LEADER 05351nam 2200685Ia 450 001 9910139802803321 005 20170810180159.0 010 $a1-282-68269-5 010 $a9786612682698 010 $a3-527-62798-7 010 $a3-527-62799-5 035 $a(CKB)1000000000790772 035 $a(EBL)481604 035 $a(OCoLC)441875100 035 $a(SSID)ssj0000334654 035 $a(PQKBManifestationID)11253603 035 $a(PQKBTitleCode)TC0000334654 035 $a(PQKBWorkID)10271062 035 $a(PQKB)11788433 035 $a(MiAaPQ)EBC481604 035 $a(CaSebORM)9783527323456 035 $a(EXLCZ)991000000000790772 100 $a20090129d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAnalysis of complex networks$b[electronic resource] $efrom biology to linguistics /$fedited by Matthias Dehmer and Frank Emmert-Streib 205 $a1st edition 210 $aWeinheim $cWiley-VCH$dc2009 215 $a1 online resource (482 p.) 300 $aDescription based upon print version of record. 311 $a3-527-32345-7 320 $aIncludes bibliographical references and index. 327 $aAnalysis of Complex Networks From Biology to Linguistics; Contents; Preface; List of Contributors; 1 Entropy, Orbits, and Spectra of Graphs; 1.1 Introduction; 1.2 Entropy or the Information Content of Graphs; 1.3 Groups and Graph Spectra; 1.4 Approximating Orbits; 1.4.1 The Degree of the Vertices; 1.4.2 The Point-Deleted Neighborhood Degree Vector; 1.4.3 Betweenness Centrality; 1.5 Alternative Bases for Structural Complexity; References; 2 Statistical Mechanics of Complex Networks; 2.1 Introduction; 2.1.1 Network Entropies; 2.1.2 Network Hamiltonians; 2.1.3 Network Ensembles 327 $a2.1.4 Some Definitions of Network Measures2.2 Macroscopics: Entropies for Networks; 2.2.1 A General Set of Network Models Maximizing Generalized Entropies; 2.2.1.1 A Unified Network Model; 2.2.1.2 Famous Limits of the Unified Model; 2.2.1.3 Unified Model: Additional Features; 2.3 Microscopics: Hamiltonians of Networks - Network Thermodynamics; 2.3.1 Topological Phase Transitions; 2.3.2 A Note on Entropy; 2.4 Ensembles of Random Networks - Superstatistics; 2.5 Conclusion; References; 3 A Simple Integrated Approach to Network Complexity and Node Centrality; 3.1 Introduction 327 $a3.2 The Small-World Connectivity Descriptors3.3 The Integrated Centrality Measure; References; 4 Spectral Theory of Networks: From Biomolecular to Ecological Systems; 4.1 Introduction; 4.2 Background on Graph Spectra; 4.3 Spectral Measures of Node Centrality; 4.3.1 Subgraph Centrality as a Partition Function; 4.3.2 Application; 4.4 Global Topological Organization of Complex Networks; 4.4.1 Spectral Scaling Method; 4.4.2 Universal Topological Classes of Networks; 4.4.3 Applications; 4.5 Communicability in Complex Networks; 4.5.1 Communicability and Network Communities 327 $a4.5.2 Detection of Communities: The Communicability Graph4.5.3 Application; 4.6 Network Bipartivity; 4.6.1 Detecting Bipartite Substructures in Complex Networks; 4.6.2 Application; 4.7 Conclusion; References; 5 On the Structure of Neutral Networks of RNA Pseudoknot Structures; 5.1 Motivation and Background; 5.1.1 Notation and Terminology; 5.2 Preliminaries; 5.3 Connectivity; 5.4 The Largest Component; 5.5 Distances in n-Cubes; 5.6 Conclusion; References; 6 Graph Edit Distance - Optimal and Suboptimal Algorithms with Applications; 6.1 Introduction; 6.2 Graph Edit Distance 327 $a6.3 Computation of GED6.3.1 Optimal Algorithms; 6.3.2 Suboptimal Algorithms; 6.3.2.1 Bipartite Graph Matching; 6.4 Applications; 6.4.1 Graph Data Sets; 6.4.2 GED-Based Nearest-Neighbor Classification; 6.4.3 Dissimilarity-Based Embedding Graph Kernels; 6.5 Experimental Evaluation; 6.5.1 Optimal vs. Suboptimal Graph Edit Distance; 6.5.2 Dissimilarity Embedding Graph Kernels Based on Suboptimal Graph Edit Distance; 6.6 Summary and Conclusions; References; 7 Graph Energy; 7.1 Introduction; 7.2 Bounds for the Energy of Graphs; 7.2.1 Some Upper Bounds; 7.2.2 Some Lower Bounds 327 $a7.3 Hyperenergetic, Hypoenergetic, and Equienergetic Graphs 330 $aMathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience. 606 $aMathematical analysis 606 $aInformation networks 606 $aGraph theory 608 $aElectronic books. 615 0$aMathematical analysis. 615 0$aInformation networks. 615 0$aGraph theory. 676 $a515 700 $aDehmer$b Matthias$0860612 701 $aDehmer$b Matthias$f1968-$0860612 701 $aEmmert-Streib$b Frank$0867728 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139802803321 996 $aAnalysis of complex networks$91936827 997 $aUNINA