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Conference Paper: Optimal finite-horizon control for probabilistic Boolean networks with hard constraints

TitleOptimal finite-horizon control for probabilistic Boolean networks with hard constraints
Authors
KeywordsBoolean Networks
Dynamic Programming
Finite-Horizon
Intervention
Markov Chain
Optimal Control
Probabilistic Boolean Networks
Issue Date2007
PublisherWorld Publishing Corporation
Citation
The International Symposium on Optimization and Systems Biology (OSB 2007), Beijing, China, 8-10 August 2007. In Zhang, XS, Chen, L, and Wu, LY et al. (Eds.). Lecture Notes in Operations Research 7, p. 21-28. Beijing, China: World Publishing Corporation, 2007 How to Cite?
AbstractIn this paper, we study optimal control policies for Probabilistic Boolean Networks (PBNs) with hard constraints. Boolean Networks (BNs) and PBNs are useful and effective tools for modelling genetic regulatory networks. A PBN is essentially a collection of BNs driven by a Markov chain process. It is well-known that the control/intervention of a genetic regulatory network is useful for avoiding undesirable states associated with diseases like cancer. Therefore both optimal finite-horizon control and infinite-horizon control policies have been proposed to achieve the purpose. Actually the optimal control problem can be formulated as a probabilistic dynamic programming problem. In many studies, the optimal control problems did not consider the case of hard constraints, i.e., to include a maximum upper bound for the number of controls that can be applied to the PBN. The main objective of this paper is to introduce a new formulation for the optimal finite-horizon control problem with hard constraints. Experimental results are given to demonstrate the efficiency of our proposed formulation.
Persistent Identifierhttp://hdl.handle.net/10722/100376
ISBN

 

DC FieldValueLanguage
dc.contributor.authorChing, WKen_HK
dc.contributor.authorZhang, Sen_HK
dc.contributor.authorJiao, Yen_HK
dc.contributor.authorAkutsu, Ten_HK
dc.contributor.authorWong, ASTen_HK
dc.date.accessioned2010-09-25T19:07:32Z-
dc.date.available2010-09-25T19:07:32Z-
dc.date.issued2007en_HK
dc.identifier.citationThe International Symposium on Optimization and Systems Biology (OSB 2007), Beijing, China, 8-10 August 2007. In Zhang, XS, Chen, L, and Wu, LY et al. (Eds.). Lecture Notes in Operations Research 7, p. 21-28. Beijing, China: World Publishing Corporation, 2007-
dc.identifier.isbn978-7-5062-7292-6/O568-
dc.identifier.urihttp://hdl.handle.net/10722/100376-
dc.description.abstractIn this paper, we study optimal control policies for Probabilistic Boolean Networks (PBNs) with hard constraints. Boolean Networks (BNs) and PBNs are useful and effective tools for modelling genetic regulatory networks. A PBN is essentially a collection of BNs driven by a Markov chain process. It is well-known that the control/intervention of a genetic regulatory network is useful for avoiding undesirable states associated with diseases like cancer. Therefore both optimal finite-horizon control and infinite-horizon control policies have been proposed to achieve the purpose. Actually the optimal control problem can be formulated as a probabilistic dynamic programming problem. In many studies, the optimal control problems did not consider the case of hard constraints, i.e., to include a maximum upper bound for the number of controls that can be applied to the PBN. The main objective of this paper is to introduce a new formulation for the optimal finite-horizon control problem with hard constraints. Experimental results are given to demonstrate the efficiency of our proposed formulation.-
dc.languageengen_HK
dc.publisherWorld Publishing Corporation-
dc.relation.ispartofLecture Notes in Operations Research 7en_HK
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBoolean Networks-
dc.subjectDynamic Programming-
dc.subjectFinite-Horizon-
dc.subjectIntervention-
dc.subjectMarkov Chain-
dc.subjectOptimal Control-
dc.subjectProbabilistic Boolean Networks-
dc.titleOptimal finite-horizon control for probabilistic Boolean networks with hard constraintsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChing, WK: wching@HKUCC.hku.hken_HK
dc.identifier.emailWong, AST: awong1@hkucc.hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.identifier.authorityWong, AST=rp00805en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros130216en_HK

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