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Conference Paper: A control model for Markovian genetic regulatory networks

TitleA control model for Markovian genetic regulatory networks
Authors
Issue Date2006
PublisherSpringer.
Citation
2005 IEEE International Conference on Granular Computing, Beijing, China, 25-27 July 2005. In Transactions on Computational Systems Biology V, 2006, p. 36-48 How to Cite?
AbstractIn this paper, we study a control model for gene intervention in a genetic regulatory network. At each time step, a finite number of controls are allowed to drive to some target states (i.e, some specific genes are on, and some specific genes are off) of a genetic network. We are interested in determining a minimum amount of control cost on a genetic network over a certain period of time such that the probabilities of obtaining such target states are as large as possible. This problem can be formulated as a stochastic dynamic programming model. However, when the number of genes is n, the number of possible states is exponentially increasing with n, and the computational cost of solving such stochastic dynamic programming model would be very huge. The main objective of this paper is to approximate the above control problem and formulate as a minimization problem with integer variables and continuous variables using dynamics of states probability distribution of genes. Our experimental results show that our proposed formulation is efficient and quite effective for solving control gene intervention in a genetic network. © Springer-Verlag Berlin Heidelberg 2006.
Persistent Identifierhttp://hdl.handle.net/10722/158863
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
Series/Report no.Lecture Notes in Computer Science ; 4070
References

 

DC FieldValueLanguage
dc.contributor.authorNg, MKen_US
dc.contributor.authorZhang, SQen_US
dc.contributor.authorChing, WKen_US
dc.contributor.authorAkutsu, Ten_US
dc.date.accessioned2012-08-08T09:03:59Z-
dc.date.available2012-08-08T09:03:59Z-
dc.date.issued2006en_US
dc.identifier.citation2005 IEEE International Conference on Granular Computing, Beijing, China, 25-27 July 2005. In Transactions on Computational Systems Biology V, 2006, p. 36-48en_US
dc.identifier.isbn978-3-540-36048-3-
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/158863-
dc.description.abstractIn this paper, we study a control model for gene intervention in a genetic regulatory network. At each time step, a finite number of controls are allowed to drive to some target states (i.e, some specific genes are on, and some specific genes are off) of a genetic network. We are interested in determining a minimum amount of control cost on a genetic network over a certain period of time such that the probabilities of obtaining such target states are as large as possible. This problem can be formulated as a stochastic dynamic programming model. However, when the number of genes is n, the number of possible states is exponentially increasing with n, and the computational cost of solving such stochastic dynamic programming model would be very huge. The main objective of this paper is to approximate the above control problem and formulate as a minimization problem with integer variables and continuous variables using dynamics of states probability distribution of genes. Our experimental results show that our proposed formulation is efficient and quite effective for solving control gene intervention in a genetic network. © Springer-Verlag Berlin Heidelberg 2006.en_US
dc.languageengen_US
dc.publisherSpringer.en_US
dc.relation.ispartofTransactions on Computational Systems Biology Ven_US
dc.relation.ispartofseriesLecture Notes in Computer Science ; 4070-
dc.titleA control model for Markovian genetic regulatory networksen_US
dc.typeConference_Paperen_US
dc.identifier.emailChing, WK:wching@hku.hken_US
dc.identifier.authorityChing, WK=rp00679en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/11790105_4-
dc.identifier.scopuseid_2-s2.0-34250836844en_US
dc.identifier.hkuros117604-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34250836844&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage36en_US
dc.identifier.epage48en_US
dc.publisher.placeBerlinen_US
dc.identifier.scopusauthoridNg, MK=34571761900en_US
dc.identifier.scopusauthoridZhang, SQ=10143093600en_US
dc.identifier.scopusauthoridChing, WK=13310265500en_US
dc.identifier.scopusauthoridAkutsu, T=7102080520en_US
dc.identifier.issnl0302-9743-

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