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dc.contributor.authorMcBride, Cameron David
dc.contributor.authorDel Vecchio, Domitilla
dc.date.accessioned2021-11-09T19:52:58Z
dc.date.available2021-11-09T18:55:57Z
dc.date.available2021-11-09T19:52:58Z
dc.date.issued2018-12
dc.identifier.urihttps://hdl.handle.net/1721.1/138034.2
dc.description.abstract© 2018 IEEE. Sharing of cellular resources in genetic circuits negatively affects performance and often leads to unpredictable behavior. Measuring key metrics from experimental data that quantify resource sharing and its effect on a system's output would be highly useful. In this paper, we propose two metrics, Q and S, representing the quantity of resources used by a genetic circuit module and the sensitivity of the output of a module to resource disturbances, respectively. Together, Q and S may be used to estimate the change in the output of a module in response to the disturbances in the availability of resources. We cast the problem of finding these metrics as a parameter estimation problem and outline a simple procedure to estimate these metrics from data. Knowledge of Q and S for a circuit module enables prediction of the effects of resource sharing and allows for resource-aware design of genetic circuits.en_US
dc.description.sponsorshipNational Science Foundation (Award 1521925)en_US
dc.language.isoen
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/cdc.2018.8619465en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleResource Sensor Design for Quantifying Resource Competition in Genetic Circuitsen_US
dc.typeArticleen_US
dc.identifier.citationMcBride, Cameron and Del Vecchio, Domitilla. 2018. "Resource Sensor Design for Quantifying Resource Competition in Genetic Circuits." Proceedings of the IEEE Conference on Decision and Control, 2018-December.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.relation.journalProceedings of the IEEE Conference on Decision and Controlen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2020-07-08T14:05:37Z
dspace.date.submission2020-07-08T14:05:39Z
mit.journal.volume2018-Decemberen_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusPublication Information Neededen_US


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