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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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A Comparative Analysis of Community Detection Algorithms on Artificial Networks

TL;DR: In this article, the Lancichinetti-Fortunato-Radicchi benchmark graph is used to compare the performance of community detection algorithms on real-world networks, and the authors provide guidelines to choose the most adequate community detection algorithm for a given network.
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Modelling interdependent infrastructures using interacting dynamical models

TL;DR: Averaging over many configurations of perturbed electrical network, results point to a sizeable amplification of the effects of faults on the electrical network on the communication network, also in the case of a moderate coupling between the two networks.
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The application of graph theoretical analysis to complex networks in the brain

TL;DR: It is demonstrated through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network.
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Emergence of network features from multiplexity

TL;DR: In this paper, the structural properties of an intrinsically multilayered real network, the European Air Transportation Multiplex Network in which each commercial airline defines a network layer, are analyzed. And the topology of each layer affects the emergence of structural properties in the aggregate network.
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Limits of modularity maximization in community detection

TL;DR: It is shown that multiresolution modularity is not capable to recover the planted community structure, not even when it is pronounced and easily detectable by other methods, for any value of the resolution parameter.
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Journal ArticleDOI

Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
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Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Book

Matrix computations

Gene H. Golub
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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.