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Stability analysis of Boolean networks with Markov jump disturbances and their application in apoptosis networks


  • Received: 13 May 2022 Revised: 23 June 2022 Accepted: 28 June 2022 Published: 20 July 2022
  • In this paper, the finite-time stability (FTS) of switched Boolean networks (SBNs) with Markov jump disturbances under the conditions of arbitrary switching signals is studied. By using the tool of the semi-tensor product, the equivalent linear-like form of SBNs with Markov jump disturbances is first established. Next, to facilitate investigation, we convert the addressed system into an augmented Markov jump Boolean network (MJBN), and propose the definition of the switching set reachability of MJBNs. A necessary and sufficient criterion is developed for the FTS of SBNs with Markov jump disturbances under the conditions of arbitrary switching signals. Finally, we give two examples to illustrate the effectiveness of our work.

    Citation: Hankang Ji, Yuanyuan Li, Xueying Ding, Jianquan Lu. Stability analysis of Boolean networks with Markov jump disturbances and their application in apoptosis networks[J]. Electronic Research Archive, 2022, 30(9): 3422-3434. doi: 10.3934/era.2022174

    Related Papers:

  • In this paper, the finite-time stability (FTS) of switched Boolean networks (SBNs) with Markov jump disturbances under the conditions of arbitrary switching signals is studied. By using the tool of the semi-tensor product, the equivalent linear-like form of SBNs with Markov jump disturbances is first established. Next, to facilitate investigation, we convert the addressed system into an augmented Markov jump Boolean network (MJBN), and propose the definition of the switching set reachability of MJBNs. A necessary and sufficient criterion is developed for the FTS of SBNs with Markov jump disturbances under the conditions of arbitrary switching signals. Finally, we give two examples to illustrate the effectiveness of our work.



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    [1] A. M. Martínez-Rodríguez, J. H. May, L. G. Vargas, An optimization-based approach for the design of Bayesian networks, Math. Comput. Modell., 48 (2008), 1265-1278. https://doi.org/10.1016/j.mcm.2008.01.007 doi: 10.1016/j.mcm.2008.01.007
    [2] G. Karlebach, R. Shamir, Modelling and analysis of gene regulatory networks, Nat. Rev. Mol. Cell Biol., 9 (2008), 770-780. https://doi.org/10.1038/nrm2503 doi: 10.1038/nrm2503
    [3] I. Shmulevich, E. R. Dougherty, S. Kim, W. Zhang, Probabilistic Boolean networks: A rule-based uncertainty model for gene regulatory networks, Bioinformatics, 18 (2002), 261-274. https://doi.org/10.1002/9783527622818.ch8 doi: 10.1002/9783527622818.ch8
    [4] K. Kobayashi, K. Hiraishi, Optimal control of asynchronous Boolean networks modeled by petri nets, in Proceedings of the 2nd International Workshop on Biological Processes Petri Nets (BioPPN2011), 1 (2011), 7-20. https://doi.org/10.1587/transfun.E96.A.532
    [5] I. Shmulevich, S. A. Kauffman, Activities and sensitivities in Boolean network models, Phys. Rev. Lett., 93 (2004), 048701. https://doi.org10.1103/PhysRevLett.93.048701 doi: 10.1103/PhysRevLett.93.048701
    [6] M. Hayashida, T. Akutsu, W. K. Ching, Control of Boolean networks: results and algorithms for tree structured networks, J. Theor. Exp. Biol., 244 (2007), 670-679. https://doi.org/10.1016/j.jtbi.2006.09.023 doi: 10.1016/j.jtbi.2006.09.023
    [7] D. Cheng, Semi-tensor product of matrices and its applications: A surveys. ICCM, 3 (2007), 641-668. https://doi.org/10.1007/109844135
    [8] D. Cheng, H. Qi, Z. Li, Analysis and control of Boolean networks: A semitensor product approach, in 2009 7th Asian Control Conference. https://doi.org/10.3724/SP.J.1004.2011.00529
    [9] X. Liu, Y. Wang, N. Shi, Z. Ji, S. He, Gapore: Boolean network inference using a genetic algorithm with novel polynomial representation and encoding scheme, Knowl. Based Syst., 288 (2021), 107277. https://doi.org/10.1016/j.amc.2019.02.067 doi: 10.1016/j.amc.2019.02.067
    [10] S. Barman, Y. K. Kwon, A neuro-evolution approach to infer a Boolean network from time-series gene expressions, Bioinformatics, 36 (2020), i762-i769. https://doi.org/10.1093/bioinformatics/btaa840 doi: 10.1093/bioinformatics/btaa840
    [11] A. Trofino, D. Assmann, C. C. Scharlau, D. F. Coutinho, Switching rule design for switched dynamic systems with affine vector fields, IEEE Trans. Autom. Control, 54 (2009), 2215-2222. https://doi.org/10.1109/TAC.2009.2026848 doi: 10.1109/TAC.2009.2026848
    [12] A. A. Agrachev, D. Liberzon, Lie-algebraic stability criteria for switched systems, SIAM J. Control Optim., 40 (2001), 253-269. https://doi.org/10.1137/S0363012999365704 doi: 10.1137/S0363012999365704
    [13] Z. Ji, L. Wang, X. Guo, On controllability of switched linear systems, IEEE Trans. Autom. Control, 53 (2008), 796-801. https://doi.org/10.1109/TAC.2008.917659 doi: 10.1109/TAC.2008.917659
    [14] S. Zhu, J. Feng, The set stabilization problem for Markovian jump Boolean control networks: An average optimal control approach, Appl. Math. Comput., 402 (2021), 126133. https://doi.org/10.1016/j.amc.2021.126133 doi: 10.1016/j.amc.2021.126133
    [15] J. Wang, W. Liu, S. Fu, J. Xia, On robust set stability and set stabilization of probabilistic Boolean control networks, Appl. Math. Comput., 422 (2022), 126992. https://doi.org/10.1016/j.amc.2022.126992 doi: 10.1016/j.amc.2022.126992
    [16] Q. Zhu, Y. Liu, J. Lu, J. Cao, Further results on the controllability of Boolean control networks, IEEE Trans. Autom. Control, 64 (2018), 440-442. https://doi.org/10.1109/TAC.2018.2830642 doi: 10.1109/TAC.2018.2830642
    [17] Y. Wu, X. Sun, X. Zhao, T. Shen, Optimal control of Boolean control networks with average cost: A policy iteration approach, Automatica, 100 (2019), 378-387. https://doi.org/10.1016/j.automatica.2018.11.036 doi: 10.1016/j.automatica.2018.11.036
    [18] S. Zhu, J. Lu, L. Lin, Y. Liu, Minimum-time and minimum-triggering observability of stochastic Boolean networks, IEEE Trans. Autom. Control, 67 (2021), 1558-1565. https://doi.org/10.1109/TAC.2021.3069739 doi: 10.1109/TAC.2021.3069739
    [19] J. Lu, L. Sun, Y. Liu, D. Ho, J. Cao, Stabilization of Boolean control networks under aperiodic sampled-data control, SIAM J. Control Optim., 56 (2018), 4385-4404. https://doi.org/10.1137/18M1169308 doi: 10.1137/18M1169308
    [20] K. Kobayashi, K. Hiraishi, Optimal control of asynchronous Boolean networks modeled by petri nets, in Proceedings of the 2nd International Workshop on Biological Processes Petri Nets (BioPPN2011), 1 (2011), 7-20. https://doi.org/10.1587/transfun.E96.A.532
    [21] Q. Zhang, J. Feng, B. Wang, Set reachability of Markovian jump Boolean networks and its applications, IET Control Theory Appl., 14 (2020), 2914-2923. https://doi.org/10.1049/iet-cta.2020.0027 doi: 10.1049/iet-cta.2020.0027
    [22] H. Li, X. Xu, X. Ding, Finite-time stability analysis of stochastic switched Boolean networks with impulsive effect, Appl. Math. Comput., 347 (2019), 557-565. https://doi.org/10.1016/j.amc.2018.11.018 doi: 10.1016/j.amc.2018.11.018
    [23] Y. Guo, Y. Ding, D. Xie, Invariant subset and set stability of Boolean networks under arbitrary switching signals, IEEE Trans. Autom. Control, 62 (2017), 4209-4214. https://doi.org/10.1109/tac.2017.2688409 doi: 10.1109/tac.2017.2688409
    [24] H. Li, Y. Wang, Z. Liu, Stability analysis for switched Boolean networks under arbitrary switching signals, IEEE Trans. Autom. Control, 59 (2014), 1978-1982. https://doi.org/10.1109/TAC.2014.2298731 doi: 10.1109/TAC.2014.2298731
    [25] Y. Yu, M. Meng, J. Feng, Y. Gao, An adjoint network approach to design stabilizable switching signals of switched Boolean networks, Appl. Math. Comput., 357 (2019), 12-22. https://doi.org/10.1016/j.knosys.2021.107277 doi: 10.1016/j.knosys.2021.107277
    [26] S. Zhu, J. Lu, Y. Lou, Y. Liu, Induced-equations-based stability analysis and stabilization of Markovian jump Boolean networks, IEEE Trans. Autom. Control, 66 (2020), 4820-4827. https://doi.org/10.1109/TAC.2020.3037142 doi: 10.1109/TAC.2020.3037142
    [27] Z. Liu, J. Zhong, Y. Liu, W. Gui, Weak stabilization of Boolean networks under state-flipped control, IEEE Trans. Autom. Control, 1 (2021), 1-8. https://doi.org/10.1109/TNNLS.2021.3106918 doi: 10.1109/TNNLS.2021.3106918
    [28] E. Fornasini, M. E. Valcher, Observability and reconstructibility of probabilistic Boolean networks, IEEE Trans. Autom. Control, 4 (2019), 319-324. https://doi.org/10.1109/LCSYS.2019.2925870 doi: 10.1109/LCSYS.2019.2925870
    [29] Y. Liu, W. Daniel, W. Gui, Minimal observability of Boolean networks, SIAM J. Control Optim., 65 (2022), 1-12. https://doi.org/10.1007/s11432-021-3365-2 doi: 10.1007/s11432-021-3365-2
    [30] S. Shafiekhani, M. Shafiekhani, S. Rahbar, A. H. Jafari, Extended robust Boolean network of budding yeast cell cycle, J. Med. Signals Sens., 10 (2020), 94-104. https://doi.org/10.4103/jmss.JMSS4019 doi: 10.4103/jmss.JMSS4019
    [31] M. Meng, L. Liu, G. Feng, Stability and $l_1$ gain analysis of Boolean networks with Markovian jump parameters, IEEE Trans. Autom. Control, 62 (2017), 4222-4228. https://doi.org/10.1109/TAC.2017.2679903 doi: 10.1109/TAC.2017.2679903
    [32] X. Ding, H. Li, Stability analysis of multi-valued logical networks with Markov jump disturbances, Int. J. Control, 95 (2022), 554-561. https://doi.org/10.1080/00207179.2020.1803410 doi: 10.1080/00207179.2020.1803410
    [33] L. Wang, Concise proof and calculation of the existence and the uniqueness of stationary distribution of Markov chain, Math. Theory Appl., 1 (2007), 40-43. https://doi.org/CNKI:SUN:LLYY.0.2007-01-012
    [34] Y. Guo, R. Zhou, Y. Wu, W. Gui, C. Yang, Stability and set stability in distribution of probabilistic Boolean networks, IEEE Trans. Autom. Control, 64 (2018), 736-742. https://doi.org/10.1109/TAC.2018.2833170 doi: 10.1109/TAC.2018.2833170
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