標題: Robust synthetic biology design: stochastic game theory approach
作者: Chen, Bor-Sen
Chang, Chia-Hung
Lee, Hsiao-Ching
生物科技學系
Department of Biological Science and Technology
公開日期: 15-七月-2009
摘要: Motivation: Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. Results: A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method.
URI: http://dx.doi.org/10.1093/bioinformatics/btp310
http://hdl.handle.net/11536/6960
ISSN: 1367-4803
DOI: 10.1093/bioinformatics/btp310
期刊: BIOINFORMATICS
Volume: 25
Issue: 14
起始頁: 1822
結束頁: 1830
顯示於類別:期刊論文


文件中的檔案:

  1. 000267665900017.pdf