This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational c...This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing the number of species in a gene regulation system. An estimate is derived for the confidence level of the predicted minimum required perturbation strength when targets are prescribed a priori. The algorithm has been used to analyze the cell cycle of Xenopus frog eggs. The results agree well with available results for single target perturbations, and multitarget interference is usually not equal to the summation of the single-target interferences.展开更多
基金Supported in part by the Basic Research Foundation of Tsinghua National Laboratory for Information Science and Technology (TNList)the National Natural Science Foundation of China (Nos. 60625305 and 60574008)the National High-Tech Research and Development (863) Program of China (No. 2006AA2Z311)
文摘This paper presents an algorithm for identifying desirable multiple targets in an intracellular regulation network. The algorithm is based on constrained state feedback and Monte-Carlo simulations. The computational complexity of the algorithm increases linearly with increasing the number of species in a gene regulation system. An estimate is derived for the confidence level of the predicted minimum required perturbation strength when targets are prescribed a priori. The algorithm has been used to analyze the cell cycle of Xenopus frog eggs. The results agree well with available results for single target perturbations, and multitarget interference is usually not equal to the summation of the single-target interferences.
