05/05/2011

ISSN (electronic): 1932-6203

Publisher: Public Library of Science


DOI: 10.1371/journal.pone.0015765


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Funder referenceFunder name
05/00587-5Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)
301303/06-1Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)
EP/E002331/1Engineering and Physical Sciences Research Council (EPSRC)
EP/G03950X/1Engineering and Physical Sciences Research Council (EPSRC)
R32-10142Ministry of Education, Science and Technology