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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

Global Organization of Metabolic Fluxes in the Bacterium Escherichia coli

TL;DR: A flux balance analysis of the metabolism of Escherichia coli strain MG1655 shows that network use is highly uneven, which probably represents a universal feature of metabolic activity in all cells, with potential implications for metabolic engineering.
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Lower bounds for the partitioning of graphs

TL;DR: In this paper, it was shown that the right-hand side is a concave function of the diagonal matrix U such that the sum of the adjacency matrix of the graph plus all the elements of the sum matrix is zero.
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Compartments revealed in food-web structure

TL;DR: It is shown that a method for detecting compartments from the social networking science identified significant compartments in three of five complex, empirical food webs.
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Cascade control and defense in complex networks.

TL;DR: This work introduces and investigates a costless strategy of defense based on a selective further removal of nodes and edges, right after the initial attack or failure, that is shown to drastically reduce the size of the cascade.
Journal ArticleDOI

Bose-Einstein Condensation in Complex Networks

TL;DR: The evolution of many complex systems, including the World Wide Web, business, and citation networks, is encoded in the dynamic web describing the interactions between the system's constituents, and addressing the dynamical properties of these nonequilibrium systems within the framework of equilibrium quantum gases predicts the "first-mover-advantage," "fit-get-rich," and "winner-takes-all" phenomena.
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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.