Particle swarm optimization algorithm

Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm

X. N. Huang, Ren, H. P., Huang, X. N., and Ren, H. P., Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm, vol. 15, p. -, 2016.

Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices.

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