In the context of network theory, Complex networks can be de?ned as a collection of nodes connected by edges representing various complex int- actions among the nodes. Almost any large-scale system, be it natural or man-made, can be viewed as a complex network of interacting entities, which is dynamically evolving over time. Naturally occurring networks include - ological, ecological and social networks (e. g. , metabolic networks, gene r- ulatory networks, protein interaction networks, signaling networks, epidemic networks, food webs, scienti?c collaboration networks and acquaintance n- works), whereas man-made networks include communication networks and transportation infrastructures (e. g. , the Internet, the World Wide Web, pe- to-peer networks, power grids and airline networks). This edited volume is a sequel to the workshop Dynamics on and of C- plex Networks (http://www. cel. iitkgp. ernet. in/?eccs07/) held as a satellite event of the fourth European Conference on Complex Systems in Dresden, Germany from October 15, 2007. The primary aim of this workshop was to systematically explore the statistical dynamics on and of complex n- works that prevail across a large number of scienti?c disciplines. Dynamics on networks refers to the di?erent types of processes, for instance, prolife- tion and di?usion, that take place on networks. The functionality/e?ciency of these processes is strongly tied to the underlying topology as well as the dynamic behavior of the network.

A comprehensive and concise presentation of current research from experts in various disciplines compiled in one volume Provides a clear conception of how complex networks can be extremely useful in dealing with difficult problems in a variety of disciplines Covers complex networks found in naturegenetic pathways, ecological networks, linguistic systems, and social systemsas well as man-made systems such as the World Wide Web and peer-to-peer networks For a broad audience of graduate students, researchers and practitioners in computer science, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences Includes supplementary material: sn.pub/extras

Klappentext

This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. Almost any large-scale system, either naturally occurring or man-made, can be viewed as a complex network of interacting entities dynamically evolving over time. Therefore, the theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline.

The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Towards this goal, the work is thematically organized into three main sections: Part I studies the application of complex networks to biological problems; Part II focuses on social networks; and Part III is an overview of networks prevalent in the information sciences.

Specific topics and features include:

• Comprehensive and concise presentation of current research from experts in various disciplines compiled in one volume

• Relevant reviews of important work in the field (8 chapters) giving the reader an up-to-date picture of the state-of-the-art

• Independent research reports (8 chapters) providing clear conceptions of how complex networks can be extremely useful to deal with difficult problems in a variety of disciplines

• Coverage of complex networks found in naturegenetic pathways, ecological networks, linguistic systems, and social systemsas well as man-made systems such as the World Wide Web and peer-to-peer networks

• A glossary of essential terms related to complex networks for quick and easy reference

The contributed chapters in this volume are intended to promote cross-fertilizationin several research areas, and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in systems exhibiting an underlying complex network structure in disciplines such as computer science, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.

Inhalt
Biological Sciences.- From Network Structure to Dynamics and Back Again: Relating Dynamical Stability and Connection Topology in Biological Complex Systems.- Regulation of Apoptosis via the NF?B Pathway: Modeling and Analysis.- Network-Based Models in Molecular Biology.- Ecological Networks: Structure, Interaction Strength, and Stability.- Signaling and Feedback in Biological Networks.- Social Sciences.- Topographic Spreading Analysis of an Empirical Sex Workers' Network.- Spectral Characterization of Network Structures and Dynamics.- Dynamics of Social Complex Networks: Some Insights into Recent Research.- The Structure and Dynamics of Linguistic Networks.- Networks Generated from Natural Language Text.- Information Sciences.- Efficiency of Navigation in Indexed Networks.- Evolution of Apache Open Source Software.- Some New Applications of Network Growth Models.- The Big Friendly Giant: The Giant Component in Clustered Random Graphs.- Technological Networks.- Advances in the Theory of Complex Networks.