Network analysis and modelling address a wide spectrum of techniques for studying domains consisting of individuals that are linked together into complex networks. Networks refer to artificial and natural systems like communication networks, social networks and biological networks. They constitute a very active area of research in a variety of scientific disciplines, including Physics, Biology, Artificial Intelligence and Mathematics.
Both graph theory and techniques recently developed for the analysis of networks provide a substantial background for studying complex network structures and dynamics in artificial and biological systems. They allow us to answer questions in common to these networks like aspects of adaptability, error and attack tolerance, complexity, community structures, and propagation patterns. One of the key features of natural networks is their ability to adapt to changing environments while maintaining an appropriate pattern of behaviour. Such adaptive capacity can be found in a whole range of natural networks, from gene-protein interaction networks within individual cells, through physiological systems, to ecosystems.
In order to engineer adaptive systems, it is necessary to develop a thorough understanding of the structural and dynamic network characteristics that underlie adaptability. Significant insight into the structure of biological networks has been gained through the application of high-throughput experimental techniques. Adaptive natural networks are being explored experimentally, but with a focus on the overall function of the network, and not on the mechanisms underlying adaptability per se. More recently, the study of artificial networks has gained increased attention in diverse areas of application such as social networks, the world wide web and citation networks. However, a number of areas of research (particularly those related to adaptability) remain relatively unstudied. For these areas, research on natural networks are likely to provide deeper insights, which could then promote research on more general theoretical models.
The aim of this symposium is to provide a forum to bring together scientists from biology, computer science and related disciplines who are concerned with theoretical and applied network analysis and modelling in the context of diverse disciplines, the adaptability in natural networks, and its application to artificial networks. Furthermore, our symposium will serve as a forum for interdisciplinary discussions to promote a comprehensive view of the state of the art in this field and to identify emerging and future research issues.
The topics of interest include, but are not limited to:Submissions in form of an extended abstract of at least 1500 word (2 pages) should be submitted until January 15th 2006 as PDF file by email to Susanne Hoche. Detailed information regarding the required format can be found here.
Please indicate in your submission if you prefer a poster presentation or a talk. For talks, we will offer additionally a possibility to put up a poster close to the lecture hall.
During the symposium working notes of the accepted contributions will be available.
Depending on the number and quality of the submissions we plan to edit special issues in major journals of related fields or a post-proceedings book. We will try to accommodate the different publishing interests of the involved research communities. Further details will be provided as soon as possible.
Submission of extended abstracts by: January 22nd 2006
Notification of decision: February 12th 2006
Camera ready copies by: March 3rd 2006