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Design and control of microbial communities

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UMCW06 - Microbial communities: current approaches and open challenges

Engineering synthetic microbial communities has great potential for clinical and biotechnological applications. Tools from engineering biology can also help us to perturb and understand natural communities. Here I show how methods based on Bayesian statistics can be used to design synthetic ecologies from the bottom-up, focussing on communities comprising quorum sensing systems and competitive interactions through bacteriocin expression. In the second part of my talk, I will describe how we have been leveraging reinforcement learning for the control of communities and how using the same methodology we can design optimal experiments to disentangle interactions within a microbial community. 

This talk is part of the Isaac Newton Institute Seminar Series series.

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