Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3784
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dc.contributor.authorBreitling, R-
dc.contributor.authorGilbert, D-
dc.contributor.authorHeiner, M-
dc.contributor.authorOrton, R-
dc.date.accessioned2009-10-27T15:19:23Z-
dc.date.available2009-10-27T15:19:23Z-
dc.date.issued2008-
dc.identifier.citationBriefings in Bioinformatics, 9(5), 404-421.en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/3784-
dc.descriptionhttp://dx.doi.org/10.1093/bib/bbn026en
dc.description.abstractQuantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted from theoretical computing science. Here we provide a general introduction to the field of formal modelling, which emphasizes the intuitive biochemical basis of the modelling process, but is also accessible for an audience with a background in computing science and/or model engineering. We show how signal transduction cascades can be modelled in a modular fashion, using both a qualitative approach { Qualitative Petri nets, and quantitative approaches { Continuous Petri Nets and Ordinary Differential Equations. We review the major elementary building blocks of a cellular signalling model, discuss which critical design decisions have to be made during model building, and present ...en
dc.language.isoen_USen
dc.publisherOxford University Pressen
dc.titleA structured approach for the engineering of biochemical network models, illustrated for signalling pathwaysen
dc.typeArticleen
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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