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dc.contributor.authorLintott, Rachelen_UK
dc.contributor.authorMcMahon, Stephenen_UK
dc.contributor.authorPrise, Kevinen_UK
dc.contributor.authorAddie-Lagorio, Celineen_UK
dc.contributor.authorShankland, Carronen_UK
dc.contributor.editorMendes, Pen_UK
dc.contributor.editorDada, JOen_UK
dc.contributor.editorSmallbone, Ken_UK
dc.description.abstractRadiation induced bystander effects are secondary effects caused by the production of chemical signals by cells in response to radiation. We present a Bio-PEPA model which builds on previous modelling work in this field to predict: the surviving fraction of cells in response to radiation, the relative proportion of cell death caused by bystander signalling, the risk of non-lethal damage and the probability of observing bystander signalling for a given dose. This work provides the foundation for modelling bystander effects caused by biologically realistic dose distributions, with implications for cancer therapies.en_UK
dc.publisherSpringer International Publishingen_UK
dc.relationLintott R, McMahon S, Prise K, Addie-Lagorio C & Shankland C (2014) Using process algebra to model radiation induced bystander effects. In: Mendes P, Dada J & Smallbone K (eds.) Computational Methods in Systems Biology: 12th International Conference, CMSB 2014, Manchester, UK, November 17-19, 2014, Proceedings. Lecture Notes in Computer Science, 8859. Computational Methods in Systems Biology 2014, Manchester, UK, 17.11.2014-19.11.2014. Cham, Switzerland: Springer International Publishing, pp. 196-210.
dc.relation.ispartofseriesLecture Notes in Computer Science, 8859en_UK
dc.rightsPublisher policy allows this work to be made available in this repository; The final publication is available at Springer via
dc.titleUsing process algebra to model radiation induced bystander effectsen_UK
dc.typeConference Paperen_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderEngineering and Physical Sciences Research Councilen_UK
dc.citation.btitleComputational Methods in Systems Biology: 12th International Conference, CMSB 2014, Manchester, UK, November 17-19, 2014, Proceedingsen_UK
dc.citation.conferencedates2014-11-17 - 2014-11-19en_UK
dc.citation.conferencelocationManchester, UKen_UK
dc.citation.conferencenameComputational Methods in Systems Biology 2014en_UK
dc.publisher.addressCham, Switzerlanden_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationQueen's University Belfasten_UK
dc.contributor.affiliationQueen's University Belfasten_UK
dc.contributor.affiliationUniversity of Stirlingen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.relation.funderprojectImproving patient outcome by integrating the generic with the personalen_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeConference Paper/Proceeding/Abstracten_UK
local.rioxx.authorLintott, Rachel|en_UK
local.rioxx.authorMcMahon, Stephen|en_UK
local.rioxx.authorPrise, Kevin|en_UK
local.rioxx.authorAddie-Lagorio, Celine|en_UK
local.rioxx.authorShankland, Carron|0000-0001-7672-2884en_UK
local.rioxx.projectEP/K039342/1|Engineering and Physical Sciences Research Council|
local.rioxx.contributorMendes, P|en_UK
local.rioxx.contributorDada, JO|en_UK
local.rioxx.contributorSmallbone, K|en_UK
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