Network Science (eBook)

Preface 5
Contents 7
Contributors 9
Complex Networks: An Invitation 12
Complex Networks: Introduction 13
Complex Networks: Origins 15
Complex Networks: Models and Algorithms 17
Complex Networks: Quantitative Features 18
Complex Networks: Chapters in this Book 19
References 19
Resistance Distance, Information Centrality, Node Vulnerability and Vibrations in Complex Networks 23
Introduction 23
Resistance Distance in Networks 24
Information Centrality 26
Vibrations in Complex Networks 26
Node Displacements and Resistance Distance 27
Node Displacement and Information Centrality 29
Node Displacement as a Measure of Node Vulnerability 29
Topological Displacements in Protein Residue Networks 32
Node Displacements for Temporal Change on Networks 34
Outlook 37
References 37
From Topology to Phenotype in Protein-Protein Interaction Networks 40
Data Sets 40
Network Comparisons 41
Network Models 44
Network Topology and Biological Function and Disease 46
Network Alignment 48
Data Integration 51
Outlook 51
References 53
Networks and Models with Heterogeneous Population Structure in Epidemiology 59
Simple Mathematical Models 60
Introducing R0 62
Density vs. Frequency Dependent Contact 62
Networks with Localisation of Contacts: Small Worlds, Clustering, Pairwise Approximations and Moment Closure 64
Small Worlds 64
Clustering on Networks and Moment Closure 65
Heterogeneity in Contacts per Individual 68
Models for Sexually Transmitted Diseases and HIV 68
Disease Transmission on Scale-Free Networks 70
Link Dynamics and STI Partnership Models 72
Integrating Networks and Epidemiology: Transmission Networks 75
The Basic Reproduction Number on Transmission Networks and Network Percolation Thresholds 76
Use of Social Networks with Real Epidemic Data 78
The Global Airline Network and SARS 79
Bovine Tuberculosis and the Network of Livestock Movements in GB 82
Integrating Networks and Epidemiology-Phylodynamics and the Identification of Transmission Networks 85
Models of HIV Infection 85
Foot-and-Mouth Disease in Great Britain 87
Conclusions 89
References 89
NESSIE: Network Example Source Supporting Innovative Experimentation 93
Motivation 93
Philosophy 95
The Networks 95
Network 1: European Economic Regions 96
Network 2: Guppy Social Interactions 96
Network 3: Reactor Core Modelling 99
Network 4: Classification of Whiskies 99
Network 5: Scottish Football Transfers 100
Network 6: Scottish Transport Networks 102
Network 7: Metabolite Network 103
Network 8: p53 Network 106
Network 9: Gene Network 106
Network 10: Protein-Protein Interaction Network 107
Network 11: Benguela Marine Ecosystem 107
Network 12: US Marine Ecosystem 110
Summary 110
References 113
Networks in Urban Design. Six Years of Research in Multiple Centrality Assessment 115
Introduction 115
Multiple Centrality Assessment 117
The One-Square-Mile Study: Establishing Centrality Analysis for Cities 118
Expanding the Scope: From Centrality to Network Analysis and from One-Square-Mile Samples to Entire Cities 122
Current Developments: Density of Centrality and Correlation 125
Conclusions and Further Research 131
Crossing the Borders: A Postscript from the First Author 131
References 136
The Structure of Financial Networks 138
Introduction 138
Similarity-Based Networks 140
Threshold Methods 141
Hierarchical Methods 142
An Application to NYSE 143
Other Similarity Based Hierarchical Networks in Finance 145
Control Networks: The Case of Directors and Ownerships 145
Stock Ownership Network 146
Distributions of s and h 149
Board of Directors 151
Transaction Networks: Interbank Networks and Bank-Firm Networks 152
Credit Networks 154
The World Trade Web 156
Gravity Models 157
The Heterogeneous Topology of Trade Neighbourhoods 158
The Fitness Network Model 159
The Maximum Likelihood Principle 163
The WTW as a Directed Network 164
References 167
A Hierarchy of Networks Spanning from Individual Organisms to Ecological Landscapes 171
Introduction 171
The Network Perspective 172
Network Data 173
Animal Social Network Data 173
Community Food Web Data 173
Landscape Graph Data 174
Understanding Complexity 174
Key Positions in Networks 175
Hierarchical Organisation of Networks 176
Dynamics 181
Descriptive Network Dynamics 181
Simulating Network Dynamics 181
Outlook 182
Closing Remarks 183
References 184
Revealing Structure of Complex Biological Systems Using Bayesian Networks 190
Introduction 190
Theory of Bayesian Networks 191
Definition 191
Interpretation 192
Dynamic Bayesian Networks 194
Structure Learning in Bayesian Networks 196
Overview 196
Bayesian Dirichlet Equivalent Score 197
Bayesian Networks in Biology 200
Complex Biological Systems 200
Molecular Biology 200
Neuroscience 202
Ecology 204
Conclusion 204
References 205
Dynamics and Statistics of Extreme Events 210
Introduction 210
Extreme Events in Networks 212
Return Times 212
Prediction of Extreme Events 213
Data Based Predictor of Extreme Events 216
Prediction of Extreme Avalanches in a Sandpile Model 218
Back to Networks 219
Conclusion 220
References 220
Dynamics of Networks of Leaky-Integrate-and-Fire Neurons 222
Introduction 222
Model Definition 224
Model Implementation 227
An Example 229
Quenched Disorder 231
Annealed Disorder 236
Cluster Width 237
Bistability and Inter-Cluster Fluxes 239
Summary and Perspectives 242
Appendix: Rescaling the Equations of Motion 243
Setup A 244
Setup B 244
References 245
Index 248