Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
Proceedings of the European Conference on Genetic Programming
On Learning Gene Regulatory Networks Under the Boolean Network Model
Machine Learning
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
A novel strategy for plant breeding based on simulations of gene network models
International Journal of Bioinformatics Research and Applications
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This paper presents a hybrid algorithm based on Genetic Programming (GP) and Particle Swarm Optimisation (PSO) for the automated recovery of gene network structure. It uses gene expression time series data as well as phenotypic data pertaining to plant flowering time as its input data. The algorithm then attempts to discover simple structures to approximate the plant gene regulatory networks that produce model gene expressions and flowering times that closely resemble the input data. To show the efficacy of the proposed approach, simulation results applied to flowering time control in Arabidopsis thaliana are demonstrated and discussed.