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Article: Distribution and enumeration of attractors in probabilistic Boolean networks

TitleDistribution and enumeration of attractors in probabilistic Boolean networks
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. 6, p. 465-474 How to Cite?
AbstractMany mathematical models for gene regulatory networks have been proposed. In this study, the authors study attractors in probabilistic Boolean networks (PBNs). They study the expected number of singleton attractors in a PBN and show that it is (2 - (1/2) L-1)n, where n is the number of nodes in a PBN and L is the number of Boolean functions assigned to each node. In the case of L=2, this number is simplified into 1.5 n. It is an interesting result because it is known that the expected number of singleton attractors in a Boolean network (BN) is 1. Then, we present algorithms for identifying singleton and small attractors and perform both theoretical and computational analyses on their average case time complexities. For example, the average case time complexities for identifying singleton attractors of a PBN with L=2 and L=3 are O(1.601 n) and O(1.763 n), respectively. The results of computational experiments suggest that these algorithms are much more efficient than the naive algorithm that examines all possible 2 n states. © 2009 © The Institution of Engineering and Technology.
Persistent Identifierhttp://hdl.handle.net/10722/156245
ISSN
2015 Impact Factor: 0.764
2015 SCImago Journal Rankings: 0.399
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHayashida, Men_US
dc.contributor.authorTamura, Ten_US
dc.contributor.authorAkutsu, Ten_US
dc.contributor.authorChing, WKen_US
dc.contributor.authorCong, Yen_US
dc.date.accessioned2012-08-08T08:41:00Z-
dc.date.available2012-08-08T08:41:00Z-
dc.date.issued2009en_US
dc.identifier.citationIET Systems Biology, 2009, v. 3 n. 6, p. 465-474en_US
dc.identifier.issn1751-8849en_US
dc.identifier.urihttp://hdl.handle.net/10722/156245-
dc.description.abstractMany mathematical models for gene regulatory networks have been proposed. In this study, the authors study attractors in probabilistic Boolean networks (PBNs). They study the expected number of singleton attractors in a PBN and show that it is (2 - (1/2) L-1)n, where n is the number of nodes in a PBN and L is the number of Boolean functions assigned to each node. In the case of L=2, this number is simplified into 1.5 n. It is an interesting result because it is known that the expected number of singleton attractors in a Boolean network (BN) is 1. Then, we present algorithms for identifying singleton and small attractors and perform both theoretical and computational analyses on their average case time complexities. For example, the average case time complexities for identifying singleton attractors of a PBN with L=2 and L=3 are O(1.601 n) and O(1.763 n), respectively. The results of computational experiments suggest that these algorithms are much more efficient than the naive algorithm that examines all possible 2 n states. © 2009 © The Institution of Engineering and Technology.en_US
dc.languageengen_US
dc.publisherThe Institution of Engineering and Technology. The Journal's web site is located at http://www.ietdl.org/IP-SYBen_US
dc.relation.ispartofIET Systems Biologyen_US
dc.subject.meshAlgorithmsen_US
dc.subject.meshAnimalsen_US
dc.subject.meshGene Regulatory Networksen_US
dc.subject.meshMarkov Chainsen_US
dc.subject.meshModels, Geneticen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshProto-Oncogene Proteins - Geneticsen_US
dc.subject.meshSystems Biology - Methodsen_US
dc.subject.meshTranscription, Geneticen_US
dc.subject.meshWnt Proteins - Geneticsen_US
dc.titleDistribution and enumeration of attractors in probabilistic Boolean networksen_US
dc.typeArticleen_US
dc.identifier.emailChing, WK:wching@hku.hken_US
dc.identifier.authorityChing, WK=rp00679en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1049/iet-syb.2008.0177en_US
dc.identifier.pmid19947772en_US
dc.identifier.scopuseid_2-s2.0-71949116759en_US
dc.identifier.hkuros168366-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-71949116759&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume3en_US
dc.identifier.issue6en_US
dc.identifier.spage465en_US
dc.identifier.epage474en_US
dc.identifier.isiWOS:000272502400004-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridHayashida, M=9275689800en_US
dc.identifier.scopusauthoridTamura, T=13609056800en_US
dc.identifier.scopusauthoridAkutsu, T=7102080520en_US
dc.identifier.scopusauthoridChing, WK=13310265500en_US
dc.identifier.scopusauthoridCong, Y=35185897700en_US

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