Multi-Target Identification in Intracellular Regulation Networks

In this paper, an algorithm is proposed for identifying desirable multi-targets in an intracellular regulation network. The major ideas are based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing species number in a gene regulation system. An estimate is derived for the confidence level of the predicted minimal required perturbation strength when targets are prescribed a priori. The algorithm has been applied to the analysis of the cell cycle of Xenopus frog eggs. It is found that the analysis results agree well with the available results for single target perturbations, and multi-target interference is usually not equal to the summation of single-target interferences.