Modern perspectives on near-equilibrium analysis of Turing systems
In the nearly seven decades since the publication of Alan Turing’s work on morphogenesis, enormous progress has been made in understanding both the mathematical and biological aspects of his proposed reaction–diffusion theory. Some of these developments were nascent in Turing’s paper, and others hav...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Royal Society
2021
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| _version_ | 1797083972078927872 |
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| author | Krause, AL Gaffney, EA Maini, PK Klika, V |
| author_facet | Krause, AL Gaffney, EA Maini, PK Klika, V |
| author_sort | Krause, AL |
| collection | OXFORD |
| description | In the nearly seven decades since the publication of Alan Turing’s work on morphogenesis, enormous progress has been made in understanding both the mathematical and biological aspects of his proposed reaction–diffusion theory. Some of these developments were nascent in Turing’s paper, and others have been due to new insights from modern mathematical techniques, advances in numerical simulations and extensive biological experiments. Despite such progress, there are still important gaps between theory and experiment, with many examples of biological patterning where the underlying mechanisms are still unclear. Here, we review modern developments in the mathematical theory pioneered by Turing, showing how his approach has been generalized to a range of settings beyond the classical two-species reaction–diffusion framework, including evolving and complex manifolds, systems heterogeneous in space and time, and more general reaction-transport equations. While substantial progress has been made in understanding these more complicated models, there are many remaining challenges that we highlight throughout. We focus on the mathematical theory, and in particular linear stability analysis of ‘trivial’ base states. We emphasize important open questions in developing this theory further, and discuss obstacles in using these techniques to understand biological reality. |
| first_indexed | 2024-03-07T01:49:07Z |
| format | Journal article |
| id | oxford-uuid:997549dc-cbb9-488a-9af4-9474e4555e15 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T01:49:07Z |
| publishDate | 2021 |
| publisher | Royal Society |
| record_format | dspace |
| spelling | oxford-uuid:997549dc-cbb9-488a-9af4-9474e4555e152022-03-27T00:14:31ZModern perspectives on near-equilibrium analysis of Turing systemsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:997549dc-cbb9-488a-9af4-9474e4555e15EnglishSymplectic ElementsRoyal Society2021Krause, ALGaffney, EAMaini, PKKlika, VIn the nearly seven decades since the publication of Alan Turing’s work on morphogenesis, enormous progress has been made in understanding both the mathematical and biological aspects of his proposed reaction–diffusion theory. Some of these developments were nascent in Turing’s paper, and others have been due to new insights from modern mathematical techniques, advances in numerical simulations and extensive biological experiments. Despite such progress, there are still important gaps between theory and experiment, with many examples of biological patterning where the underlying mechanisms are still unclear. Here, we review modern developments in the mathematical theory pioneered by Turing, showing how his approach has been generalized to a range of settings beyond the classical two-species reaction–diffusion framework, including evolving and complex manifolds, systems heterogeneous in space and time, and more general reaction-transport equations. While substantial progress has been made in understanding these more complicated models, there are many remaining challenges that we highlight throughout. We focus on the mathematical theory, and in particular linear stability analysis of ‘trivial’ base states. We emphasize important open questions in developing this theory further, and discuss obstacles in using these techniques to understand biological reality. |
| spellingShingle | Krause, AL Gaffney, EA Maini, PK Klika, V Modern perspectives on near-equilibrium analysis of Turing systems |
| title | Modern perspectives on near-equilibrium analysis of Turing systems |
| title_full | Modern perspectives on near-equilibrium analysis of Turing systems |
| title_fullStr | Modern perspectives on near-equilibrium analysis of Turing systems |
| title_full_unstemmed | Modern perspectives on near-equilibrium analysis of Turing systems |
| title_short | Modern perspectives on near-equilibrium analysis of Turing systems |
| title_sort | modern perspectives on near equilibrium analysis of turing systems |
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