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Complex networks: Structure and dynamics

TLDR
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.
Journal ArticleDOI

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

Crossover from scale-free to spatial networks

Marc Barthelemy
- 01 Sep 2003 - 
TL;DR: A simple model which combines both preferential attachment and distance selection characterized by a typical finite "interaction range" shows that if the total length is fixed, the optimal network which minimizes both thetotal length and the diameter lies in between the scale-free and spatial networks.
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Synchronization conditions and desynchronizing patterns in coupled limit-cycle and chaotic systems

TL;DR: In this paper, the authors show that for a given oscillator type and a given choice of oscillator variables to use in the coupling arrangement, the stability of each linear coupling scheme can be calculated from the stability for symmetric coupling schemes.
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Scale-free networks on lattices.

TL;DR: It is found that all networks with lambda>2 can be successfully embedded up to a (Euclidean) distance xi which can be made as large as desired upon the changing of an external parameter.
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Topological properties of high-voltage electrical transmission networks

TL;DR: In this paper, the topological properties of high-voltage electrical power transmission networks in several UE countries (the Italian 380 kV, the French 400 kV and the Spanish 400kV networks) have been studied from available data.
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Bounded confidence and social networks

TL;DR: The influence of possible social network topologies on the dynamics of the bounded confidence model, proposed by Deffuant et al, is discussed.
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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.