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Bogdanov–Takens and Hopf Bifurcations Analysis of a Genetic Regulatory Network

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Abstract

The stability and two kinds of bifurcations of a genetic regulatory network are considered in this paper. We have given a complete stability analysis involved in mentioned model. The Hopf bifurcation of codimension 1 and Bogdanov–Takens bifurcation of codimension 2 for the nonhyperbolic equilibria of the model is characterized analytically. In order to determine the stability of limit cycle of Hopf bifurcation, the first Lyapunov number is calculated and a numerical example is given to illustrate graphically. Three bifurcation curves related to Bogdanov–Takens bifurcation, namely saddle-node, Hopf and homoclinic bifurcation curves, are given explicitly by calculating a universal unfolding near the cusp. Moreover, the numerical continuation results show that the model has other bifurcation types, including saddle-node and cusp bifurcations. The bifurcation diagram and phase portraits are also given to verify the validity of the theoretical results. These results show that there exists rich bifurcation behavior in the genetic regulatory network.

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References

  1. Xue, Y., Zhang, L.N., Zhang, X.: Reachable set estimation for genetic regulatory networks with time-varying delays and bounded disturbances. Neurocomputing 403, 203–210 (2020)

    Article  Google Scholar 

  2. Liu, C.Y., Wang, X., Xue, Y.: Global exponential stability analysis of discrete-time genetic regulatory networks with time-varying discrete delays and unbounded distributed delays. Neurocomputing 372, 100–108 (2020)

    Article  Google Scholar 

  3. Gnanakkumaar, P., Murugesan, R., Ahmed, S.: Gene regulatory networks in peripheral mononuclear cells reveals critical regulatory modules and regulators of multiple sclerosis. Sci. Rep. 9, 12732 (2019)

    Article  Google Scholar 

  4. Edwards, D.R.: Cell signaling and the control of gene transcription. Trends Pharmacol. Sci. 15, 239–244 (1994)

    Article  Google Scholar 

  5. Pandiselvi, S., Raja, R., Cao, J.D., Rajchakit, G.: Stabilization of switched stochastic genetic regulatory networks with leakage and impulsive effects. Neural Process. Lett. 49, 593–610 (2019)

    Article  Google Scholar 

  6. Ghosh, A., Greenberg, M.: Calcium signaling in neurons: molecular mechanisms and cellular consequences. Science 268, 239–247 (1995)

    Article  Google Scholar 

  7. Shen, H., Huo, S.C., Yan, H.C., Park, J.H., Sreeram, V.: Distributed dissipative state estimation for Markov jump genetic regulatory networks subject to round-robin scheduling. IEEE Trans. Neural Netw. Learn. Syst. 31, 762–771 (2020)

    Article  MathSciNet  Google Scholar 

  8. Zhang, X., Wu, L.G., Cui, S.C.: An improved integral inequality to stability analysis of genetic regulatory networks with interval time-varying delays. IEEE/ACM Trans. Comput. Biol. Bioinf. 12, 398–409 (2015)

    Article  Google Scholar 

  9. Sun, Q.S., Xiao, M., Tao, B.B.: Local bifurcation analysis of a fractional-order dynamic model of genetic regulatory networks with delays. Neural Process. Lett. 47, 1285–1296 (2018)

    Article  Google Scholar 

  10. Liu, H.H., Yan, F., Liu, Z.R.: Oscillatory dynamics in a gene regulatory network mediated by small RNA with time delay. Nonlinear Dyn. 76, 147–159 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  11. Mussel, C., Hopfensitz, M., Kestler, H.A.: BoolNet-an R package for generation, reconstruction and analysis of Boolean networks. Bioinformatics 26, 1378–1380 (2010)

    Article  Google Scholar 

  12. Liu, F., Zhang, S.W., Guo, W.F., Wei, Z.G., Chen, L.N.: Inference of gene regulatory network based on local Bayesian networks. PLOS Comput. Biol. 12, e1005024 (2016)

    Article  Google Scholar 

  13. Krämer, N., Schäfer, J., Boulesteix, A.L.: Regularized estimation of large-scale gene association networks using graphical Gaussian models. BMC Bioinform. 10, 1–24 (2009)

    Article  Google Scholar 

  14. Pan, W., Wang, Z.D., Gao, H.J., Liu, X.H.: Monostability and multistability of genetic regulatory networks with different types of regulation functions. Nonlinear Anal.-R.W.A. 11, 3170–3185 (2010)

    Article  MATH  Google Scholar 

  15. Braniff, N., Richards, A., Ingalls, B.: Optimal experimental design for a bistable gene regulatory network. IFAC-PapersOnLine 52, 255–261 (2019)

    Article  Google Scholar 

  16. Duan, L., Di, F.J., Wang, Z.Y.: Existence and global exponential stability of almost periodic solutions of genetic regulatory networks with time-varying delays. J. Exp. Theor. Artif. In. 32, 453–463 (2020)

    Article  Google Scholar 

  17. Zang, H., Zhang, T.H., Zhang, Y.D.: Bifurcation analysis of a mathematical model for genetic regulatory network with time delays. Appl. Math. Comput. 260, 204–226 (2015)

    MathSciNet  MATH  Google Scholar 

  18. Poignard, C.: Inducing chaos in a gene regulatory network by coupling an oscillating dynamics with a hysteresis-type one. J. Math. Biol. 69, 335–368 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  19. Khlebodarova, T.M., Kogai, V.V., Fadeev, S.I., Likhoshvai, V.A.: Chaos and hyperchaos in simple gene network with negative feedback and time delays. J. Bioinf. Comput. Biol. 15, 1650042 (2017)

    Article  Google Scholar 

  20. Lai, Q., Chen, Q.: Stability and bifurcation of delayed gene regulatory network with self-feedback, positive feedback and negative feedback. In: 37th Chinese Control Conference. https://doi.org/10.23919/chicc.2018.8483014 (2018)

  21. Takens, F.: Singularities of vector fields. Publ. Math. IHES. 43, 47–100 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  22. Bogdanov, R.I.: Versal deformations of a singular point on the plane in the case of zero eigenvalues. Funct. Anal. Appl. 9, 144–145 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  23. Steindl, A.: Numerical investigation of the Hopf-Bogdanov-Takens mode interaction for a fluid-conveying tube. Procedia Eng. 199, 857–862 (2017)

    Article  Google Scholar 

  24. Algaba, A., Domínguez-Moreno, M.C., Merino, M., Rodríguez-Luis, A.J.: Takens-Bogdanov bifurcations of equilibria and periodic orbits in the Lorenz system. Commun. Nonlinear Sci. Numer. Simul. 30, 328–343 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  25. de Blank, H.J., Kuznetsov, Y.A., Pekkér, M.J., Veldman, D.W.M.: Degenerate Bogdanov-Takens bifurcations in a one-dimensional transport model of a fusion plasma. Physica D 331, 13–26 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  26. Yu, P., Zhang, W.J.: Complex dynamics in a unified SIR and HIV disease model: a bifurcation theory approach. J. Nonlinear Sci. 29, 2447–2500 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  27. Lu, M., Huang, J.C., Ruan, S.G., Yu, P.: Bifurcation analysis of an SIRS epidemic model with ageneralized nonmonotone and saturated incidence rate. J. Differ. Equ. 267, 1859–1898 (2019)

    Article  MATH  Google Scholar 

  28. Hu, D.P., Cao, H.J.: Stability and bifurcation analysis in a predator-prey system with Michaelis-Menten type predator harvesting. Nonlinear Anal.-R.W.A. 33, 58–82 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  29. Titz, S., Kuhlbrodt, T., Feudel, U.: Homoclinic bifurcation in an ocean circulation box model. Int. J. Bifurcat. Chaos 12, 869–875 (2002)

    Article  Google Scholar 

  30. Lenz, E., Pagano, D.J., Tahim, A.P.N.: Codimension-two bifurcation analysis in DC microgrids under droop control. Int. J. Bifurcat. Chaos 26, 1650028 (2016)

    Article  MATH  Google Scholar 

  31. Marwan, M., Ahmad, S., Aqeel, M., Sabir, M.: Control analysis of rucklidge chaotic system. J. Dyn. Sys. Meas. Control 141, 041010 (2019)

    Article  Google Scholar 

  32. Marsden, J.E., McCracken, M.: The Hopf Bifurcation and Its Applications. Springer, New York (1976)

    Book  MATH  Google Scholar 

  33. Novák, B., Tyson, J.J.: Design principles of biochemical oscillators. Nat. Rev. Mol. Cell Biol. 9, 981–991 (2008)

    Article  Google Scholar 

  34. Liu, M., Meng, F.W., Hu, D.P.: Impacts of multiple time delays on a gene regulatory network mediated by small noncoding RNA. Int. J. Bifurcat. Chaos 30, 2050069 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  35. Sun, Q.S., Xiao, M., Tao, B.B.: Local bifurcation analysis of a fractional-order dynamic model of genetic regulatory networks with delays. Neural Process. Lett. 47, 1285–1296 (2017)

    Article  Google Scholar 

  36. Yue, D.D., Guan, Z.H., Li, J., Liu, F., Xiao, J.W., Ling, G.: Stability and bifurcation of delay-coupled genetic regulatory networks with hub structure. J. Franklin I. 356, 2847–2869 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  37. Wang, G.Y., Yang, Z.Q., Turcotte, M.: Dynamic analysis of the time-delayed genetic regulatory network between two auto-regulated and mutually inhibitory genes. B. Math. Biol. 82, 46 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  38. Smolen, P., Baxter, D.A., Byrne, J.H.: Frequency selectivity, multistability, and oscillations emerge from models of genetic regulatory systems. Am. J. Physiol. 274, C531–C542 (1998)

    Article  Google Scholar 

  39. Wan, A.Y., Zou, X.F.: Hopf bifurcation analysis for a model of genetic regulatory system with delay. J. Math. Anal. Appl. 356, 464–476 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  40. Yu, T.T., Zhang, X., Zhang, G.D., Niu, B.: Hopf bifurcation analysis for genetic regulatory networks with two delays. Neurocomputing 164, 190–200 (2015)

    Article  Google Scholar 

  41. Cheng, X.J., Wang, H., Wang, X., Duan, J.Q., Li, X.F.: Most probable transition pathways and maximal likely trajectories in a genetic regulatory system. Physica A 531, 121779 (2019)

    Article  MathSciNet  Google Scholar 

  42. Wang, H., Cheng, X.J., Duan, J.Q., Kurths, J., Li, X.F.: Likelihood for transcriptions in a genetic regulatory system under asymmetric stable Lévy noise. Chaos 28, 013121 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  43. Liu, F., Ren, J., Ling, G., Wei, L.S., Zheng, S.Q., Wang, H.: Stability analysis and bifurcation control of a delayed fractional order GRNs model. In: Proceedings of the 37th Chinese Control Conference (2018)

  44. Wiggins, S.: Introduction to Applied Nonlinear Dynamical Systems and Chaos, Texts in applied mathematics, vol. 2. Springer, New York (2003)

    MATH  Google Scholar 

  45. Strogatz, S.H.: Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, 2nd edn. CRC Press (2018)

  46. Kuznetsov, Y.A.: Elements of applied bifurcation theory. In: Texts in Applied Mathematical Sciences, vol. 112, 2nd edn. Springer, New York, (1998)

  47. Dhooge, A., Govaerts, W., Kuznetsov, Y.A.: MatCont: a MATLAB package for numerical bifurcation analysis of ODEs. ACM TOMS 29, 141–164 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  48. Zhu, Q.H., Shen, J.W., Han, F., Lu, W.L.: Bifurcation analysis and probabilistic energy landscapes of two-component genetic network. IEEE Access 8, 150696–150708 (2020)

    Article  Google Scholar 

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Funding

This work is supported by Natural Science Foundation of China (NSFC) under Project No. 11671227, NSF of Shandong Province under Project Nos. ZR2021MA016, ZR2018BF018 and China Postdoctoral Science Foundation under No. 2019M652349 and the Youth Creative Team Sci-Tech Program of Shandong Universities under No. 2019KJI007.

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Correspondence to Dongpo Hu.

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Liu, M., Meng, F. & Hu, D. Bogdanov–Takens and Hopf Bifurcations Analysis of a Genetic Regulatory Network. Qual. Theory Dyn. Syst. 21, 45 (2022). https://doi.org/10.1007/s12346-022-00575-0

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