This book deals with the analysis of the structure of complex networks by combining results from graph theory, physics, and pattern recognition. The book is divided into two parts. 11 chapters are dedicated to the development of theoretical tools for the structural analysis of networks, and 7 chapters are illustrating, in a critical way, applications of these tools to real-world scenarios. The first chapters provide detailed coverage of adjacency and metric and
topological properties of networks, followed by chapters devoted to the analysis of individual fragments and fragment-based global invariants in complex networks. Chapters that analyse the concepts of communicability, centrality, bipartivity, expansibility and communities in networks follow. The second
part of this book is devoted to the analysis of genetic, protein residue, protein-protein interaction, intercellular, ecological and socio-economic networks, including important breakthroughs as well as examples of the misuse of structural concepts.
Ernesto Estrada obtained a PhD in Mathematical Chemistry from the Central University of Las Villas, Cuba in 1997 and completed post-doctoral studies at the University of Valencia, Spain and the Hebrew University of Jerusalem, Israel. In 2008 he was appointed Professor and Chair in Complexity Science at the Department of Mathematics and Statistics and the Department of Physics, University of Strathclyde, Glasgow, U.K. In 2005 he was elected fellow of the International Academy of Mathematical Chemistry (IAMC) and in 2007 he received the IAMC award as Outstanding Scientist for his multidisciplinary research in the field of complex networks. Estrada has published more than 140 scientific papers and has made seminal pioneering contributions in the areas of network matrix functions, communicability, bipartivity, subgraph centrality, generalised topological indices and the so-called Estrada index of a network.
1: Introduction 2: Adjacency Relationships in Networks 3: Metric and Topological Structure of Networks 4: Fragments (Subgraphs) in Complex Networks 5: Accounting for all parts (subgraphs) 6: Communicability Functions in Networks 7: Centrality Measures 8: Global Network Invariants 9: Expansion and Network Classes 10: Community Structure in Networks 11: Network Bipartivity 12: Random Models of Networks 13: Genetic Networks 14: Protein Residue Networks 15: Protein-protein Interaction Networks 16: The Structure of Reaction Networks 17: Intercellular Networks 18: Networks in Ecology 19: Socio-Economic Networks 20: Conclusions