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Networks: Dynamics and Flows

NET2009@ECCS'09 will be organised as a satellite conference of ECCS'09, which will take place on Thursday, 24th September 2009, Room B3.03. This day will have selected contributions from network theories and their applications. These serve as invitations to NET2009, a one week workshop taking place in the week after ECCS'09.

14:00 - 15:40 Introduction & Talks

Markus Kirkilionis (Warwick)
From static to dynamic networks – Outlook to NET2009

Felix Reed-Tsochas (Oxford)
Studying the structure and dynamics of organisational networks in the wild

Abstract: This talk will be based on a number of related projects, all grounded in the same empirical data, recording the evolution of an organisational network. Our dataset tracks interactions between manufacturers and suppliers in the New York garment industry over a period of almost 20 years, and provides a unique opportunity to explore the dynamics of a self-organised network. I will start by discussing the dynamics of network contraction, both in terms of the empirically observed behaviour and with respect to a simulation model that we have constructed on this basis. Here, the key findings relate to what mechanisms generate topological robustness in a network that is shrinking. I will then consider what assembly rules, in terms of a stochastic model, are able to generate some of the key structural features observed in our organisational network, if we represent it as a bipartite network. Here, the focus is on the extent to which the proposed bipartite cooperation model may be applied to different contexts. Finally, I consider the propagation of errors in this supplier network, where errors correspond to refund payments. The question here is whether errors appear to propagate through the network, and what mechanisms enable of inhibit contagion.


Fatihcan M. Atay ( Max Planck Institute for Mathematics in the Sciences, Germany
Mathematical Tools for Studying Collective Behavior in Dynamical Networks

Abstract: Mathematical sciences provide some powerful tools for investigating complex networks. Conversely, the latter contributes to the development of new methods by posing novel problems. In this talk I will present ideas from the theory of dynamical systems and graph theory that are useful for studying dynamical networks, that is, networks where either the states of the nodes or the network structure is changing in time. I will mostly focus on collective behavior such as synchronization and consensus, and discuss the emergence of novel behavior through coordination of network action. In addition to undirected, directed, and weighted networks, I will indicate extensions to networks with time delays, networks with time-varying links, and signed networks, i.e. those with both positive and negative weighted links, as in the excitatory and inhibitory connections in the brain.


16:00 - 16:30 Coffee Break

16:30 - 17:50 Talks, Focus on Biological Applications.

Markus Kirkilionis (Warwick)
Detailed Modeling of Gene Regulatory Networks
Abstract: We discuss new ways of modeling small genetic networks with high resolution of molecular details. The theory is based on an extension
of reaction systems where particles can be both unstructured or structured with discrete state spaces. Genetic regulation is modeled by binding sites along the DNA and the communication of smaller (unstructured) particles (like transcription factors) affecting the state of DNA binding sites.


François KEPES
Epigenomics Project, Genopole, CNRS & Univ. Evry, France

Abstract: Biologists are fond of wiring diagrams abstracting the system's components and their interactions. Network-based approaches extend this common viewpoint, while providing a well-paved path to more formal analysis. In particular, a simple topological or dynamical analysis may sometimes allow to reject a biologist's model with little effort. A deeper analysis may shed light on the plausible mechanisms of a well-described and poorly understood phenomenon. Besides this explanatory capacity, the analysis may in different settings be of predictive value or increase the efficiency of subsequent experimental testing. However, what often appears on the biologist's cartoons and is not directly amenable to network-based analysis stricto sensu is the spatial aspect of the biological process under scrutiny. The spatial development of regulatory networks will be emphasized in this talk.