Robust synthetic biology design: stochastic game theory approach.
Robust synthetic biology design: stochastic game theory approach.
复制标题
DOI：
10.1093/bioinformatics/btp310
复制
发表时间：
2009-07-15
期刊：
影响因子：
--
通讯作者：
Lee HC
中科院分区：
文献类型：
--
作者：
Chen BS;Chang CH;Lee HC
动机：合成生物学是设计人工生物系统来研究自然生物现象和各种应用。然而，合成基因网络的发展仍然是困难的，大多数新创建的基因网络是不起作用的，由于不确定的初始条件和干扰的细胞外环境的宿主细胞。目前，如何设计一个健壮的合成基因网络，使其在这些不确定因素下正常工作，是合成生物学研究的重要课题。结果如下：针对随机合成基因网络，从极小极大调控的角度提出了一种鲁棒调控设计，使其在这些不确定因素下达到预定的稳态。这个极小极大管制设计问题可以转化为一个等价的随机对策问题。针对合成基因网络鲁棒调控设计问题难以直接用非线性随机博弈方法求解的问题，利用Matlab中的鲁棒控制算法，通过线性矩阵不等式（LMI）技术，提出了Takagi-Sugeno（T-S）模糊模型来逼近非线性合成基因网络.最后，通过一个计算机模拟的例子来说明设计过程，并证实所提出的鲁棒基因设计方法的效率和功效。可用性：http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf联系：bschen@ee.nthu.edu.tw补充信息：补充数据可在生物信息学在线。
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. Availability: http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf Contact: bschen@ee.nthu.edu.tw Supplementary information: Supplementary data are available at Bioinformatics online.
登录
查看更多内容
影响因子：
--
作者：
Kaznessis, Yiannis N.
通讯作者：
Kaznessis, Yiannis N.
DOI：
10.1073/pnas.0408507102
发表时间：
2005-03-08
影响因子：
11.1
作者：
Hooshangi, S;Thiberge, S;Weiss, R
通讯作者：
Weiss, R
影响因子：
46.9
作者：
Canton, Barry;Labno, Anna;Endy, Drew
通讯作者：
Endy, Drew
影响因子：
4.3
作者：
Chen, Bor-Sen;Wu, Wei-Sheng
通讯作者：
Wu, Wei-Sheng
影响因子：
2
作者：
Chen, Bor-Sen;Chang, Chia-Hung;Chuang, Yung-Jen
通讯作者：
Chuang, Yung-Jen