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dc.contributor.authorRubens, Jacob R.
dc.contributor.authorSelvaggio, Gianluca
dc.contributor.authorLu, Timothy K.
dc.date.accessioned2016-06-09T15:13:34Z
dc.date.available2016-06-09T15:13:34Z
dc.date.issued2016-06
dc.date.submitted2015-09
dc.identifier.issn2041-1723
dc.identifier.urihttp://hdl.handle.net.ezproxyberklee.flo.org/1721.1/103081
dc.description.abstractLiving cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.en_US
dc.description.sponsorshipFundacao para a Ciencia e a Tecnologia (Fellowship SFRH/BD/51576/2011)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (1350625)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (1124247)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (N000141310424)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (New Innovator Award 1DP2OD008435)en_US
dc.description.sponsorshipNational Centers for Systems Biology (U.S.) (1P50GM098792)en_US
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org.ezproxyberklee.flo.org/10.1038/ncomms11658en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleSynthetic mixed-signal computation in living cellsen_US
dc.typeArticleen_US
dc.identifier.citationRubens, Jacob R., Gianluca Selvaggio, and Timothy K. Lu. “Synthetic Mixed-Signal Computation in Living Cells.” Nature Communications 7 (June 3, 2016): 11658.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Synthetic Biology Centeren_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Microbiology Graduate Programen_US
dc.contributor.departmentMassachusetts Institute of Technology. Research Laboratory of Electronicsen_US
dc.contributor.mitauthorRubens, Jacob R.en_US
dc.contributor.mitauthorSelvaggio, Gianlucaen_US
dc.contributor.mitauthorLu, Timothy K.en_US
dc.relation.journalNature Communicationsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsRubens, Jacob R.; Selvaggio, Gianluca; Lu, Timothy K.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1304-0151
dc.identifier.orcidhttps://orcid.org/0000-0002-9999-6690
mit.licensePUBLISHER_CCen_US


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