Novel structure learning method for constructing gene regulatory network
一种新颖的基因调控网络结构学习方法

Structure learning of Bayesian network is a NP hard problem. A structure learning method without an ordering requirement based on novel Particle Swarm Optimization (PSO) was proposed. In this method, the structures were represented by particles, and updated according to swarm intelligence of PSO. Then the net structures were modified with mutual information. Finally the K2 algorithm was applied with the global best particle as the ordering and updating the best particle for next generation. Experimental results demonstrate that the performance of this new strategy is better than that of K2 and BN-PSO, especially it has higher convergence rate and better Bayesian score without a previous ordering.