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Nodes Having a Major Influence to Break Cooperation Define a Novel Centrality Measure: Game Centrality

Overview of attention for article published in PLOS ONE, June 2013
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Title
Nodes Having a Major Influence to Break Cooperation Define a Novel Centrality Measure: Game Centrality
Published in
PLOS ONE, June 2013
DOI 10.1371/journal.pone.0067159
Pubmed ID
Authors

Gabor I. Simko, Peter Csermely

Abstract

Cooperation played a significant role in the self-organization and evolution of living organisms. Both network topology and the initial position of cooperators heavily affect the cooperation of social dilemma games. We developed a novel simulation program package, called 'NetworGame', which is able to simulate any type of social dilemma games on any model, or real world networks with any assignment of initial cooperation or defection strategies to network nodes. The ability of initially defecting single nodes to break overall cooperation was called as 'game centrality'. The efficiency of this measure was verified on well-known social networks, and was extended to 'protein games', i.e. the simulation of cooperation between proteins, or their amino acids. Hubs and in particular, party hubs of yeast protein-protein interaction networks had a large influence to convert the cooperation of other nodes to defection. Simulations on methionyl-tRNA synthetase protein structure network indicated an increased influence of nodes belonging to intra-protein signaling pathways on breaking cooperation. The efficiency of single, initially defecting nodes to convert the cooperation of other nodes to defection in social dilemma games may be an important measure to predict the importance of nodes in the integration and regulation of complex systems. Game centrality may help to design more efficient interventions to cellular networks (in forms of drugs), to ecosystems and social networks.

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The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 2%
Netherlands 1 2%
Germany 1 2%
Unknown 48 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 29%
Researcher 7 14%
Student > Master 7 14%
Student > Bachelor 4 8%
Student > Doctoral Student 3 6%
Other 9 18%
Unknown 6 12%
Readers by discipline Count As %
Computer Science 9 18%
Agricultural and Biological Sciences 5 10%
Physics and Astronomy 4 8%
Medicine and Dentistry 4 8%
Biochemistry, Genetics and Molecular Biology 3 6%
Other 13 25%
Unknown 13 25%