Parameter identification for stochastic hybrid models of biological interaction networks
dc.contributor.author
Cinquemani, Eugenio
dc.contributor.author
Porreca, Riccardo
dc.contributor.author
Ferrari-Trecate, Giancarlo
dc.contributor.author
Lygeros, John
dc.date.accessioned
2020-10-09T13:02:25Z
dc.date.available
2017-06-08T17:26:34Z
dc.date.available
2020-10-09T13:02:25Z
dc.date.issued
2007
dc.identifier.isbn
978-1-4244-1497-0
en_US
dc.identifier.isbn
978-1-4244-1498-7
en_US
dc.identifier.other
10.1109/CDC.2007.4434647
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/6553
dc.description.abstract
Based on a model of subtilin production by Bacillus subtilis, in this paper we discuss the parameter identification of stochastic hybrid dynamics that are typically found in biological regulatory networks. In accordance with the structure of the model, identification is split in two subproblems: estimation of the genetic network regulating subtilin production from gene expression data, and estimation of population dynamics based on nutrient and population profiles. Techniques for parameter estimation from sparse and irregularly sampled observations are developed and applied to simulated data. Numerical results are provided to show the effectiveness of our methods.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
Parameter identification for stochastic hybrid models of biological interaction networks
en_US
dc.type
Conference Paper
dc.date.published
2008-01-21
ethz.book.title
Proceedings of the 46th IEEE Conference on Decision and Control
en_US
ethz.pages.start
5180
en_US
ethz.pages.end
5185
en_US
ethz.event
46th IEEE Conference on Decision and Control (CDC 2007)
en_US
ethz.event.location
New Orleans, LA, USA
en_US
ethz.event.date
December 12-14, 2007
en_US
ethz.identifier.nebis
000037563
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::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02650 - Institut für Automatik / Automatic Control Laboratory::03751 - Lygeros, John / Lygeros, John
ethz.date.deposited
2017-06-08T17:26:43Z
ethz.source
ECIT
ethz.identifier.importid
imp59364ba384f9f75884
ethz.ecitpid
pub:16984
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2017-07-12T10:57:06Z
ethz.rosetta.lastUpdated
2021-02-15T17:58:10Z
ethz.rosetta.versionExported
true
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