Freie Universität Berlin, Germany
Institute for Mathematics,
Arnimallee 6, 14195 Berlin
Topic & Preliminary Program
Modeling real-world systems as complex networks and analyzing both their topology and dynamics has been shown to be a fruitful approach to attaining a deeper understanding of such systems. Over the years, the research area of complex networks has gained more and more interest and became significant in fields as diverse as the life- and social sciences, physics and engineering. A large number of mathematical and computational methods allows to analyze the topology of and, if modeled, the dynamics generated by a given network. A closer look, however, quickly shows that an understanding of a static network is not sufficient to meet the challenges encountered in many areas of the applied sciences. Molecular networks, traffic networks, social networks, the Internet – they all undergo changes in their topology over time which in turn influences their functionality. Considering only a few snapshots of these dynamic processes is not enough to comprehend the underlying rules governing the network evolution. Only insights into the mechanisms of change and the evolution of properties will allow us to generate well-supported predictions concerning the network behavior and to develop strategies for efficient network control.
The workshop will encompass three days, each devoted to a particular topic on investigating evolving systems: (1) reverse-engineering, (2) analysis and (3) control of time-evolving networks.
On the first day, we will motivate the interest in time-evolving systems by highlighting their occurrence and importance in the context of molecular evolution, e.g., for the development of cancer types. A natural follow-up is then the question of how to derive models for such networks to make the system accessible for mathematical methods. We address this question by introducing different reverse-engineering approaches, closely related to the presented applications in epidemiology and evolution.
The second day will then focus on the analysis of time-evolving networks by introducing the key theoretical concepts of time-evolving networks such as the statistical properties and measures of temporaltopological structures. Additionally, the topic of dynamical processes on time-evolving networks will be discussed as one of the main tools for understanding the structural changes of the underlying network. This will set the theoretical foundation for describing biological processes on evolving networks, like disease spreading and virus evolution.
Having provided the necessary terminology, inference methods and analysis approaches, this last session will take us one step further, addressing the question of how to influence time-evolving networks to elicit favorable properties. Control strategies for such networks are of major interest in the applications presented in this workshop, e.g., for managing epidemics or for mitigating drug resistance development. Within this session the demands on the mathematical tools stemming from application will be highlighted
and, complementing this, formal approaches to the problem will be presented.
The workshop will be held at the Freie Universität Berlin, Germany. An overview of the session and the invited speakers is given in the following list:
• Day 1: Session "Time-evolving Networks – Significance and Inference"
Invited speakers: Niko Beerenwinkel (ETH Zürich), Dirk Brockmann (Robert Koch Institute Berlin, Humbolt University), Michael Stumpf (Imperial College London)
• Day 2: Session "Analysis of Time-evolving Networks"
Invited speakers: Renaud Lambiotte (University of Namur), Vito Latora (Queen Mary, University of London), Ciro Cattuto (ISI Foundation Torino), Simon Frost (University Cambridge)
• Day 3: Session "Network Control – Theory and Application"
Invited speakers: Istvan Kiss (University of Sussex), Márton Karsai (ENS de Lyon), John Mittler (University of Washington)