Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3026
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dc.contributor.authorCalder, M-
dc.contributor.authorVyshemirsky, V-
dc.contributor.authorGilbert, D-
dc.contributor.authorOrton, R-
dc.coverage.spatial12en
dc.date.accessioned2009-02-06T16:37:55Z-
dc.date.available2009-02-06T16:37:55Z-
dc.date.issued2005-
dc.identifier.citationProceedings of Third International CMSB 2005 (Computational Methods in Systems Biology), University of Edinburgh , 3-5 April 2005 , pp. 179-190en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/3026-
dc.description.abstractWe describe a new modelling and analysis approach for signal transduction networks in the presence of incomplete data. We illustrate the approach with an example, the RKIP inhibited ERK pathway [1]. Our models are based on high level descriptions of continuous time Markov chains: reactions are modelled as synchronous processes and concentrations are modelled by discrete, abstract quantities. The main advantage of our approach is that using a (continuous time) stochastic logic and the PRISM model checker, we can perform quantitative analysis of queries such as if a concentration reaches a certain level, will it remain at that level thereafter? We also perform standard simulations and compare our results with a traditional ordinary differential equation model. An interesting result is that for the example pathway, only a small number of discrete data values is required to render the simulations practically indistinguishable.en
dc.format.extent408037 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherUniversity of Edinburghen
dc.titleAnalysis of signalling pathways using the prism model checkeren
dc.typeConference Paperen
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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