Integrative Cell ModelsBridging Microbial Physiology and Systems biology

26 - 30 January 2015

Venue: Lorentz Center@Oort

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New developments in experimental technologies allow high resolution and global quantification of many molecular processes in microbiology. 

This fresh source of large-scale quantified information brings a momentous change to our understanding of cell biology. Originally, we thought of cellular regulation merely in terms of the molecular mechanisms underpinning point-to-point information flows. But growing evidence now points to the major impact that global trade-offs in the physiology of cells have on the execution of sub-cellular processes.

Predictive models in systems biology need to incorporate these new insights and take into account global physiological effects alongside the sub-cellular processes to understand the emergent behaviour of cells. The necessity to model global couplings becomes yet more evident in the context of synthetic biology. If we want to design synthetic gene circuits that implement functions in a cell, then we need to make sure that the synthetic construct can make efficient use of the host environment while the cell can maintain its vital processes. Just as in traditional engineering, good models are essential to rationally engineer a viable interplay.

For this to happen, a prerequisite is to measure and quantitatively understand the deep couplings between a cell and its natural or synthetic processes. The associated experiments and the new insights will be guided by and rely on the currently existing cell models. The broad ambition of this workshop is to chart the landscape of available cell models, their underpinning concepts, and associated tools, and to promote the further development and use of these models.


    Vitor Martins dos Santos, Wageningen UR  

    Andrea Weiße, School of Informatics, Edinburgh  

    Peter Swain, School of Biological Sciences, Edinburgh  

    Diego Oyarzun, Dept. of Mathematics, Imperial College  

    Vincent Danos, School of Informatics, Edinburgh  

    Frank Bruggeman, Department of Molecular Cell Physiology  

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