Computer Science ›› 2017, Vol. 44 ›› Issue (5): 193-198.doi: 10.11896/j.issn.1002-137X.2017.05.035

Previous Articles     Next Articles

Optimal Control of Probabilistic Boolean Networks Using Model Checking

GUO Zong-hao and WEI Ou   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Systems biology expected to construct a realistic and computational model of complex biology systems that aims at system-level understanding of biological systems.One of the significant topics in the field of system biology is that the control theory of gene regulatory networks (GRNs) is developed by applying external intervention control for gene theory technologies in the future.At present,Boolean networks and extended probabilistic Boolean networks have been used as the model of GRNs widely.In the research of control problem,the state transition of probabilistic Boolean control networks essentially forms a finite-state and discrete-time Markov decision processes (MDP).According to MDP theory,finite-horizon optimal control problem and infinite-horizon optimal control problem can be solved by using probabilistic model checking.For content-sensitive probabilistic Boolean control networks with random perturbation,probabilistic model checker PRISM is used to model formally.Then two kinds of optimal control problems are expressed by temporal logic.Finally,the optimal solution is found via model checking.The results indicate that this proposed approach can be used for analysis and optimal control of biology networks effectively.

Key words: Gene regulatory networks,Probabilistic Boolean network,Optimal control,Probabilistic model checking

[1] LI P,ZHANG C,PERKINS E J,et al.Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks[J].BMC Bioinformatics,2007,8(1):S13.
[2] STEGGLES L J,BANKS R,SHAW O,et al.Qualitatively mo-delling and analysing genetic regulatory networks:a Petri net approach[J].Bioinformatics,2007,23(3):336-343.
[3] KOBAYASHI K,HIRAISHI K.Optimal control of gene regulatory networks with effectiveness of multiple drugs:a Boolean network approach[J].Biomed Research International,2013,2013(23):10233-10240.
[4] SHMULEVICH I,DOUGHERTY E R,KIM S,et al.Probabilistic Boolean Networks:a rule-based uncertainty model for gene regulatory networks[J].Bioinformatics,2002,18(2):261-274.
[5] CHING W K,ZHANG S Q,JIAO Y,et al.Optimal finite-horizon control for probabilistic Boolean networks with hard constraints[C]∥International Symposium on Optimization & Systems Biology.Beijing,China,2007:21-28.
[6] PAL R,DATTA A,DOUGHERTY E R.Optimal infinite-horizon control for probabilistic Boolean networks[J].IEEE Tran-sactions on Signal Processing,2006,54(6):2375-2387.
[7] CIESINSK F,GRβER M.On Probabilistic Computation Tree Logic[M]∥Validation of Stochastic Systems.Berlin Heidelberg:Springer,2004:147-188.
[8] ZHANG H,WANG X,LIN X.Synchronization of Boolean Networks with Different Update Schemes[J].IEEE/ACM Transactions on Computational Biology & Bioinformatics,2014,11(5):965-972.
[9] ZHU P,HAN J.Asynchronous stochastic Boolean networks as gene network models[J].Journal of Computational Biology,2014,21(10):771-783.
[10] FARYABI B,VAHEDI G,CHAMBERLAND J F,et al.Intervention in Context-Sensitive Probabilistic Boolean Networks Revisited[J].Eurasip Journal on Bioinformatics & Systems Biology,2009,2009(1):1-13.
[11] SHMULEVICH I,DOUGHERTY E R,ZHANG W.Gene perturbation and interventionin probabilistic Boolean networks[J].Bioinformatics,2002,8(10):1319-1331.
[13] KWIATKOWSKA M,NORMAN G,PARKER D.StochasticModel Checking[M].REMKE A,STOELINGA M,eds.Berlin Heidelberg:Springer,2014.
[14] DATTA A,CHOUDHARY A,BITTNER M L,et al.External Control in Markovian Genetic Regulatory Networks[J].Journal of Chemical Physics,2003,109(11):4569-4575.
[15] TOURNIER L,CHAVES M.Uncovering operational interac-tions in genetic networks using asynchronous boolean dynamics[J].Journal of Theoretical Biology,2009,260(2):196-209.
[17] FENG J,YAO J,PENG C.Singular Boolean networks:Semi-tensor product approach[J].Science China(Information Scien-ces),2013,56(11):1-14.
[19] KOBAYASHI K,HIRAISHI K.Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization[J].The Scientific World Journal,2014,2014(2):295-318.
[20] LIU Q,GUO X,ZHOU T.Optimal control for probabilisticBoolean networks[J].IET Systems Biology,2010,4(2):99-107.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!