Employing decomposable partially observable Markov decision processes to control gene regulatory networks

The reported test results using both synthetic and real GRNs are promising in demonstrating the applicability, effectiveness and efficiency of the proposed approach. This is due to the fact that partial observability fits well to the problem of noisy acquisition of gene expression data as there are technological limitations to measure precisely exact expression levels of genes.