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A game theoretic neighbourhood-based relevance index

Cesari, Giulia; Algaba, Encarnación; Moretti, Stefano; Napumeceno, Juan A. (2017), A game theoretic neighbourhood-based relevance index, in Cherifi, Chantal; Cherifi, Hocine; Karsai, Márton; Musolesi, Mirco, Complex Networks & Their Applications VI, Proceedings of Complex Networks 2017, Springer International Publishing : Cham, p. 29-40. 10.1007/978-3-319-72150-7_3

Type
Communication / Conférence
Date
2017
Conference title
Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications)
Conference date
2017-11
Conference city
Lyon
Conference country
France
Book title
Complex Networks & Their Applications VI, Proceedings of Complex Networks 2017
Book author
Cherifi, Chantal; Cherifi, Hocine; Karsai, Márton; Musolesi, Mirco
Publisher
Springer International Publishing
Published in
Cham
ISBN
978-3-319-72149-1
Number of pages
1288
Pages
29-40
Publication identifier
10.1007/978-3-319-72150-7_3
Metadata
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Author(s)
Cesari, Giulia
Dipartimento di Matematica, "Francesco Brioschi"
Algaba, Encarnación
Departamento de Matemática Aplicada I [IMUS]
Moretti, Stefano cc
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Napumeceno, Juan A.
Department of Languages and Computer Systems [LSI-US]
Abstract (EN)
Centrality measures are used in network analysis to identify the relevant elements in a network. Recently, several centrality measures based on coalitional game theory have been successfully applied to different kinds of biological networks, such as brain networks, gene networks, and metabolic networks. We propose an approach, using coalitional games, to the problem of identifying relevant genes in a biological network. Our model generalizes the notion of degree centrality, whose correlation with the relevance of genes for different biological functions is supported by several practical evidences in the literature. The new relevance index we propose is characterized by a set of axioms defined on gene networks and a formula for its computation is provided. Furthermore, an application to the analysis of a large co-expression network is shortly presented.
Subjects / Keywords
Complex Networks; Network Analysis; Game theory

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