Network Science is the emerging field concerned with the study of
large, realistic networks. This interdisciplinary endeavor,
focusing on the patterns of interactions that arise between
individual components of natural and engineered systems, has been
applied to data sets from activities as diverse as high-throughput
biological experiments, online trading information, smart-meter
utility supplies, and pervasive telecommunications and surveillance
technologies. This unique text/reference provides a fascinating
insight into the state of the art in network science, highlighting
the commonality across very different areas of application and the
ways in which each area can be advanced by injecting ideas and
techniques from another. The book includes contributions from an
international selection of experts, providing viewpoints from a
broad range of disciplines. It emphasizes networks that arise in
nature-such as food webs, protein interactions, gene expression,
and neural connections-and in technology-such as finance, airline
transport, urban development and global trade. Topics and Features:
begins with a clear overview chapter to introduce this
interdisciplinary field; discusses the classic network science of
fixed connectivity structures, including empirical studies,
mathematical models and computational algorithms; examines
time-dependent processes that take place over networks, covering
topics such as synchronisation, and message passing algorithms;
investigates time-evolving networks, such as the World Wide Web and
shifts in topological properties (connectivity, spectrum,
percolation); explores applications of complex networks in the
physical and engineering sciences, looking ahead to new
developments in the field. Researchers and professionals from
disciplines as varied as computer science, mathematics,
engineering, physics, chemistry, biology, ecology, neuroscience,
epidemiology, and the social sciences will all benefit from this
topical and broad overview of current activities and grand
challenges in the unfolding field of network science.
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