Design, optimization and control
in systems and synthetic biology

Paris, June 11-12, 2012


The main aim of quantitative systems biology is to obtain a quantitative understanding of the functioning of biological systems at the cellular and tissue levels. To reach this goal, significant research efforts have been made to combine quantitative modeling approaches and state-of-the-art live-cell observation methods, notably via the joint use of time-lapse microscopy, reporter genes techniques and microfluidics.

Although mainly developed with the objective of helping with better understanding the complex functioning of biological system, this approach has also been applied to two other problems. Firstly, it plays a central role to support the rational design and optimization of engineered biological systems in synthetic biology. Secondly, it has been instrumental to the development of novel methods for the control of intracellular processes at the cell level.

This workshop focuses on these two recent research directions. Its main aim is to gather during two days, leading international scientists who significantly contributed to these domains. Topics of particular interest include long-term imaging of cellular processes, microfluidics, synthetic biology, quantitative modeling of biomolecular processes, and control theory applied to biological systems.

Keywords: quantitative biology, microfluidics and single cell biology, biological noise, control and optimization, synthetic biology, deterministic and stochastic modeling.

Registration: Registration is free but mandatory. The workshop will happen in June at ENS Paris, located in the heart of Quartier Latin.

The list of confirmed speakers include

This interdisciplinary workshop will be of interest for biologists looking for innovative means to probe the functionning of cellular systems, notably at the single-cell level, physicists developping innovative microfluidics or microscopy systems, and mathematicians and computer scientists working on modeling and control of biological systems.

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