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dc.contributor.author
Busetto, Alberto G.
dc.contributor.author
Lygeros, John
dc.date.accessioned
2020-10-01T07:47:28Z
dc.date.available
2017-06-11T15:33:14Z
dc.date.available
2019-07-03T12:20:26Z
dc.date.available
2020-10-01T07:47:28Z
dc.date.issued
2014
dc.identifier.isbn
978-1-4799-7746-8
en_US
dc.identifier.isbn
978-1-4673-6090-6
en_US
dc.identifier.isbn
978-1-4799-7745-1
en_US
dc.identifier.other
10.1109/CDC.2014.7040282
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/96542
dc.description.abstract
This study is primarily motivated by biological applications and focuses on the identification of Boolean networks from scarce and noisy data. We consider two Bayesian experimental design scenarios: selection of the observations under a budget, and input design. The goal is to maximize the mutual information between models and data, that is the ultimate statistical upper bound on the identifiability of a system from empirical data. First, we introduce a method to select which components of the state variable to measure under a budget constraint, and at which time points. Our greedy approach takes advantage of the submodularity of the mutual information, and hence requires only a polynomial number of evaluations of the objective to achieve near-optimal designs. Second, we consider the computationally harder task of designing sequences of input interventions, and propose a likelihood-free approximation method. Exact and approximate design solutions are verified with predictive models of genetic regulatory interaction networks in embryonic development.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
Experimental design for system identication of boolean control networks in biology
en_US
dc.type
Conference Paper
dc.date.published
2015-02-12
ethz.book.title
2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)
en_US
ethz.pages.start
5704
en_US
ethz.pages.end
5709
en_US
ethz.event
53rd IEEE Annual Conference on Decision and Control (CDC 2014)
en_US
ethz.event.location
Los Angeles, CA, USA
en_US
ethz.event.date
December 15-17, 2014
en_US
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
2017-06-11T15:33:40Z
ethz.source
ECIT
ethz.identifier.importid
imp593652d240baa63933
ethz.ecitpid
pub:151177
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2017-07-25T10:58:57Z
ethz.rosetta.lastUpdated
2021-02-15T17:42:19Z
ethz.rosetta.versionExported
true
ethz.COinS
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