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OverviewThis 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. Full Product DetailsAuthor: Ernesto Estrada (Chair in Complexity Science, Chair in Complexity Science, Department of Mathematics and Statistics, Department of Physics, University of Strathclyde, Glasgow)Publisher: Oxford University Press Imprint: Oxford University Press Dimensions: Width: 19.00cm , Height: 2.50cm , Length: 24.70cm Weight: 0.874kg ISBN: 9780198783800ISBN 10: 0198783809 Pages: 478 Publication Date: 09 June 2016 Audience: Professional and scholarly , Professional and scholarly , Professional & Vocational , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: To order Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us. Table of Contents1: 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: ConclusionsReviewsThe Structure of Complex Networks by E. Estrada is a great book, written by an expert in this new and exciting field. Starting from basic concepts, it describes the most recent advancements in the field in an open and enjoyable way. I recommend this book to both beginners and practitioners as a valuable tool for their research. * Guido Caldarelli, ISC-CNR Rome, Italy * The book is intended for researchers, graduate and advanced undergraduate students in interdisciplinary areas such as bioinformatics, chemistry, chemometrics, graph theory, mathematical chemistry, medical informatics, network biology and systems biology. [...] The book is nicely written and its thematical composition is unique. Its interesting interplay between theory and practical problems makes it a 'must read' for all scientists who work in network science and who want to use graph theory to solve new problems. * Matthias Dehmer, MATCH Communications in Mathematical and in Computer Chemistry * The emphasis on structural analysis is unique in comparison to other more popular positions in the field. In comparison to other books recently published on this topic, whether general or very specialized, this book focuses on understanding and elaborates on topics with examples, making it useful even for undergraduate students ... thus, although the book has an inclination to natural sciences (mainly physics and biology), it is aimed at a general audience. * Piotr Cholda, Computing Reviews * The emphasis on structural analysis is unique in comparison to other more popular positions in the field. In comparison to other books recently published on this topic, whether general or very specialized, this book focuses on understanding and elaborates on topics with examples, making it useful even for undergraduate students ... thus, although the book has an inclination to natural sciences (mainly physics and biology), it is aimed at a general audience. Piotr Cholda, Computing Reviews The book is intended for researchers, graduate and advanced undergraduate students in interdisciplinary areas such as bioinformatics, chemistry, chemometrics, graph theory, mathematical chemistry, medical informatics, network biology and systems biology. [...] The book is nicely written and its thematical composition is unique. Its interesting interplay between theory and practical problems makes it a 'must read' for all scientists who work in network science and who want to use graph theory to solve new problems. Matthias Dehmer, MATCH Communications in Mathematical and in Computer Chemistry The Structure of Complex Networks by E. Estrada is a great book, written by an expert in this new and exciting field. Starting from basic concepts, it describes the most recent advancements in the field in an open and enjoyable way. I recommend this book to both beginners and practitioners as a valuable tool for their research. Guido Caldarelli, ISC-CNR Rome, Italy Author InformationErnesto 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. 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