Overview

This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and homogenous style, this reference is equally suitable for courses on computational networks.

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9783527337248

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The authors present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and homogeneous style, this reference is equally suitable for courses on computational networks. (Zentralblatt MATH 2016)

In summary, Advances in Network Complexity is a valuable treatise, outlining the many facets of the contemporary approaches to network complexity. It will be useful for both experts and beginners. It should be a must for any decent science library. ( MATCH Communications in Mathematical and in Computer Chemistry, 1 March 2014) This volume will be particularly valuable to researchers in these areas as a resource to learn about earlier threads of network analysis coming from unfamiliar fields such as computer science and pure mathematics. ( Journal of Complex Networks, 1 March 2014) Theory and practical applications are intertwined to give the reader a deeper appreciation of the problems and possible solutions. Network complexity is a rapidly evolving field touching on a wide range of issues from pure mathematics, physics and chemistry to industrial processes and consumer behavior. This book satisfies a pressing need for a comprehensive overview of the current state of the field. ( AMS Journal, 1 October 2013) Overall, a valuable addition to the literature and a must-have for anyone dealing with complex systems. The articles of this volume will not be reviewed individually. ( Zentralblatt Math, 1 September 2013) In summary, \Advances in Network Complexity is a valuable treatise, outliningthe many facets of the contemporary approaches to network complexity. It will beuseful for both experts and beginners. It should be a must for any decent sciencelibrary.

Author Information

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). Afterwards, he was a research fellow at Vienna Bio Center (Austria), Vienna University of Technology, and University of Coimbra (Portugal). He obtained his habilitation in applied discrete mathematics from the Vienna University of Technology. Currently, he is Professor at UMIT - The Health and Life Sciences University (Austria) and also holds a position at the Universität der Bundeswehr München. His research interests are in applied mathematics, bioinformatics, systems biology, graph theory, complexity and information theory. He has written over 180 publications in his research areas. Frank Emmert-Streib studied physics at the University of Siegen (Germany) gaining his PhD in theoretical physics from the University of Bremen (Germany). He received postdoctoral training from the Stowers Institute for Medical Re- search (Kansas City, USA) and the University of Washington (Seattle, USA). Currently, he is an associate professor at the Queen's University Belfast (UK) at the Center for Cancer Research and Cell Biology heading the Computational Biology and Machine Learning Laboratory. His main research interests are in the field of computational medicine, network biology and statistical genomics.

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