Kobayashi Koichi, Hiraishi Kunihiko
School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, Japan.
ScientificWorldJournal. 2014 Jan 23;2014:968341. doi: 10.1155/2014/968341. eCollection 2014.
One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs.
系统生物学中的一个重要课题是发展基因调控网络（GRN）的控制理论。在典型的GRN控制中，一些基因的表达通过操纵外部刺激和其他基因的表达来被抑制（激活）。预计未来将GRN的控制理论应用于基因治疗技术。本文研究了一种使用布尔网络（BN）的控制方法。BN被广泛用作GRN的模型，基因表达由二进制值（开或关）表示。特别地，使用了上下文敏感概率布尔网络（CS-PBN），它是BN的扩展模型之一。对于CS-PBN，考虑了验证问题和最优控制问题。对于验证问题，提出了一种使用概率模型检查器PRISM的解决方法。对于最优控制问题，提出了一种使用多项式优化的解决方法。最后，给出了一个与黑色素瘤相关的WNT5A网络的数值例子。所提出的方法为我们提供了GRN控制理论中的有用工具。
