In the post-genomic era, the construction and control of genetic regulatory networks using gene expression data is a hot research topic. Boolean networks (BNs) and its extension Probabilistic Boolean Networks (PBNs) h...In the post-genomic era, the construction and control of genetic regulatory networks using gene expression data is a hot research topic. Boolean networks (BNs) and its extension Probabilistic Boolean Networks (PBNs) have been served as an effective tool for this purpose. However, PBNs are difficult to be used in practice when the number of genes is large because of the huge computational cost. In this paper, we propose a simplified multivariate Markov model for approximating a PBN The new model can preserve the strength of PBNs, the ability to capture the inter-dependence of the genes in the network, qnd at the same time reduce the complexity of the network and therefore the computational cost. We then present an optimal control model with hard constraints for the purpose of control/intervention of a genetic regulatory network. Numerical experimental examples based on the yeast data are given to demonstrate the effectiveness of our proposed model and control policy.展开更多
We aim to further study the global stability of Boolean control networks(BCNs)under aperiodic sampleddata control(ASDC).According to our previous work,it is known that a BCN under ASDC can be transformed into a switch...We aim to further study the global stability of Boolean control networks(BCNs)under aperiodic sampleddata control(ASDC).According to our previous work,it is known that a BCN under ASDC can be transformed into a switched Boolean network(SBN),and further global stability of the BCN under ASDC can be obtained by studying the global stability of the transformed SBN.Unfortunately,since the major idea of our previous work is to use stable subsystems to offset the state divergence caused by unstable subsystems,the SBN considered has at least one stable subsystem.The central thought in this paper is that switching behavior also has good stabilization;i.e.,the SBN can also be stable with appropriate switching laws designed,even if all subsystems are unstable.This is completely different from that in our previous work.Specifically,for this case,the dwell time(DT)should be limited within a pair of upper and lower bounds.By means of the discretized Lyapunov function and DT,a sufficient condition for global stability is obtained.Finally,the above results are demonstrated by a biological example.展开更多
We study the Markov decision processes under the average-value-at-risk criterion.The state space and the action space are Borel spaces,the costs are admitted to be unbounded from above,and the discount factors are sta...We study the Markov decision processes under the average-value-at-risk criterion.The state space and the action space are Borel spaces,the costs are admitted to be unbounded from above,and the discount factors are state-action dependent.Under suitable conditions,we establish the existence of optimal deterministic stationary policies.Furthermore,we apply our main results to a cash-balance model.展开更多
文摘In the post-genomic era, the construction and control of genetic regulatory networks using gene expression data is a hot research topic. Boolean networks (BNs) and its extension Probabilistic Boolean Networks (PBNs) have been served as an effective tool for this purpose. However, PBNs are difficult to be used in practice when the number of genes is large because of the huge computational cost. In this paper, we propose a simplified multivariate Markov model for approximating a PBN The new model can preserve the strength of PBNs, the ability to capture the inter-dependence of the genes in the network, qnd at the same time reduce the complexity of the network and therefore the computational cost. We then present an optimal control model with hard constraints for the purpose of control/intervention of a genetic regulatory network. Numerical experimental examples based on the yeast data are given to demonstrate the effectiveness of our proposed model and control policy.
基金Project supported by the Natural Science Foundation of Jiangsu Province,China(No.BK20170019)the Fundamental Research Funds for the Central Universities+2 种基金the National Natural Science Foundation of China(Nos.61973078,61573102,and 11671158)Hong Kong RGC GRF,China(No.17301519)IMR and RAE Research Fund from Faculty of Science,HKU,China。
文摘We aim to further study the global stability of Boolean control networks(BCNs)under aperiodic sampleddata control(ASDC).According to our previous work,it is known that a BCN under ASDC can be transformed into a switched Boolean network(SBN),and further global stability of the BCN under ASDC can be obtained by studying the global stability of the transformed SBN.Unfortunately,since the major idea of our previous work is to use stable subsystems to offset the state divergence caused by unstable subsystems,the SBN considered has at least one stable subsystem.The central thought in this paper is that switching behavior also has good stabilization;i.e.,the SBN can also be stable with appropriate switching laws designed,even if all subsystems are unstable.This is completely different from that in our previous work.Specifically,for this case,the dwell time(DT)should be limited within a pair of upper and lower bounds.By means of the discretized Lyapunov function and DT,a sufficient condition for global stability is obtained.Finally,the above results are demonstrated by a biological example.
基金supported in part by HKRGC GrantHKU Strategic Theme Grant on Computational SciencesNational Natural Science Foundation of China under Grant Nos.10971075 and 11271144
基金supported by the National Natural Science Foundation of China(Grant Nos.61673019,11931018)the Natural Science Foundation of Guangdong Province(Grant Nos.2018A030313738,2021A1515010057)+1 种基金Guangdong Province Key Laboratory of Computational Science at the Sun Yat-sen University(2020B1212060032)IMR and RAE Research Fund,Faculty of Science,HKU.
文摘We study the Markov decision processes under the average-value-at-risk criterion.The state space and the action space are Borel spaces,the costs are admitted to be unbounded from above,and the discount factors are state-action dependent.Under suitable conditions,we establish the existence of optimal deterministic stationary policies.Furthermore,we apply our main results to a cash-balance model.
