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oapen-20.500.12657-429342020-11-14T01:47:17Z Modeling Excitable Tissue Tveito, Aslak Mardal, Kent-Andre Rognes, Marie E. Mathematical and Computational Biology Applications of Mathematics Mathematical Modeling and Industrial Mathematics applied mathematics scientific computing computational physiology finite element methods cardiac modelling biomechanics numerical methods preconditioning open access Maths for scientists Mathematical modelling Maths for engineers bic Book Industry Communication::P Mathematics & science::PD Science: general issues::PDE Maths for scientists bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBW Applied mathematics bic Book Industry Communication::P Mathematics & science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling This open access volume presents a novel computational framework for understanding how collections of excitable cells work. The key approach in the text is to model excitable tissue by representing the individual cells constituting the tissue. This is in stark contrast to the common approach where homogenization is used to develop models where the cells are not explicitly present. The approach allows for very detailed analysis of small collections of excitable cells, but computational challenges limit the applicability in the presence of large collections of cells. 2020-11-13T13:36:02Z 2020-11-13T13:36:02Z 2021 book ONIX_20201113_9783030611576_40 https://library.oapen.org/handle/20.500.12657/42934 eng Simula SpringerBriefs on Computing; Reports on Computational Physiology application/pdf n/a 2021_Book_ModelingExcitableTissue.pdf https://www.springer.com/9783030611576 Springer Nature Springer International Publishing 10.1007/978-3-030-61157-6 10.1007/978-3-030-61157-6 6c6992af-b843-4f46-859c-f6e9998e40d5 Springer International Publishing 7 100 open access
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OAPEN
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English
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This open access volume presents a novel computational framework for understanding how collections of excitable cells work. The key approach in the text is to model excitable tissue by representing the individual cells constituting the tissue. This is in stark contrast to the common approach where homogenization is used to develop models where the cells are not explicitly present. The approach allows for very detailed analysis of small collections of excitable cells, but computational challenges limit the applicability in the presence of large collections of cells.
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title |
2021_Book_ModelingExcitableTissue.pdf
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2021_Book_ModelingExcitableTissue.pdf
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title_short |
2021_Book_ModelingExcitableTissue.pdf
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title_full |
2021_Book_ModelingExcitableTissue.pdf
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title_fullStr |
2021_Book_ModelingExcitableTissue.pdf
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title_full_unstemmed |
2021_Book_ModelingExcitableTissue.pdf
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title_sort |
2021_book_modelingexcitabletissue.pdf
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publisher |
Springer Nature
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publishDate |
2020
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https://www.springer.com/9783030611576
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1771297530776125440
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