“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, 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.
A well-balanced overview of mathematical approaches to complex systems
ranging from applications in chemistry and ecology to basic research questions on network complexity. Matthias Dehmer, Abbe Mowshowitz, and Frank Emmert-Streib, well-known pioneers in the field, have edited this volume with a view to balancing classical and modern approaches to ensure broad coverage of contemporary research problems.
The book is a valuable addition to the literature and a must-have for anyone dealing with network compleaity and complexity issues.
From the Back Cover
A well-balanced overview of mathematical approaches to complex systems
ranging from applications in chemistry and ecology to basic research questions on network complexity. Matthias Dehmer, Abbe Mowshowitz, and Frank Emmert-Streib, well-known pioneers in the field, have edited this volume with a view to balancing classical and modern approaches to ensure broad coverage of contemporary research problems.
The book is a valuable addition to the literature and a must-have for anyone dealing with network compleaity and complexity issues.
About the Author
Matthias Dehmer studied mathematics at the University of Siegen, Germany, and received his PhD in computer science from the Darmstadt University of Technology, 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, and is Head of the Institute for Bioinformatics and TranslationalResearch. His research interests are in bioinformatics, chemical graph theory, systems biology, complex networks, complexity, statistics and information theory. He has published extensively on network complexity and methods to analyze complex networks quantitatively.
Abbe Mowshowitz studied mathematics at the University of Chicago (BA 1961), and both mathematics and computer science at the University of Michigan (PhD 1967). He has held academic positions at the University of Toronto, The University of British Columbia, Erasmus University-Rotterdam, the University of Amsterdam and has been a professor of computer science at the City College of New York and in the PhD Program in Computer Science of the City University of New York since 1984. His research interests lie in applications of graph theory to the analysis of complex networks, and in the study of virtual organization.
Frank Emmert-Streib studied physics at the University of Siegen, Germany, gaining his PhD in theoretical physics from the University of Bremen. He was a postdoctoral research associate at the Stowers Institute for Medical Research, Kansas City, USA, and a senior fellow at the University of Washington, Seattle, USA. Currently, he is Lecturer/Assistant Professor at the Queen’s University Belfast, UK, at the Center for Cancer Research and Cell Biology, heading the Computational Biology and Machine Learning Lab. His research interests are in the field of computational biology, machine learning and network medicine.
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