Key features of turing systems are determined purely by network topology
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Diego, Xavier
- dc.contributor.author Marcon, Luciano, 1983-
- dc.contributor.author Müller, Patrick
- dc.contributor.author Sharpe, James
- dc.date.accessioned 2019-12-03T07:57:52Z
- dc.date.available 2019-12-03T07:57:52Z
- dc.date.issued 2018
- dc.description.abstract Turing’s theory of pattern formation is a universal model for self-organization, applicable to many systems in physics, chemistry, and biology. Essential properties of a Turing system, such as the conditions for the existence of patterns and the mechanisms of pattern selection, are well understood in small networks. However, a general set of rules explaining how network topology determines fundamental system properties and constraints has not been found. Here we provide a first general theory of Turing network topology, which proves why three key features of a Turing system are directly determined by the topology: the type of restrictions that apply to the diffusion rates, the robustness of the system, and the phase relations of the molecular species.
- dc.description.sponsorship This research was supported by the ERC advanced grant SIMBIONT (670555) and the Ministerio de Economía y Competitividad (through Centro de Excelencia Severo Ochoa 2013-2017, SEV-2012-0208). X. D. acknowledges support by the ERC-FP7 Grant Swarmorgan (601062). J. S. ackowledges support from ICREA. P. M. and L. M. were supported by ERC Starting Grant QUANTPATTERN (637840).
- dc.format.mimetype application/pdf
- dc.identifier.citation Diego X, Marcon L, Müller P, Sharpe J. Key features of turing systems are determined purely by network topology. Phys Rev X. 2018;8(2):021071. DOI: 10.1103/PhysRevX.8.021071
- dc.identifier.doi http://dx.doi.org/10.1103/PhysRevX.8.021071
- dc.identifier.issn 2160-3308
- dc.identifier.uri http://hdl.handle.net/10230/43059
- dc.language.iso eng
- dc.publisher American Physical Society
- dc.relation.ispartof Physical Review X. 2018;8(2):021071
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/670555
- dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/601062
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/637840
- dc.rights © Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/). Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Biological physics complex systems
- dc.subject.keyword Nonlinear dynamics
- dc.title Key features of turing systems are determined purely by network topology
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion