Abstract: The phenotype of the crops can be predicted through the gene regulatory network (GRN) , which is important for the global food security. This paper proposed a Cartesian genetic programming and linear decreasing inertia weight particle swarm optimization algorithm for GRN modeling. To verify the effectiveness of the proposed algorithm,we applied it to the recovery of the Arabidopsis flowering time control system. The computer simulation indicates that our proposed algorithm is able to infer the GRN model which can predict the phenotype of the crops fairly accurately based on its genotype and environmental conditions.

Key words: Flowering time control in arabidopsis, Gene regulatory network, Genetic programming, Particle swarm optimization, CGP-WPSO hybrid algorithm