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Book Chapter: Boolean Model

TitleBoolean Model
Authors
Chen, XChing, WKTsing, NK
Issue Date2013
PublisherSpringer
Citation
Boolean Model. In Dubitzky, W ... (et al) (Eds.), Encyclopedia of Systems Biology, p. 155-157. New York: Springer, 2013 How to Cite?
DOI: http://dx.doi.org/10.1007/978-1-4419-9863-7_375
AbstractBoolean network (BN) is known as a popular mathematical model for modeling genetic regulatory networks. The BN model was first proposed by Kauffman (1969). In a BN model, the gene expression states are quantized into only two levels: on and off (represented as 1 and 0). The target gene is determined by several other genes called its input genes according to regulation rules (given as Boolean functions). A BN is said to be well defined when all the input genes and Boolean functions are given (Kauffman (1993)). There are two types of BN models: synchronous BNs and asynchronous BNs, depending on whether or not the states of nodes are updated synchronously. Synchronous model is more popular and easier to analyze and therefore we adopt it in our discussion. We note that a BN model is a deterministic model and the only randomness comes from its initial state. Considering the inherent deterministic directional
Persistent Identifierhttp://hdl.handle.net/10722/198730
ISBN
9781441998620

 

DC FieldValueLanguage
dc.contributor.authorChen, Xen_US
dc.contributor.authorChing, WKen_US
dc.contributor.authorTsing, NKen_US
dc.date.accessioned2014-07-07T09:40:03Z-
dc.date.available2014-07-07T09:40:03Z-
dc.date.issued2013en_US
dc.identifier.citationBoolean Model. In Dubitzky, W ... (et al) (Eds.), Encyclopedia of Systems Biology, p. 155-157. New York: Springer, 2013en_US
dc.identifier.isbn9781441998620en_US
dc.identifier.urihttp://hdl.handle.net/10722/198730-
dc.description.abstractBoolean network (BN) is known as a popular mathematical model for modeling genetic regulatory networks. The BN model was first proposed by Kauffman (1969). In a BN model, the gene expression states are quantized into only two levels: on and off (represented as 1 and 0). The target gene is determined by several other genes called its input genes according to regulation rules (given as Boolean functions). A BN is said to be well defined when all the input genes and Boolean functions are given (Kauffman (1993)). There are two types of BN models: synchronous BNs and asynchronous BNs, depending on whether or not the states of nodes are updated synchronously. Synchronous model is more popular and easier to analyze and therefore we adopt it in our discussion. We note that a BN model is a deterministic model and the only randomness comes from its initial state. Considering the inherent deterministic directional-
dc.languageengen_US
dc.publisherSpringeren_US
dc.relation.ispartofEncyclopedia of Systems Biologyen_US
dc.titleBoolean Modelen_US
dc.typeBook_Chapteren_US
dc.identifier.emailChing, WK: wching@hku.hken_US
dc.identifier.emailTsing, NK: nktsing@hku.hken_US
dc.identifier.authorityChing, WK=rp00679en_US
dc.identifier.authorityTsing, NK=rp00794en_US
dc.identifier.doi10.1007/978-1-4419-9863-7_375en_US
dc.identifier.hkuros229721en_US
dc.identifier.spage155en_US
dc.identifier.epage157en_US
dc.publisher.placeNew Yorken_US

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