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Book Chapter: A Heuristic Method for Generating Probabilistic Boolean Networks from a Prescribed Transition Probability Matrix

TitleA Heuristic Method for Generating Probabilistic Boolean Networks from a Prescribed Transition Probability Matrix
Authors
Ching, WKChen, XLeung, HYTsing, NK
Issue Date2008
PublisherWorld Publishing Corporation.
Citation
A Heuristic Method for Generating Probabilistic Boolean Networks from a Prescribed Transition Probability Matrix, In Zhang, X, Chen, L, Wu, L et al. (eds.), Optimization and Systems Biology-The Second International Symposium, OSB'08, Lijiang, China, October 31-November 3, 2008, Proceedings, p. 271-278. World Publishing Corporation, 2008 How to Cite?
AbstractProbabilistic Boolean Networks (PBNs) have received much attention for modeling genetic regulatory networks. In this paper, we propose efficient algorithms for constructing a probabilistic Boolean network when its transition probability matrix is given. This is an important inverse problem in network inference from steady-state data, as most microarray data sets are assumed to be obtained from sampling the steady-state.
Persistent Identifierhttp://hdl.handle.net/10722/64485
ISBN
978-7-5062-9289-4/O639

 

DC FieldValueLanguage
dc.contributor.authorChing, WKen_HK
dc.contributor.authorChen, Xen_HK
dc.contributor.authorLeung, HYen_HK
dc.contributor.authorTsing, NKen_HK
dc.date.accessioned2010-07-13T04:51:50Z-
dc.date.available2010-07-13T04:51:50Z-
dc.date.issued2008en_HK
dc.identifier.citationA Heuristic Method for Generating Probabilistic Boolean Networks from a Prescribed Transition Probability Matrix, In Zhang, X, Chen, L, Wu, L et al. (eds.), Optimization and Systems Biology-The Second International Symposium, OSB'08, Lijiang, China, October 31-November 3, 2008, Proceedings, p. 271-278. World Publishing Corporation, 2008en_HK
dc.identifier.isbn978-7-5062-9289-4/O639-
dc.identifier.urihttp://hdl.handle.net/10722/64485-
dc.description.abstractProbabilistic Boolean Networks (PBNs) have received much attention for modeling genetic regulatory networks. In this paper, we propose efficient algorithms for constructing a probabilistic Boolean network when its transition probability matrix is given. This is an important inverse problem in network inference from steady-state data, as most microarray data sets are assumed to be obtained from sampling the steady-state.-
dc.languageengen_HK
dc.publisherWorld Publishing Corporation.en_HK
dc.relation.ispartofOptimization and Systems Biology-The Second International Symposium, OSB'08, Lijiang, China, October 31-November 3, 2008, Proceedings-
dc.titleA Heuristic Method for Generating Probabilistic Boolean Networks from a Prescribed Transition Probability Matrixen_HK
dc.typeBook_Chapteren_HK
dc.identifier.emailChing, WK: wching@HKUCC.hku.hken_HK
dc.identifier.emailChen, X: dlkcissy@hotmail.comen_HK
dc.identifier.emailLeung, HY: obliging@hkusua.hku.hken_HK
dc.identifier.emailTsing, NK: nktsing@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.identifier.authorityTsing, NK=rp00794en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.hkuros153460en_HK

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