2020
DOI: 10.3934/dcds.2020170
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Hysteresis-driven pattern formation in reaction-diffusion-ODE systems

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Cited by 24 publications
(26 citation statements)
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“…Therefore, we phenomenologically summarize HyWnt3 inhibition by a diffusive HyWnt3 inhibitor possibly including Sp5 and HmTSP. Similar dynamics may result from multistability in the intracellular signaling [73][74][75], or a negative feedback loop stemming from mechano-chemical interactions [66,76]. The reduced mathematical representation of the underlying mechanisms is sufficient for the purpose of this paper, since we focus on the role of HAS-7 in the pattern formation process.…”
Section: Mathematical Modelmentioning
confidence: 99%
“…Therefore, we phenomenologically summarize HyWnt3 inhibition by a diffusive HyWnt3 inhibitor possibly including Sp5 and HmTSP. Similar dynamics may result from multistability in the intracellular signaling [73][74][75], or a negative feedback loop stemming from mechano-chemical interactions [66,76]. The reduced mathematical representation of the underlying mechanisms is sufficient for the purpose of this paper, since we focus on the role of HAS-7 in the pattern formation process.…”
Section: Mathematical Modelmentioning
confidence: 99%
“…If the system exhibits Turing instability, the same mechanism which destabilizes the spatially homogeneous steady state also induces instability of all close-to-equilibrium patterns in the limit system [23,24,49,50]. The underlying loss of compactness results in emergence of a larger class of stationary patterns that may exhibit spatial irregularity not observed in the model with a small but strictly positive diffusion [24,25]. Consequently, the pattern selection process changes significantly.…”
Section: Far-from-equilibrium Patternsmentioning
confidence: 99%
“…This is to highlight the methodology, rather than the specific modelling context. Indeed, a pattern forming process as described here, can take place in a wide variety of models including systems of reaction–diffusion equations [20], non-local models of integro-differential equations [21,22], degenerated reaction–diffusion-ODE systems [2325] or fourth-order partial differential equation models accounting for evolution of thin elastic structures [17,26]. Hence, it seems useful to adapt a rather abstract approach and describe the system as the evolution of a state variable ufalse(x,tfalse)double-struckRn determined by the evolution equation Δtu=Ffalse[ufalse], where the functional F encodes the evolution rules.…”
Section: Introductionmentioning
confidence: 99%
“…for x ∈ [0, 1], supplemented with homogeneous Neumann boundary condition for u was introduced in [18] in order to understand the role of bistability and hysteresis in pattern formation (see also [12] for more comments). We refer the reader to [13] for a construction of stable discontinuous stationary solutions of the one dimensional problem (1.7). Here, in Section 7, we apply the general theory from this work to extend results from [13] on the N-dimensional version of model (1.7).…”
Section: Introductionmentioning
confidence: 99%