Automatic Network Fingerprinting through Single-Node Motifs

Author(s)

Echtermeyer, Christoph ^[1] ; Costa, Luciano da Fontoura ^[2] ; Rodrigues, Francisco A. ^[3] ; Kaiser, Marcus ^{[1, 4, 5]}

Affiliation

^[1] Newcastle Univ, Sch Comp Sci, Newcastle Upon Tyne NE1 7RU, Tyne & Wear - England

^[2] Univ Sao Paulo, Inst Fis Sao Carlos, Sao Carlos, SP - Brazil

^[3] Univ Sao Paulo, Dept Matemat Aplicada & Estat, Inst Ciencia & Tecnol Polimeros, Inst Ciencias Matemat & Computacao, Sao Carlos, SP - Brazil

^[4] Seoul Natl Univ, Dept Brain & Cognit Sci, Seoul - South Korea

^[5] Newcastle Univ, Sch Med, Inst Neurosci, Newcastle Upon Tyne NE1 7RU, Tyne & Wear - England

• Document type: Journal article
• Source: PLoS One; v. 6, n. 1, p. e15765, 2011.
• Web of Science Citations: 12

Abstract

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. (AU)

• FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
• Grantee: Roberto Marcondes Cesar Junior
• Support Opportunities: Research Projects - Thematic Grants