Autor: Matthias Dehmer
ISBN-13: 9783527323456
Veröffentl: 01.04.2009
Einband: Buch
Seiten: 462
Gewicht: 1031 g
Format: 250x177x30 mm
Sprache: Englisch

Analysis of Complex Networks

Quantitative and Network Biology
From Biology to Linguistics
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This title first gives an overview of graph theory followed by applications of this field in biomedical (e.g. systems biology) and computational science. Based on a novel, comprehensive conceptwith contributions by renowned experts in the field.

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)
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.
Editiert von: Matthias Dehmer, Frank Emmert-Streib
Matthias Dehmer studied mathematics at the University of Siegen (Germany) and received his PhD in computer science from the Technical University of Darmstadt (Germany). Afterwards, he was a research fellow at Vienna Bio Center (Austria), Vienna University of Technology and University of Coimbra (Portugal). Currently, he is Professor at UMIT - The Health and Life Sciences University (Austria). His research interests are in bioinformatics, cancer analysis, chemical graph theory, systems biology, complex networks, complexity, statistics and information theory. In particular, he is also working on machine learning-based methods to design new data analysis methods for solving problems in computational biology and medicinal chemistry.Frank Emmert-Streib studied physics at the University of Siegen (Germany) and received his Ph.D. in Theoretical Physics from the University of Bremen (Germany). He was a postdoctoral research associate at the Stowers Institute for Medical Research (Kansas City, USA) in the Department for Bioinformatics and a Senior Fellow at the University of Washington (Seattle, USA) in the Department of Biostatistics and the Department of Genome Sciences. Currently, he is Lecturer/Assistant Professor at the Queen's University Belfast at the Center for Cancer Research and Cell Biology (CCRCB) leading the Computational Biology and Machine Learning Lab. His research interests are in the field of computational biology, machine learning and biostatistics in the development and application of methods from statistics and machine learning for the analysis of high-throughput data from genomics and genetics experiments.

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Autor: Matthias Dehmer
ISBN-13:: 9783527323456
ISBN: 3527323457
Erscheinungsjahr: 01.04.2009
Verlag: Wiley VCH Verlag GmbH
Gewicht: 1031g
Seiten: 462
Sprache: Englisch
Sonstiges: Buch, 250x177x30 mm, 300 schwarz-weiße Abbildungen