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Bespoke Turing systems

Abstract:
Reaction–diffusion systems are an intensively studied form of partial differential equation, frequently used to produce spatially heterogeneous patterned states from homogeneous symmetry breaking via the Turing instability. Although there are many prototypical “Turing systems” available, determining their parameters, functional forms, and general appropriateness for a given application is often difficult. Here, we consider the reverse problem. Namely, suppose we know the parameter region associated with the reaction kinetics in which patterning is required—we present a constructive framework for identifying systems that will exhibit the Turing instability within this region, whilst in addition often allowing selection of desired patterning features, such as spots, or stripes. In particular, we show how to build a system of two populations governed by polynomial morphogen kinetics such that the: patterning parameter domain (in any spatial dimension), morphogen phases (in any spatial dimension), and even type of resulting pattern (in up to two spatial dimensions) can all be determined. Finally, by employing spatial and temporal heterogeneity, we demonstrate that mixed mode patterns (spots, stripes, and complex prepatterns) are also possible, allowing one to build arbitrarily complicated patterning landscapes. Such a framework can be employed pedagogically, or in a variety of contemporary applications in designing synthetic chemical and biological patterning systems. We also discuss the implications that this freedom of design has on using reaction–diffusion systems in biological modelling and suggest that stronger constraints are needed when linking theory and experiment, as many simple patterns can be easily generated given freedom to choose reaction kinetics.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s11538-021-00870-y

Authors


More by this author
Role:
Author
ORCID:
0000-0001-6225-5365
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Oxford college:
St Anne's College
Role:
Author
ORCID:
0000-0001-9638-7278


Publisher:
Springer
Journal:
Bulletin of Mathematical Biology More from this journal
Volume:
83
Issue:
5
Article number:
41
Publication date:
2021-03-19
Acceptance date:
2021-02-11
DOI:
EISSN:
1522-9602
ISSN:
0092-8240
Pmid:
33740210


Language:
English
Keywords:
Pubs id:
1170344
Local pid:
pubs:1170344
Deposit date:
2021-05-10

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