? This proposal focuses on the computational modeling and experimental construction of synthetic gene regulatory networks. The project seeks to isolate carefully chosen subsystems from natural organisms and focusing both modeling and experimental efforts on determining the subsystems' behavior within living cells in real-time. The broad goal of such work is to assemble increasingly complex gene networks, while at each stage maintaining the ability to test models in a tractable experimental system. In this way, the accomplishment of the specific aims in this proposal will lead to significant advances in the development of theoretical, computational and experimental tools for modeling, designing and constructing synthetic gene networks for interfacing with the cellular environment. The proposed construction of a faster genetic switch will provide a critical step towards sophisticated cellular control schemes that require rapid transitions between genetic """"""""states"""""""". From a modular perspective, the toggle switch can be viewed as one particular building-block circuit that constitutes large-scale genomic wiring, and thus represents a first step towards an understanding of whole-genome regulatory complexity. Likewise, the proposed coupling of genetic switches will build upon this modular perspective by designing and constructing higher order networks consisting of coupled regulatory modules. The oscillator project will provide a means for entraining or inducing network oscillations in cellular protein levels. Such control could prove useful in the design of networks which interact with processes such as cellular growth that require precise timing. From a medical perspective, such control of cellular function through the design and manipulation of gene regulatory networks is an intriguing possibility. Current examples of potential applicability range from the use of oncolytic viruses capable of selectively killing tumor cells, to the flipping of genetic switches in mammalian neuronal cells. This proposal would provide an experimentally-validated computational framework for designing such gene networks. ? ? ?
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