dc.contributor.author | Del Vecchio, Domitilla | |
dc.contributor.author | Dy, Aaron James | |
dc.contributor.author | Qian, Yili | |
dc.date.accessioned | 2018-11-16T19:44:24Z | |
dc.date.available | 2018-11-16T19:44:24Z | |
dc.date.issued | 2016-07 | |
dc.date.submitted | 2016-05 | |
dc.identifier.issn | 1742-5689 | |
dc.identifier.issn | 1742-5662 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/119159 | |
dc.description.abstract | The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology. | en_US |
dc.description.sponsorship | United States. Air Force. Office of Scientific Research (grant no. FA9550-14-1- 0060) | en_US |
dc.description.sponsorship | United States. Office of Naval Research (grant no. N000141310074) | en_US |
dc.description.sponsorship | National Science Foundation (U.S.). Graduate Research Fellowship Program | en_US |
dc.publisher | Royal Society Publishing | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1098/RSIF.2016.0380 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | MIT Web Domain | en_US |
dc.title | Control theory meets synthetic biology | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Del Vecchio, Domitilla, Aaron J. Dy, and Yili Qian. “Control Theory Meets Synthetic Biology.” Journal of The Royal Society Interface 13, no. 120 (July 2016): 20160380. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Institute for Medical Engineering & Science | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Biological Engineering | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Synthetic Biology Center | en_US |
dc.contributor.mitauthor | Del Vecchio, Domitilla | |
dc.contributor.mitauthor | Dy, Aaron James | |
dc.contributor.mitauthor | Qian, Yili | |
dc.relation.journal | Journal of The Royal Society Interface | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2018-11-09T18:18:46Z | |
dspace.orderedauthors | Del Vecchio, Domitilla; Dy, Aaron J.; Qian, Yili | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-6472-8576 | |
dc.identifier.orcid | https://orcid.org/0000-0003-0319-5416 | |
dc.identifier.orcid | https://orcid.org/0000-0002-1097-0401 | |
mit.license | OPEN_ACCESS_POLICY | en_US |