Analysis and reconstruction of genetic regulatory networks based on QPSO algorithm and S-system
基于QPSO算法和S-系统的基因调控网络分析与重构

This paper discussed the analysis and reconstruction of genetic regulatory network based on QPSO algorithm, defined the problem based on the S-system model as an estimation problem of the S-system parameter. Used the sum of squared errors between experimental values and predicted values as the objective optimization function in the basic method, but it could predict only a very small number of parameters and the convergence rate was low. Proposed the gradual optimization strategy based on QPSO algorithm with the sparsity of the genetic network. The optimization procedure became simper with the futile parameters gradually fixed. The dynamic of a small genetic network constructs with 60 parameters for 5 network variables is successfully inferred in experiments by the improved algorithm.