Multi-scale dynamics and evolvability of biological networks
Scientific Objectives
A major challenge in systems biology is to understand the dynamics of biological networks at different scales of organization, and to integrate this knowledge into models, thereby exhibiting functional sub-networks embedded in larger dynamical systems. Multi-scale dynamics is at the heart of biological function: proteins and RNA molecules, for example, may be seen as elementary computational devices that capture various types of information from the cellular environment, providing the bottom layer of cellular dynamics from which emerge the functional networks of metabolism, signal transduction and gene regulation. Similarly, the genome not only codes for proteins, but it also determines the dynamical processing of this information in space and time via gene regulatory networks and in the epigenetic organization of the genome. The multi-scale architecture of biological networks has been shaped by evolution, and it clearly strongly influences the evolvability of organisms, i.e. their potential to adopt new functions or new phenotypes. Thus evolutionary frameworks are also necessary for us to reach a good understanding of the how and why of cellular dynamics.
The main objective of this interdisciplinary workshop is to bring together leading scientists in key fields for integrated modeling of the function and evolution of biological networks, namely: gene regulatory networks, epigenomics, metabolic networks, RNA, and evolution of biological networks. While the main focus will be on the theoretical (modeling) side, recent advances from experiments will also be considered to identify important problems that challenge existing modeling paradigms. As a major outcome, we expect the identification of common questions and promising lines of research at the interfaces of functional sub-networks, possibly leading to a future integration into more detailed and more realistic models of biological systems.
The workshop is supported by the Max Planck Society (MPG) and the Centre national de la recherche scientifique (CNRS), through the CNRS-MPG joint program in systems biology.