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Semidefinite programming for Turing instability analysis in molecular communication networks | IEEE Conference Publication | IEEE Xplore

Semidefinite programming for Turing instability analysis in molecular communication networks


Abstract:

This paper proposes a computationally tractable algebraic condition for Turing instability, a type of local instability inducing self-organized spatial pattern formation,...Show More

Abstract:

This paper proposes a computationally tractable algebraic condition for Turing instability, a type of local instability inducing self-organized spatial pattern formation, in molecular communication networks. The molecular communication networks consist of spatially distributed homogeneous compartments, or biological cells, that interact with neighbor compartments using a small number of diffusible chemical species. Thus, the underlying spatio-temporal dynamics of the system can be modeled by reaction-diffusion equations whose diffusion terms are zero for some chemical species. We show that the molecular communication networks are not Turing unstable if and only if certain polynomials are non-negative. This leads to sum-of-squares optimizations for Turing instability analysis. The proposed approach is capable of predicting the formation of spatial patterns in molecular communication networks based on the mathematically rigorous analysis of Turing instability.
Date of Conference: 11-13 December 2019
Date Added to IEEE Xplore: 12 March 2020
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Conference Location: Nice, France

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