Network Science

1. Front Matter

   Pages I-XI

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2. Complex Networks: An Invitation

   • Ernesto Estrada, Maria Fox, Desmond J. Higham, Gian-Luca Oppo

   Pages 1-11

3. Resistance Distance, Information Centrality, Node Vulnerability and Vibrations in Complex Networks

   • Ernesto Estrada, Naomichi Hatano

   Pages 13-29

4. From Topology to Phenotype in Protein–Protein Interaction Networks

   • Nataša Pržulj

   Pages 31-49

5. Networks and Models with Heterogeneous Population Structure in Epidemiology

   • R. R. Kao

   Pages 51-84

6. NESSIE: Network Example Source Supporting Innovative Experimentation

   • Alan Taylor, Desmond J. Higham

   Pages 85-106

7. Networks in Urban Design. Six Years of Research in Multiple Centrality Assessment

   • Sergio Porta, Vito Latora, Emanuele Strano

   Pages 107-129

8. The Structure of Financial Networks

   • Stefano Battiston, James B. Glattfelder, Diego Garlaschelli, Fabrizio Lillo, Guido Caldarelli

   Pages 131-163

9. A Hierarchy of Networks Spanning from Individual Organisms to Ecological Landscapes

   • Ferenc Jordán, Gabriella Baranyi, Federica Ciocchetta

   Pages 165-183

10. Revealing Structure of Complex Biological Systems Using Bayesian Networks

    • V. Anne Smith

    Pages 185-204

11. Dynamics and Statistics of Extreme Events

    • Holger Kantz

    Pages 205-216

12. Dynamics of Networks of Leaky-Integrate-and-Fire Neurons

    • Antonio Politi, Stefano Luccioli

    Pages 217-242

13. Back Matter

    Pages 243-245

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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.

• Natur
• Sage
• Synchronisation
• communication
• complex networks
• complexity
• information
• mathematics
• algorithm analysis and problem complexity

From the reviews:

“Unlike many existing books that address mathematical network science or that focus on a single application area, this book collects papers written by experts specializing in different fields. … the goal of this book is to broaden the view of readers. It focuses on applications of network science rather than on the mathematics of network analysis. It is suitable for readers with any background.” (Hsun-Hsien Chang, ACM Computing Reviews, March, 2011)

• , Dept. Mathematics, University of Strathclyde, Glasgow, United Kingdom

  Ernesto Estrada

• , Dept. Computer & Information Sciences, University of Strathclyde, Glasgow, United Kingdom

  Maria Fox

• Dept. Mathematics, University of Strathclyde, Glasgow, United Kingdom

  Desmond J. Higham

• , Dept. Physics & Applied Physics, University of Strathclyde, Glasgow, United Kingdom

  Gian-Luca Oppo

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