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dc.contributor.authorSzymanska, Zuzanna
dc.contributor.authorCytowski, Maciej
dc.contributor.authorMitchell, Elaine
dc.contributor.authorMacnamara, Cicely K.
dc.contributor.authorChaplain, Mark A. J.
dc.date.accessioned2018-06-20T23:32:03Z
dc.date.available2018-06-20T23:32:03Z
dc.date.issued2018-05
dc.identifier249923859
dc.identifier4e8c1550-b7b0-4ab8-80fc-788ee108e617
dc.identifier85021181308
dc.identifier000431110400018
dc.identifier.citationSzymanska , Z , Cytowski , M , Mitchell , E , Macnamara , C K & Chaplain , M A J 2018 , ' Computational modelling of cancer development and growth : modelling at multiple scales and multiscale modelling ' , Bulletin of Mathematical Biology , vol. 80 , no. 5 , pp. 1366-1403 . https://doi.org/10.1007/s11538-017-0292-3en
dc.identifier.issn0092-8240
dc.identifier.otherORCID: /0000-0003-4961-6052/work/34574000
dc.identifier.otherORCID: /0000-0001-5727-2160/work/55378907
dc.identifier.urihttps://hdl.handle.net/10023/14364
dc.descriptionMAJC and CKM gratefully acknowledge support of EPSRC grant no. EP/N014642/1 (EPSRC Centre for Multiscale Soft Tissue Mechanics – With Application to Heart & Cancer).en
dc.description.abstractIn this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of a three-gene repressilator is given) and an actual gene regulatory network, the NF- κB pathway. The second model is a force-based individual-based model of the development of a solid avascular tumour with specific application to tumour cords, i.e. a mass of cancer cells growing around a central blood vessel. In each case, we compare our computational simulation results with experimental data. In the final discussion section, we outline how to take the work forward through the development of a multiscale model focussed at the cell level. This would incorporate key intracellular signalling pathways associated with cancer within each cell (e.g. p53–Mdm2, NF- κB) and through the use of high-performance computing be capable of simulating up to 109 cells, i.e. the tissue scale. In this way, mathematical models at multiple scales would be combined to formulate a multiscale computational model.
dc.format.extent38
dc.format.extent7959646
dc.language.isoeng
dc.relation.ispartofBulletin of Mathematical Biologyen
dc.subjectMultiscale cancer modellingen
dc.subjectGene regulatory networken
dc.subjectSpatial stochastic modelen
dc.subjectIndividual based modelen
dc.subjectComputational simulationsen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subjectBDCen
dc.subjectR2Cen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subject.lccQA75en
dc.subject.lccQH301en
dc.titleComputational modelling of cancer development and growth : modelling at multiple scales and multiscale modellingen
dc.typeJournal articleen
dc.contributor.sponsorEPSRCen
dc.contributor.institutionUniversity of St Andrews. Applied Mathematicsen
dc.identifier.doi10.1007/s11538-017-0292-3
dc.description.statusPeer revieweden
dc.date.embargoedUntil2018-06-20
dc.identifier.grantnumberEP/N014642/1en


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