Comparing individual-based approaches to modelling the self-organization of multicellular tissues
The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by...
| প্রধান লেখক: | , , , , |
|---|---|
| বিন্যাস: | Journal article |
| ভাষা: | English |
| প্রকাশিত: |
Public Library of Science
2017
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| _version_ | 1826257301686714368 |
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| author | Osbourne, J Fletcher, A Pitt-Francis, J Maini, P Gavaghan, D |
| author_facet | Osbourne, J Fletcher, A Pitt-Francis, J Maini, P Gavaghan, D |
| author_sort | Osbourne, J |
| collection | OXFORD |
| description | The coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage. |
| first_indexed | 2024-03-06T18:16:00Z |
| format | Journal article |
| id | oxford-uuid:04a48848-101c-4616-aef1-9a163225dc59 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:16:00Z |
| publishDate | 2017 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:04a48848-101c-4616-aef1-9a163225dc592022-03-26T08:52:50ZComparing individual-based approaches to modelling the self-organization of multicellular tissuesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:04a48848-101c-4616-aef1-9a163225dc59EnglishSymplectic Elements at OxfordPublic Library of Science2017Osbourne, JFletcher, APitt-Francis, JMaini, PGavaghan, DThe coordinated behaviour of populations of cells plays a central role in tissue growth and renewal. Cells react to their microenvironment by modulating processes such as movement, growth and proliferation, and signalling. Alongside experimental studies, computational models offer a useful means by which to investigate these processes. To this end a variety of cell-based modelling approaches have been developed, ranging from lattice-based cellular automata to lattice-free models that treat cells as point-like particles or extended shapes. However, it remains unclear how these approaches compare when applied to the same biological problem, and what differences in behaviour are due to different model assumptions and abstractions. Here, we exploit the availability of an implementation of five popular cell-based modelling approaches within a consistent computational framework, Chaste (http://www.cs.ox.ac.uk/chaste). This framework allows one to easily change constitutive assumptions within these models. In each case we provide full details of all technical aspects of our model implementations. We compare model implementations using four case studies, chosen to reflect the key cellular processes of proliferation, adhesion, and short- and long-range signalling. These case studies demonstrate the applicability of each model and provide a guide for model usage. |
| spellingShingle | Osbourne, J Fletcher, A Pitt-Francis, J Maini, P Gavaghan, D Comparing individual-based approaches to modelling the self-organization of multicellular tissues |
| title | Comparing individual-based approaches to modelling the self-organization of multicellular tissues |
| title_full | Comparing individual-based approaches to modelling the self-organization of multicellular tissues |
| title_fullStr | Comparing individual-based approaches to modelling the self-organization of multicellular tissues |
| title_full_unstemmed | Comparing individual-based approaches to modelling the self-organization of multicellular tissues |
| title_short | Comparing individual-based approaches to modelling the self-organization of multicellular tissues |
| title_sort | comparing individual based approaches to modelling the self organization of multicellular tissues |
| work_keys_str_mv | AT osbournej comparingindividualbasedapproachestomodellingtheselforganizationofmulticellulartissues AT fletchera comparingindividualbasedapproachestomodellingtheselforganizationofmulticellulartissues AT pittfrancisj comparingindividualbasedapproachestomodellingtheselforganizationofmulticellulartissues AT mainip comparingindividualbasedapproachestomodellingtheselforganizationofmulticellulartissues AT gavaghand comparingindividualbasedapproachestomodellingtheselforganizationofmulticellulartissues |