Estrada / Fox / Higham Network Science

Complexity in Nature and Technology
1. Auflage 2010
ISBN: 978-1-84996-396-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 245 Seiten

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.

Autoren/Hrsg.

Estrada, Ernesto

Fox, Maria

Oppo, Gian-Luca

Higham, Desmond J.

Inhaltsverzeichnis

1;Preface;5
2;Contents;7
3;Contributors;9
4;Complex Networks: An Invitation;12
4.1;Complex Networks: Introduction;13
4.2;Complex Networks: Origins;15
4.3;Complex Networks: Models and Algorithms;17
4.4;Complex Networks: Quantitative Features;18
4.5;Complex Networks: Chapters in this Book;19
4.6;References;19
5;Resistance Distance, Information Centrality, Node Vulnerability and Vibrations in Complex Networks;23
5.1;Introduction;23
5.2;Resistance Distance in Networks;24
5.3;Information Centrality;26
5.4;Vibrations in Complex Networks;26
5.5;Node Displacements and Resistance Distance;27
5.6;Node Displacement and Information Centrality;29
5.7;Node Displacement as a Measure of Node Vulnerability;29
5.8;Topological Displacements in Protein Residue Networks;32
5.9;Node Displacements for Temporal Change on Networks;34
5.10;Outlook;37
5.11;References;37
6;From Topology to Phenotype in Protein-Protein Interaction Networks;40
6.1;Data Sets;40
6.2;Network Comparisons;41
6.3;Network Models;44
6.4;Network Topology and Biological Function and Disease;46
6.5;Network Alignment;48
6.6;Data Integration;51
6.7;Outlook;51
6.8;References;53
7;Networks and Models with Heterogeneous Population Structure in Epidemiology;59
7.1;Simple Mathematical Models;60
7.1.1;Introducing R0;62
7.1.2;Density vs. Frequency Dependent Contact;62
7.2;Networks with Localisation of Contacts: Small Worlds, Clustering, Pairwise Approximations and Moment Closure;64
7.2.1;Small Worlds;64
7.2.2;Clustering on Networks and Moment Closure;65
7.3;Heterogeneity in Contacts per Individual;68
7.3.1;Models for Sexually Transmitted Diseases and HIV;68
7.3.2;Disease Transmission on Scale-Free Networks;70
7.3.3;Link Dynamics and STI Partnership Models;72
7.3.4;Integrating Networks and Epidemiology: Transmission Networks;75
7.3.5;The Basic Reproduction Number on Transmission Networks and Network Percolation Thresholds;76
7.4;Use of Social Networks with Real Epidemic Data;78
7.4.1;The Global Airline Network and SARS;79
7.4.2;Bovine Tuberculosis and the Network of Livestock Movements in GB;82
7.5;Integrating Networks and Epidemiology-Phylodynamics and the Identification of Transmission Networks;85
7.5.1;Models of HIV Infection;85
7.5.2;Foot-and-Mouth Disease in Great Britain;87
7.5.3;Conclusions;89
7.6;References;89
8;NESSIE: Network Example Source Supporting Innovative Experimentation;93
8.1;Motivation;93
8.2;Philosophy;95
8.3;The Networks;95
8.3.1;Network 1: European Economic Regions;96
8.3.2;Network 2: Guppy Social Interactions;96
8.3.3;Network 3: Reactor Core Modelling;99
8.3.4;Network 4: Classification of Whiskies;99
8.3.5;Network 5: Scottish Football Transfers;100
8.3.6;Network 6: Scottish Transport Networks;102
8.3.7;Network 7: Metabolite Network;103
8.3.8;Network 8: p53 Network;106
8.3.9;Network 9: Gene Network;106
8.3.10;Network 10: Protein-Protein Interaction Network;107
8.3.11;Network 11: Benguela Marine Ecosystem;107
8.3.12;Network 12: US Marine Ecosystem;110
8.4;Summary;110
8.5;References;113
9;Networks in Urban Design. Six Years of Research in Multiple Centrality Assessment;115
9.1;Introduction;115
9.2;Multiple Centrality Assessment;117
9.2.1;The One-Square-Mile Study: Establishing Centrality Analysis for Cities;118
9.2.2;Expanding the Scope: From Centrality to Network Analysis and from One-Square-Mile Samples to Entire Cities;122
9.2.3;Current Developments: Density of Centrality and Correlation;125
9.3;Conclusions and Further Research;131
9.3.1;Crossing the Borders: A Postscript from the First Author;131
9.4;References;136
10;The Structure of Financial Networks;138
10.1;Introduction;138
10.2;Similarity-Based Networks;140
10.2.1;Threshold Methods;141
10.2.2;Hierarchical Methods;142
10.2.3;An Application to NYSE;143
10.2.4;Other Similarity Based Hierarchical Networks in Finance;145
10.3;Control Networks: The Case of Directors and Ownerships;145
10.3.1;Stock Ownership Network;146
10.3.1.1;Distributions of s and h;149
10.3.2;Board of Directors;151
10.4;Transaction Networks: Interbank Networks and Bank-Firm Networks;152
10.4.1;Credit Networks;154
10.5;The World Trade Web;156
10.5.1;Gravity Models;157
10.5.2;The Heterogeneous Topology of Trade Neighbourhoods;158
10.5.3;The Fitness Network Model;159
10.5.4;The Maximum Likelihood Principle;163
10.5.5;The WTW as a Directed Network;164
10.6;References;167
11;A Hierarchy of Networks Spanning from Individual Organisms to Ecological Landscapes;171
11.1;Introduction;171
11.2;The Network Perspective;172
11.3;Network Data;173
11.3.1;Animal Social Network Data;173
11.3.2;Community Food Web Data;173
11.3.3;Landscape Graph Data;174
11.4;Understanding Complexity;174
11.5;Key Positions in Networks;175
11.6;Hierarchical Organisation of Networks;176
11.7;Dynamics;181
11.7.1;Descriptive Network Dynamics;181
11.7.2;Simulating Network Dynamics;181
11.8;Outlook;182
11.9;Closing Remarks;183
11.10;References;184
12;Revealing Structure of Complex Biological Systems Using Bayesian Networks;190
12.1;Introduction;190
12.2;Theory of Bayesian Networks;191
12.2.1;Definition;191
12.2.2;Interpretation;192
12.2.3;Dynamic Bayesian Networks;194
12.3;Structure Learning in Bayesian Networks;196
12.3.1;Overview;196
12.3.2;Bayesian Dirichlet Equivalent Score;197
12.4;Bayesian Networks in Biology;200
12.4.1;Complex Biological Systems;200
12.4.2;Molecular Biology;200
12.4.3;Neuroscience;202
12.4.4;Ecology;204
12.5;Conclusion;204
12.6;References;205
13;Dynamics and Statistics of Extreme Events;210
13.1;Introduction;210
13.2;Extreme Events in Networks;212
13.3;Return Times;212
13.4;Prediction of Extreme Events;213
13.5;Data Based Predictor of Extreme Events;216
13.6;Prediction of Extreme Avalanches in a Sandpile Model;218
13.7;Back to Networks;219
13.8;Conclusion;220
13.9;References;220
14;Dynamics of Networks of Leaky-Integrate-and-Fire Neurons;222
14.1;Introduction;222
14.2;Model Definition;224
14.3;Model Implementation;227
14.3.1;An Example;229
14.4;Quenched Disorder;231
14.5;Annealed Disorder;236
14.5.1;Cluster Width;237
14.5.2;Bistability and Inter-Cluster Fluxes;239
14.6;Summary and Perspectives;242
14.7;Appendix: Rescaling the Equations of Motion;243
14.7.1;Setup A;244
14.7.2;Setup B;244
14.8;References;245
15;Index;248