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Complex networks: Structure and dynamics

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The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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This article is published in Physics Reports.The article was published on 2006-02-01 and is currently open access. It has received 9441 citations till now. The article focuses on the topics: Network dynamics & Complex network.

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Complex brain networks: graph theoretical analysis of structural and functional systems

TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
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Complex network measures of brain connectivity: uses and interpretations.

TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.
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Community detection in graphs

TL;DR: A thorough exposition of community structure, or clustering, is attempted, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists.
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Community detection in graphs

TL;DR: A thorough exposition of the main elements of the clustering problem can be found in this paper, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.
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Journal ArticleDOI

Self-organization and identification of Web communities

TL;DR: This work shows that the Web self-organizes and its link structure allows efficient identification of communities and is significant because no central authority or process governs the formation and structure of hyperlinks.
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Power-Law Distribution of the World Wide Web

TL;DR: An improved version of the Erdos-Renyi (ER) theory of random networks is proposed to account for the scaling properties of a number of systems, including the link structure of the World Wide Web.
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Evolutionary dynamics of biological games.

TL;DR: This paper focuses on frequency-dependent selection, and argues that game-theoretic arguments are more appropriate than optimization algorithms for studying frequency- dependent selection.

Nonequilibrium Phase Transitions in Lattice Models

TL;DR: In this paper, Driven lattice gases: simulations are used to model the contact process of a lattice gas with a reaction and a contact process with a particle reaction model.
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Epidemic outbreaks in complex heterogeneous networks

TL;DR: The large connectivity fluctuations usually found in these networks strengthen considerably the incidence of epidemic outbreaks and defines a new epidemiological framework characterized by a highly heterogeneous response of the system to the introduction of infected individuals with different connectivity.
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The authors review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.