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dc.contributor.author
Steel, Harrison
dc.contributor.author
Lillacci, Gabriele
dc.contributor.author
Khammash, Mustafa Hani
dc.contributor.author
Papachristodoulou, Antonis
dc.date.accessioned
2020-10-02T09:02:10Z
dc.date.available
2018-02-28T13:10:59Z
dc.date.available
2018-02-28T13:10:33Z
dc.date.available
2018-01-30T10:49:31Z
dc.date.available
2018-01-30T14:33:49Z
dc.date.available
2018-02-28T01:57:16Z
dc.date.available
2020-10-02T09:02:10Z
dc.date.issued
2017
dc.identifier.isbn
978-1-5090-2873-3
en_US
dc.identifier.isbn
978-1-5090-2872-6
en_US
dc.identifier.isbn
978-1-5090-2874-0
en_US
dc.identifier.other
10.1109/CDC.2017.8263791
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/245251
dc.description.abstract
Synthetic biology is a rapidly expanding field at the interface of the engineering and biological sciences which aims to apply rational design principles in biological contexts. Many natural processes utilise regulatory architectures that parallel those found in control and electrical engineering, which has motivated their implementation as part of synthetic biological constructs. Tools based upon control theoretical concepts can be used to design such systems, as well as to guide their experimental realisation. In this paper we provide examples of biological implementations of negative feedback systems, and discuss progress made toward realisation of other feedback and control architectures. We then outline major challenges posed by the design of such systems, particularly focusing on those which are specific to biological contexts and on which feedback control can have a significant impact. We explore future directions for work in the field, including new approaches for theoretical design of biological control systems, the utilisation of novel components for their implementation, and the potential for application of automation and machine-learning approaches to accelerate synthetic biological research.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
Challenges at the interface of control engineering and synthetic biology
en_US
dc.type
Conference Paper
dc.date.published
2018-01-23
ethz.book.title
2017 IEEE 56th Annual Conference on Decision and Control (CDC)
en_US
ethz.pages.start
1014
en_US
ethz.pages.end
1023
en_US
ethz.event
56th IEEE Annual Conference on Decision and Control (CDC 2017)
en_US
ethz.event.location
Melbourne, Australia
en_US
ethz.event.date
December 12-15, 2017
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::03921 - Khammash, Mustafa / Khammash, Mustafa
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::03921 - Khammash, Mustafa / Khammash, Mustafa
en_US
ethz.date.deposited
2018-01-30T10:49:32Z
ethz.source
FORM
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2018-03-01T07:41:52Z
ethz.rosetta.lastUpdated
2024-02-02T12:13:16Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/244771
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/236931
ethz.COinS
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