Request a copy

Full Text

• Akutsu, T., Hayashida, M., Ching, W.K., Ng, M.K.: Control of Boolean networks: hardness results and algorithms for tree structured networks. J. Theor. Biol. 244(4), 670–679 (2007). https://doi.org/10.1016/j.jtbi.2006.09.023
• Biane, C., Delaplace, F.: Abduction based drug target discovery using boolean control network. In: Feret, J., Koeppl, H. (eds.) CMSB 2017. LNCS, vol. 10545, pp. 57–73. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67471-1_4
• Cheng, D., Qi, H.: Controllability and observability of Boolean control networks. Automatica 45(7), 1659–1667 (2009). https://doi.org/10.1016/j.automatica.2009.03.006
• Cheng, D., Qi, H., Li, Z.: Analysis and control of Boolean networks: a semi-tensor product approach. Acta Automatica Sinica 37, 529–540 (2011)
• Cheng, D., Qi, H., Li, Z.: Identification of Boolean control networks. Automatica 47(4), 702–710 (2011). https://doi.org/10.1016/j.automatica.2011.01.083
• Cheng, D., Qi, H., Liu, T., Wang, Y.: A note on observability of Boolean control networks. Syst. Control Lett. 87, 76–82 (2016). https://doi.org/10.1016/j.sysconle.2015.11.004
• Fornasini, E., Valcher, M.E.: Observability, reconstructibility and state observers of Boolean control networks. IEEE Trans. Autom. Control 58(6), 1390–1401 (2013). https://doi.org/10.1109/TAC.2012.2231592
• Guo, Y.: Observability of Boolean control networks using parallel extension and set reachability. IEEE Trans. Neural Netw. Learn. Syst. 29(12), 6402–6408 (2018). https://doi.org/10.1109/TNNLS.2018.2826075
• Ideker, T., Galitski, T., Hood, L.: A new approach to decoding life: systems biology. Ann. Rev. Genomics Hum. Genet. 2(1), 343–372 (2001). https://doi.org/10.1146/annurev.genom.2.1.343
• Jacob, F., Monod, J.: Genetic regulatory mechanisms in the synthesis of proteins. J. Mol. Biol. 3(3), 318–356 (1961). https://doi.org/10.1016/S0022-2836(61)80072-7
• Kauffman, S.A.: Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theor. Biol. 22(3), 437–467 (1969). https://doi.org/10.1016/0022-5193(69)90015-0
• Kaufman, M., Andris, F., Leo, O.: A logical analysis of t cell activation and anergy. Proc. Natl. Acad. Sci. 96(7), 3894–3899 (1999). https://doi.org/10.1073/pnas.96.7.3894
• Klamt, S., Saez-Rodriguez, J., Lindquist, J.A., Simeoni, L., Gilles, E.D.: A methodology for the structural and functional analysis of signaling and regulatory networks. BMC Bioinf. 7(1), 56 (2006). https://doi.org/10.1186/1471-2105-7-56
• Li, F., Sun, J.: Observability analysis of Boolean control networks with impulsive effects. IET Control Theory Appl. 5, 1609–1616 (2011). https://doi.org/10.1049/iet-cta.2010.0558
• Mandon, H., Su, C., Haar, S., Pang, J., Paulevé, L.: Sequential reprogramming of boolean networks made practical. In: Bortolussi, L., Sanguinetti, G. (eds.) CMSB 2019. LNCS, vol. 11773, pp. 3–19. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-31304-3_1
• Su, C., Pang, J.: Target control of asynchronous Boolean networks. IEEE/ACM Trans. Comput. Biol. Bioinf. 20(1), 707–719 (2023)
• Su, C., Pang, J., Paul, S.: Towards optimal decomposition of Boolean networks. IEEE/ACM Trans. Comput. Biol. Bioinf. 18(6), 2167–2176 (2021)
• Su, C., Paul, S., Pang, J.: Controlling large Boolean networks with temporary and permanent perturbations. In: ter Beek, M.H., McIver, A., Oliveira, J.N. (eds.) FM 2019. LNCS, vol. 11800, pp. 707–724. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30942-8_41
• Thunberg, J., Ogren, P., Hu, X.: A Boolean control network approach to pursuit evasion problems in polygonal environments. In: IEEE International Conference on Robotics and Automation, pp. 4506–4511 (2011). https://doi.org/10.1109/ICRA.2011.5979948
• Wang, B., Feng, J., Cheng, D.: On identification of Boolean control networks. SIAM J. Control. Optim. 60(3), 1591–1612 (2022). https://doi.org/10.1137/20M1373773
• Wu, G., Pang, J.: Single-experiment reconstructibility of Boolean control networks revisited. In: Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics, pp. 95–93. SCITEPRESS (2023)
• Yuan, Q., Mizera, A., Pang, J., Qu, H.: A new decomposition-based method for detecting attractors in synchronous Boolean networks. Sci. Comput. Program. 180, 18–35 (2019)
• Zhang, K., Zhang, L.: Observability of Boolean control networks: a unified approach based on finite automata. IEEE Trans. Autom. Control 61(9), 2733–2738 (2016). https://doi.org/10.1109/TAC.2015.2501365
• Zhang, K., Zhang, L., Xie, L.: Detectability of nondeterministic finite-transition systems. In: Discrete-Time and Discrete-Space Dynamical Systems. CCE, pp. 165–175. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-25972-3_8
• Zhang, K., Zhang, L., Xie, L.: Different types of discrete-time and discrete-space dynamical systems. In: Discrete-Time and Discrete-Space Dynamical Systems. CCE, pp. 35–56. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-25972-3_2
• Zhang, K., Zhang, L., Xie, L.: Observability and detectability of large-scale boolean control networks. In: Discrete-Time and Discrete-Space Dynamical Systems. CCE, pp. 117–142. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-25972-3_6
• Zhang, K., Zhang, L., Xie, L.: Observability of Boolean control networks. In: Discrete-Time and Discrete-Space Dynamical Systems. CCE, pp. 87–104. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-25972-3_4
• Zhao, Y., Qi, H., Cheng, D.: Input-state incidence matrix of Boolean control networks and its applications. Syst. Control Lett. 59(12), 767–774 (2010). https://doi.org/10.1016/j.sysconle.2010.09.002
• Zhong, D., Li, Y., Lu, J.: Feedback stabilization of Boolean control networks with missing data. IEEE Trans. Neural Netw. Learn. Syst. 34, 7784–7795 (2023). https://doi.org/10.1109/TNNLS.2022.3146262
• Zhu, S., Lu, J., Lin, L., Liu, Y.: Minimum-time and minimum-triggering observability of stochastic Boolean networks. IEEE Trans. Autom. Control 67(3), 1558–1565 (2022). https://doi.org/10.1109/TAC.2021.3069739
• Zhu, S., Lu, J., Zhong, J., Liu, Y., Cao, J.: On the sensors construction of large Boolean networks via pinning observability. IEEE Trans. Autom. Control (2021). https://doi.org/10.1109/TAC.2021.3110165