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https://hdl.handle.net/10356/84326
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sloot, Peter M. A. | en |
dc.contributor.author | Hoekstra, Alfons G. | en |
dc.date.accessioned | 2013-06-10T04:46:21Z | en |
dc.date.accessioned | 2019-12-06T15:42:48Z | - |
dc.date.available | 2013-06-10T04:46:21Z | en |
dc.date.available | 2019-12-06T15:42:48Z | - |
dc.date.copyright | 2009 | en |
dc.date.issued | 2009 | en |
dc.identifier.citation | Sloot, P. M. A., & Hoekstra, A. G. (2009). Multi-scale modelling in computational biomedicine. Briefings in Bioinformatics, 11(1), 142-152. | en |
dc.identifier.uri | https://hdl.handle.net/10356/84326 | - |
dc.description.abstract | The inherent complexity of biomedical systems is well recognized; they are multi-scale, multi-science systems, bridging a wide range of temporal and spatial scales. This article reviews the currently emerging field of multi-scale modelling in computational biomedicine. Many exciting multi-scale models exist or are under development. However, an underpinning multi-scale modelling methodology seems to be missing. We propose a direction that complements the classic dynamical systems approach and introduce two distinct case studies, transmission of resistance in human immunodeficiency virus spreading and in-stent restenosis in coronary artery disease. | en |
dc.language.iso | en | en |
dc.relation.ispartofseries | Briefings in bioinformatics | en |
dc.rights | © 2009 The Author. | en |
dc.title | Multi-scale modelling in computational biomedicine | en |
dc.type | Journal Article | en |
dc.contributor.school | School of Computer Engineering | en |
dc.identifier.doi | 10.1093/bib/bbp038 | en |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
Appears in Collections: | SCSE Journal Articles |
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