Finite-Horizon Control of Genetic Regulatory Networks with Multiple Hard-Constraints

摘要：

Probabilistic Boolean Networks (PBNs) provide a convenient tool for studying the interactions among different genes while allowing uncertainty. This paper deals with the issue of finite-horizon control with multiple hard-constraints in a PBN. More precisely, under the constraint of the number of times that each control method can be applied, we develop a control strategy by which the state of a given genetic network falls into a desired state set with a prescribed minimum probability. We propose an efficient algorithm to find the feasible solutions. An upper bound for the computational cost is also given. An numerical experiment is then conducted to demonstrate the efficiency of our proposed method.

关键词： Probability Boolean Networks Finite-Horizon Multiple Hard-Constraints Intervention Markov Chain Optimal Control

作者: Wai-Ki Ching Yang Cong

作者单位: Advanced Modeling and Applied Computing Laboratory,Department of Mathematics,The University of Hong Kong,Hong Kong

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 33-40

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）