Detalle de: A non-linear analysis of Turing pattern formation
| Title | A non-linear analysis of Turing pattern formation |
| Abstract |
Reaction-diffusion schemes are widely used to model and interpret phenomena in various fields. In that context, phenomena driven by Turing instabilities are particularly relevant to describe patterning in a number of biological processes. While the conditions that determine the appearance of Turing patterns and their wavelength can be easily obtained by a linear stability analysis, the estimation of pattern amplitudes requires cumbersome calculations due to non-linear terms. Here we introduce an expansion method that makes possible to obtain analytical, approximated, solutions of the pattern amplitudes. We check and illustrate the reliability of this methodology with results obtained from numerical simulations. |
| Apa Reference | Chen, Y., & Buceta, J. (2019). A non-linear analysis of Turing pattern formation. PLOS ONE, 14(8), e0220994. 10.1371/journal.pone.0220994 |
| Doi | 10.1371/journal.pone.0220994 |
| Publication Date | 9 Aug 2019 |
| Publication Type | Article |
| Researcher | Javier Buceta |
| Ontology | Computational models and simulations |
| Research Groups | TheSiMBioSys (Theoretical and In Silico Modeling of Biological Systems) |
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