Analysis of Complex Networks
From Biology to Linguistics
1st Edition
Published on 22. April 2009
Book
Hardback
XVIII, 462 pages
978-3-527-32345-6 (ISBN)
Description
Mathematical 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.
More details
Series
Edition
1. Auflage
Language
English
Place of publication
Berlin
Germany
Publishing group
Wiley-VCH
Target group
Professional and scholarly
Illustrations
106
83 s/w Abbildungen, 8 farbige Abbildungen, 15 s/w Tabellen
Dimensions
Height: 24 cm
Width: 17 cm
Thickness: 2.8 cm
Weight
1028 gr
ISBN-13
978-3-527-32345-6 (9783527323456)
Schweitzer Classification
Other editions
Additional editions
E-Book
07/2009
1st Edition
Wiley-Blackwell
€165.99
Available for download
Persons
Matthias Dehmer studied mathematics at the University of Siegen (Germany) and received his Ph.D. in computer science from the Technical University of Darmstadt (Germany). Currently, he is with the Vienna University of Technology (Austria) in the department of Discrete Mathematics and Geometry. His research interests are Graph Theory, Information Theory, Computational Biology and Machine Learning.
Frank Emmert-Streib studied Physics at the University of Siegen (Germany) and received his Ph.D. in Theoretical Physics form the University of Bremen (Germany). He was postdoctoral research associate at the Stowers Institute for Medical Research (Kansas City, USA) in the Department for Bioinformatics and is currently senior research fellow at the University of Washington (Seattle, USA) in Biostatistics and Genome Sciences. His research interests are in the field of Computational Biology, Biostatistics, Machine Learning and Information Theory and Statistical Learning.
Frank Emmert-Streib studied Physics at the University of Siegen (Germany) and received his Ph.D. in Theoretical Physics form the University of Bremen (Germany). He was postdoctoral research associate at the Stowers Institute for Medical Research (Kansas City, USA) in the Department for Bioinformatics and is currently senior research fellow at the University of Washington (Seattle, USA) in Biostatistics and Genome Sciences. His research interests are in the field of Computational Biology, Biostatistics, Machine Learning and Information Theory and Statistical Learning.
Content
Entropy, Orbits, and Spectra of Graphs (Mowshowitz, Mitsou)
Statistical Mechanics of Complex Networks (Thurner)
A Simple Integrated Approach to Network Complexity and Node Centrality (Bonchev)
Graph Spectra and the Structure of Complex Networks (Estrada)
Random Induced Subgraphs of n-Cubes (Reidys)
Graph Edit Distance - Optimal and Suboptimal Algorithms with Applications (Bunke, Riesen)
Graph Energy (Gutman, Li, Zhang)
Generalized Shortest Path Trees: A Novel Graph Class by Example of Semiotic Networks (Mehler)
Applications of Graph Theory in Chemo- and Bioinformatics (Dimitropoulos, Golovin, John, Krissinel) Structural and Functional Dynamics in Cortical and Neuronal Networks (Kaiser, Simonotto)
Network Mapping of Metabolic Pathways (Cheng, Zelikovsky)
Graph Structure Analysis and Computational Tractability of Scheduling Problems (Sevastyanov, Kononov)
Counting Cubes in Median Graphs and Related Problems (Kovse)
Elementary Elliptic (R, q)-Polycycles (Deza, Sikiric, Shtogrin)
Optimal Dynamic Flows in Networks and Algorithms for Finding Them (Lozovanu, Fonoberova)
Analyzing and Modeling European R&D Collaborations: Challenges and Opportunities from a Large Social Network (Barber, Paier, Scherngell)
Analytic Combinatorics on Random Graphs (Drmota, Gittenberger)
Statistical Mechanics of Complex Networks (Thurner)
A Simple Integrated Approach to Network Complexity and Node Centrality (Bonchev)
Graph Spectra and the Structure of Complex Networks (Estrada)
Random Induced Subgraphs of n-Cubes (Reidys)
Graph Edit Distance - Optimal and Suboptimal Algorithms with Applications (Bunke, Riesen)
Graph Energy (Gutman, Li, Zhang)
Generalized Shortest Path Trees: A Novel Graph Class by Example of Semiotic Networks (Mehler)
Applications of Graph Theory in Chemo- and Bioinformatics (Dimitropoulos, Golovin, John, Krissinel) Structural and Functional Dynamics in Cortical and Neuronal Networks (Kaiser, Simonotto)
Network Mapping of Metabolic Pathways (Cheng, Zelikovsky)
Graph Structure Analysis and Computational Tractability of Scheduling Problems (Sevastyanov, Kononov)
Counting Cubes in Median Graphs and Related Problems (Kovse)
Elementary Elliptic (R, q)-Polycycles (Deza, Sikiric, Shtogrin)
Optimal Dynamic Flows in Networks and Algorithms for Finding Them (Lozovanu, Fonoberova)
Analyzing and Modeling European R&D Collaborations: Challenges and Opportunities from a Large Social Network (Barber, Paier, Scherngell)
Analytic Combinatorics on Random Graphs (Drmota, Gittenberger)