DocumentCode :
1647836
Title :
Multi-Target Identification in Intracellular Regulation Networks
Author :
Tong, Zhou ; Shao, Li
Author_Institution :
Tsinghua Univ., Beijing
fYear :
2007
Firstpage :
112
Lastpage :
116
Abstract :
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.
Keywords :
Monte Carlo methods; biology computing; cellular biophysics; computational complexity; genetics; state feedback; Monte-Carlo simulation; computational complexity; constrained state feedback; gene regulation system; intracellular regulation network; multitarget identification; perturbation strength; Automation; Biomedical imaging; Computational complexity; Diseases; Drugs; Interference; Nonlinear dynamical systems; Pharmaceutical technology; State feedback; Systematics; Cell cycle; Constrained state feedback; Drug discovery; Intracellular regulation network; Monte Carlo method; Uniform distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
Type :
conf
DOI :
10.1109/CHICC.2006.4347194
Filename :
4347194
Link To Document :
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