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Article: Optimal control policy for probabilistic Boolean networks with hard constraints

TitleOptimal control policy for probabilistic Boolean networks with hard constraints
Authors
Issue Date2009
PublisherThe Institution of Engineering and Technology. The Journal's web site is located at http://www.ietdl.org/IP-SYB
Citation
IET Systems Biology, 2009, v. 3 n. 2, p. 90-99 How to Cite?
AbstractIt is well known that the control/intervention of some genes in a genetic regulatory network is useful for avoiding undesirable states associated with some diseases like cancer. For this purpose, both optimal finite-horizon control and infinite-horizon control policies have been proposed. Boolean networks (BNs) and its extension probabilistic Boolean networks (PBNs) as useful and effective tools for modelling gene regulatory systems have received much attention in the biophysics community. The control problem for these models has been studied widely. The optimal control problem in a PBN can be formulated as a probabilistic dynamic programming problem. In the previous studies, the optimal control problems did not take into account the hard constraints, i.e. to include an upper bound for the number of controls that can be applied to the captured PBN. This is important as more treatments may bring more side effects and the patients may not bear too many treatments. A formulation for the optimal finite-horizon control problem with hard constraints introduced by the authors. This model is state independent and the objective function is only dependent on the distance between the desirable states and the terminal states. An approximation method is also given to reduce the computational cost in solving the problem. Experimental results are given to demonstrate the efficiency of our proposed formulations and methods. © The Institution of Engineering and Technology 2009.
Persistent Identifierhttp://hdl.handle.net/10722/58975
ISSN
2015 Impact Factor: 0.764
2015 SCImago Journal Rankings: 0.399
ISI Accession Number ID
Funding AgencyGrant Number
RGC7017/07P
HKU Strategic Research Theme Fund on Computational Sciences
Hung Hing Ying Physical Research Fund
HKU CRGC
MEXT, Japan
Funding Information:

W.-K. Ching is supported in part by RGC Grant 7017/07P, HKU Strategic Research Theme Fund on Computational Sciences, Hung Hing Ying Physical Research Fund, HKU CRGC Grants. T. Akutsu is partially supported by Grant-in-Aid Systems Genomics from MEXT, Japan.

References

 

DC FieldValueLanguage
dc.contributor.authorChing, WKen_HK
dc.contributor.authorZhang, SQen_HK
dc.contributor.authorJiao, Yen_HK
dc.contributor.authorAkutsu, Ten_HK
dc.contributor.authorTsing, NKen_HK
dc.contributor.authorWong, ASen_HK
dc.date.accessioned2010-05-31T03:40:39Z-
dc.date.available2010-05-31T03:40:39Z-
dc.date.issued2009en_HK
dc.identifier.citationIET Systems Biology, 2009, v. 3 n. 2, p. 90-99en_HK
dc.identifier.issn1751-8849en_HK
dc.identifier.urihttp://hdl.handle.net/10722/58975-
dc.description.abstractIt is well known that the control/intervention of some genes in a genetic regulatory network is useful for avoiding undesirable states associated with some diseases like cancer. For this purpose, both optimal finite-horizon control and infinite-horizon control policies have been proposed. Boolean networks (BNs) and its extension probabilistic Boolean networks (PBNs) as useful and effective tools for modelling gene regulatory systems have received much attention in the biophysics community. The control problem for these models has been studied widely. The optimal control problem in a PBN can be formulated as a probabilistic dynamic programming problem. In the previous studies, the optimal control problems did not take into account the hard constraints, i.e. to include an upper bound for the number of controls that can be applied to the captured PBN. This is important as more treatments may bring more side effects and the patients may not bear too many treatments. A formulation for the optimal finite-horizon control problem with hard constraints introduced by the authors. This model is state independent and the objective function is only dependent on the distance between the desirable states and the terminal states. An approximation method is also given to reduce the computational cost in solving the problem. Experimental results are given to demonstrate the efficiency of our proposed formulations and methods. © The Institution of Engineering and Technology 2009.en_HK
dc.languageengen_HK
dc.publisherThe Institution of Engineering and Technology. The Journal's web site is located at http://www.ietdl.org/IP-SYBen_HK
dc.relation.ispartofIET Systems Biologyen_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshGene Regulatory Networksen_HK
dc.subject.meshModels, Geneticen_HK
dc.subject.meshModels, Statisticalen_HK
dc.subject.meshSystems Biology - methodsen_HK
dc.titleOptimal control policy for probabilistic Boolean networks with hard constraintsen_HK
dc.typeArticleen_HK
dc.identifier.emailChing, WK: wching@hku.hken_HK
dc.identifier.emailTsing, NK: nktsing@hku.hken_HK
dc.identifier.emailWong, AS: awong1@hkucc.hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.identifier.authorityTsing, NK=rp00794en_HK
dc.identifier.authorityWong, AS=rp00805en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1049/iet-syb.2008.0120en_HK
dc.identifier.pmid19292563-
dc.identifier.scopuseid_2-s2.0-62649169298en_HK
dc.identifier.hkuros154827en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-62649169298&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3en_HK
dc.identifier.issue2en_HK
dc.identifier.spage90en_HK
dc.identifier.epage99en_HK
dc.identifier.eissn1751-8857-
dc.identifier.isiWOS:000264454600003-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChing, WK=13310265500en_HK
dc.identifier.scopusauthoridZhang, SQ=10143093600en_HK
dc.identifier.scopusauthoridJiao, Y=24764580800en_HK
dc.identifier.scopusauthoridAkutsu, T=7102080520en_HK
dc.identifier.scopusauthoridTsing, NK=6602663351en_HK
dc.identifier.scopusauthoridWong, AS=23987963300en_HK

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