Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/18081
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dc.contributor.authorFigueiredo, Danielpt
dc.contributor.authorMartins, Manuel A.pt
dc.contributor.authorChaves, Madalenapt
dc.date.accessioned2017-07-14T14:05:34Z-
dc.date.issued2017-09-
dc.identifier.issn0025-5564pt
dc.identifier.urihttp://hdl.handle.net/10773/18081-
dc.description.abstractQualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system’s global dynamics and the latter pro- viding more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic ( d L ), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how d L can be used as an alternative, or also as a complement to methods already used.pt
dc.language.isoengpt
dc.publisherElsevierpt
dc.relationUID/MAT/04106/2013pt
dc.relationPOCI-01-0145-FEDER-016692pt
dc.relationPD/BD/114186/2016pt
dc.relationANR-16-CE33-0016-01pt
dc.rightsopenAccesspor
dc.subjectDifferential dynamic logicpt
dc.subjectBiological regulatory networkspt
dc.subjectHybrid systemspt
dc.subjectDiscrete controllerspt
dc.titleApplying differential dynamic logic to reconfigurable biological networkspt
dc.typearticlept
dc.peerreviewedyespt
ua.distributioninternationalpt
degois.publication.firstPage10pt
degois.publication.lastPage20pt
degois.publication.titleMathematical Biosciencespt
degois.publication.volume291pt
dc.date.embargo2018-09-01T14:00:00Z-
dc.identifier.doi10.1016/j.mbs.2017.05.012pt
Appears in Collections:CIDMA - Artigos
AGG - Artigos

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