Application of Evolutionary Algorithms for the Optimization of Genetic Regulatory Networks

Rosati, Elise; Madec, Morgan; Rezgui, Abir; Colman, Quentin; Toussaint, Nicolas; Lallement, Christophe; Collet, Pierre

doi:10.1007/978-3-319-31204-0_13

Cited by 2 publications

(1 citation statement)

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“…This set has been chosen to have, for each regulation, a symmetric and stiff dose-response curve, which could be considered as the most favourable condition to insure the good operation of the complete system but the research of another set of default parameters that make the GRN more reliable would be a nice complementary analysis. Such analysis can be performed by running an optimisation algorithm similar to the one used in [ 52 ]. However, two main challenges have to be faced: finding an appropriate relevant and quantitative metric to evaluate each set of default parameters, on the one hand, and computation time, on the other hand.…”

Section: Discussionmentioning

confidence: 99%

Feasibility and reliability of sequential logic with gene regulatory networks

2021

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Gene regulatory networks exhibiting Boolean behaviour, e.g. AND, OR or XOR, have been routinely designed for years. However, achieving more sophisticated functions, such as control or computation, usually requires sequential circuits or so-called state machines. For such a circuit, outputs depend both on inputs and the current state of the system. Although it is still possible to design such circuits by analogy with digital electronics, some particularities of biology make the task trickier. The impact of two of them, namely the stochasticity of biological processes and the inhomogeneity in the response of regulation mechanisms, are assessed in this paper. Numerical simulations performed in two use cases point out high risks of malfunctions even for designed GRNs functional from a theoretical point of view. Several solutions to improve reliability of such systems are also discussed.

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Section: Discussionmentioning

confidence: 99%