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Complexity
Volume 2017, Article ID 1409865, 20 pages
https://doi.org/10.1155/2017/1409865
Research Article

Bifurcations and Dynamics of the Rb-E2F Pathway Involving miR449

1Department of Basic Courses, Guangdong Polytechnic College, Zhaoqing 526100, China
2Institute of Applied Mathematics, Xuchang University, Xuchang, Henan 461000, China

Correspondence should be addressed to Jianwei Shen; moc.liamg@nehswjcx

Received 23 February 2017; Revised 19 April 2017; Accepted 14 May 2017; Published 19 October 2017

Academic Editor: Shanmugam Lakshmanan

Copyright © 2017 Lingling Li and Jianwei Shen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Shen, Z. Liu, W. Zheng, F. Xu, and L. Chen, “Oscillatory dynamics in a simple gene regulatory network mediated by small RNAs,” Physica A. Statistical Mechanics and its Applications, vol. 388, no. 14, pp. 2995–3000, 2009. View at Publisher · View at Google Scholar · View at MathSciNet
  2. X. Yang, M. Feng, X. Jiang et al., “miR-449a and miR-449b are direct transcriptional targets of E2F1 and negatively regulate pRb-E2F1 activity through a feedback loop by targeting CDK6 and CDC25A,” Genes & Development, vol. 23, no. 20, pp. 2388–2393, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. T. Bou Kheir, E. Futoma-Kazmierczak, A. Jacobsen et al., “miR-449 inhibits cell proliferation and is down-regulated in gastric cancer,” Molecular Cancer, vol. 10, article 29, 2011. View at Publisher · View at Google Scholar · View at Scopus
  4. E. Khav, Visualing an Rb-E2F cellular switch that controls cell oliferation [Dissertation, thesis], Academic Dissertation, The University of Arizona, 2013.
  5. J. White, E. Stead, R. Faast, S. Conn, P. Cartwright, and S. Dalton, “Developmental activation of the Rb-E2F pathway and establishment of cell cycle-regulated cyclin-dependent kinase activity during embryonic stem cell differentiation,” Molecular Biology of the Cell, vol. 16, no. 4, pp. 2018–2027, 2005. View at Publisher · View at Google Scholar · View at Scopus
  6. J. R. Nevins, G. Leone, J. DeGregori, and L. Jakoi, “Role of the Rb/E2F pathway in cell growth control,” Journal of Cellular Physiology, vol. 173, no. 2, pp. 233–236, 1997. View at Publisher · View at Google Scholar · View at Scopus
  7. J. R. Nevins, “The Rb/E2F pathway and cancer,” Human Molecular Genetics, vol. 10, no. 7, pp. 699–703, 2001. View at Publisher · View at Google Scholar · View at Scopus
  8. L. Hangnoh, Regulation of differentiation-specific genes by the Drosophila RB, E2F, and Myb-interacting proteins complex (dREAM [Dissertation, thesis], Academic Dissertation, The State University of New Jersey, 2011.
  9. D. Hanahan and R. A. Weinberg, “The hallmarks of cancer,” Cell, vol. 100, no. 1, pp. 57–70, 2000. View at Publisher · View at Google Scholar · View at Scopus
  10. R. C. Sears and J. R. Nevins, “Signaling networks that link cell proliferation and cell fate,” Journal of Biological Chemistry, vol. 277, no. 14, pp. 11617–11620, 2002. View at Publisher · View at Google Scholar · View at Scopus
  11. N. Ghanem, M. G. Andrusiak, D. Svoboda et al., “The Rb/E2F pathway modulates neurogenesis through direct regulation of the Dlx1/Dlx2 bigene cluster,” Journal of Neuroscience, vol. 32, no. 24, pp. 8219–8230, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. F. Yan, H. Liu, J. Hao, and Z. Liu, “Dynamical Behaviors of Rb-E2F Pathway Including Negative Feedback Loops Involving miR449,” PLoS ONE, vol. 7, no. 9, Article ID e43908, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. M. N. Obeyesekere, S. O. Zimmerman, E. S. Tecarro, and G. Auchmuty, “A model of cell cycle behavior dominated by kinetics of a pathway stimulated by growth factors,” Bulletin of Mathematical Biology, vol. 61, no. 5, pp. 917–934, 1999. View at Publisher · View at Google Scholar · View at Scopus
  14. G. Yao, T. J. Lee, S. Mori, J. R. Nevins, and L. You, “A bistable Rb-E2F switch underlies the restriction point,” Nature Cell Biology, vol. 10, no. 4, pp. 476–482, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. H. Chen, P. A. Mundra, L. N. Zhao, F. Lin, and J. Zheng, “Highly sensitive inference of time-delayed gene regulation by network deconvolution,” BMC Systems Biology, vol. 8, no. 4, article no. S6, 2014. View at Publisher · View at Google Scholar · View at Scopus
  16. J.-P. Richard, “Time-delay systems: an overview of some recent advances and open problems,” Automatica. A Journal of IFAC, the International Federation of Automatic Control, vol. 39, no. 10, pp. 1667–1694, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  17. C. Y. Ko, M. B. Liu, Z. Song, Z. Qu, and J. N. Weiss, “Multiscale Determinants of Delayed Afterdepolarization Amplitude in Cardiac Tissue,” Biophysical Journal, vol. 112, no. 9, pp. 1949–1961, 2017. View at Publisher · View at Google Scholar
  18. L. Mier-y-Tern-Romero, M. Silber, and V. Hatzimanikatis, “The origins of time-delay in template biopolymerization processes,” PLoS Computational Biology, vol. 6, no. 4, e1000726, 15 pages, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  19. Q. Zheng, Z. Wang, and J. Shen, “Pattern dynamics of network-organized system with cross-diffusion,” Chinese Physics B, vol. 26, no. 2, p. 020501, 2017. View at Publisher · View at Google Scholar
  20. Q. Zheng and J. Shen, “Dynamics and pattern formation in a cancer network with diffusion,” Communications in Nonlinear Science and Numerical Simulation, vol. 27, no. 1-3, pp. 93–109, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  21. Y. Xu, Y.-N. Zhu, J. W. Shen, and J. B. Su, “Switch dynamics for stochastic model of genetic toggle switch,” Physica A: Statistical Mechanics and Its Applications, vol. 416, pp. 461–466, 2014. View at Publisher · View at Google Scholar · View at Scopus
  22. Q. Zheng and J. Shen, “Pattern formation in the FitzHugh—Nagumo model,” Computers & Mathematics with Applications, vol. 70, no. 5, pp. 1082–1097, 2015. View at Publisher · View at Google Scholar · View at MathSciNet
  23. Q. Zheng and J. Shen, “Turing instability in a gene network with cross-diffusion,” Nonlinear Dynamics. An International Journal of Nonlinear Dynamics and Chaos in Engineering Systems, vol. 78, no. 2, pp. 1301–1310, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. Q. Zheng and J. Shen, “Bifurcations and dynamics of cancer signaling network regulated by MicroRNA,” Discrete Dynamics in Nature and Society, vol. 2013, Article ID 176956, 2013. View at Publisher · View at Google Scholar · View at Scopus
  25. G. Orosz, J. Moehlis, and R. M. Murray, “Controlling biological networks by time-delayed signals,” Philosophical Transactions of the Royal Society of London. Series A. Mathematical, Physical and Engineering Sciences, vol. 368, no. 1911, pp. 439–454, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. Z. Song, Z. Qu, and A. Karma, “Stochastic initiation and termination of calcium-mediated triggered activity in cardiac myocytes,” Proceedings of the National Academy of Sciences, vol. 114, no. 3, pp. E270–E279, 2017. View at Publisher · View at Google Scholar
  27. P. Zoppoli, S. Morganella, and M. Ceccarelli, “Timedelay-ARACNE: reverse engineering of gene networks from time-course data by an information theoretic approach,” BMC Bioinformatics, vol. 11, no. 1, article 154, 2010. View at Publisher · View at Google Scholar · View at Scopus
  28. Y. Li and A. Ngom, “The max-min high-order dynamic Bayesian network learning for identifying gene regulatory networks from time-series microarray data,” in Proceedings of the 10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, pp. 83–90, April 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. Y. Cao and P. M. Frank, “Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach,” IEEE Transactions on Fuzzy Systems, vol. 8, no. 2, pp. 200–211, 2000. View at Publisher · View at Google Scholar · View at Scopus
  30. Z. Song, C. Y. Ko, M. Nivala, J. N. Weiss, and Z. Qu, “Complex darly and delayed afterdepolarization dynamics caused by voltage-calcium coupling in cardiac myocytes,” Biophysical Journal, vol. 108, no. 8, pp. 261A–262A, 2015. View at Publisher · View at Google Scholar
  31. C. Y. Ko, Z. Song, Z. Qu, and J. N. Weiss, “Multiscale Consequences of Spontaneous Calcium Release on Cardiac Delayed Afterdepolarizations,” Biophysical Journal, vol. 108, no. 2, p. 264a, 2015. View at Publisher · View at Google Scholar