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Recent advances in synthetic biology have brought the fantasy of having synthetic multicellular systems working at nanoscale closer to reality. Indeed, such systems consisting of networked biological nanomachines have a great potential for many novel applications like environmental monitoring and healthcare. In this paper, we consider dense networks of interacting bacteria capable of monitoring and treating diseases that affect microscopic regions in the human body. Towards this end, we propose a modeling approach for capturing the dynamics of such dense populations of interacting bacteria and estimate their performance for diagnostic and drug delivery purposes. Consequently, our approach can be used to identify various design trade-offs for dense networks of bacteria and design predictable and reliable synthetic multicellular systems.
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Wei et al. (2013) studied this question.
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