1. Adam, J.A., and Bellomo, N., A survey of models for tumor-immune system dynamics, Birkhäuser Verlag AG, Basel-Berlin-Boston, 1996.
2. Ashyani, A., Mohammadinejad, H.M., and RabieiMotlagh, O., Hopf bifurcation analysis in a delayed system for cancer virotherapy, Indag. Math.,27(1) (2015), 318–339.
3. Chen, Y., and Su, Y.M., An improved model of tumor therapy with the Oncolytic virus, Journal of Henan University of Science and Technology, 37 (2016), 92–96.
4. Choudhury, B. S., and Nasipuri, B., Efficient virotherapy of cancer in the presence of an immune response, Int. J. Dyn. Control. 2 (2014), 314–325.
5. Hassard, B.D., Kazarinoff, N.D., and Wan, Y.H., Theory and applications of Hopf bifurcation, Cambridge University, Press, Cambridge, 1981.
6. Kim, P. H., Sohn, J. H., Choi, J. W., Jung, Y., Kim, S. W., Haam. S., and Yun, C. O., Active targeting and safety profileof PEG-modified adenovirus conjugated with herceptin, Biomaterials, 32(9) (2011), 2314–2326.
7. Mohammadian, H., and Asnafi, A., Presentation of a model for virus therapy of cancer tumors using the modified prey-predator population dy namics, Solids and Structures, 2 (2013), 17–22.
8. Ruan, S., Absolute stability, conditional stability, and bifurcation in Kolmogrove-type predator-prey systems with discrete delays, Quart. Appl. Math. 59 (2001), 159–173.
9. Si, W., and Zhang, W., Control exponential growth of tumor cells with slow spread of the Oncolytic virus, J. Theor. Biol. 367 (2015), 111–129.
10. Tian, J. P., Kuang, Y., and Yang, H., Intracellular viral life-cycle in duced rich dynamics in tumor virotherapy, Canadian Journal of Applied Mathematics, (2016).
11. Wodarz, D., Viruses as antitumor weapons: Defining conditions for tumor remission, Cancer Res. 61 (2001), 3501–3507.
12. Wodarz, D., Gene therapy for killing p53-Negative cancer cells: Use of replicating versus nonreplicating agents, Human Gene Theory, 14 (2003),153–159.
13. Wodarz, D., Computational modeling approaches to the dynamics of On colytic viruses, WIREs. Syst. Biol. Med. 8 (2016), 242–252.
14. Wodarz, D., and Komarova, N.,Towards predictive computational models of Oncolytic virus therapy: basis for experimental validation and model selection, PloS one, 4(1) (2009), 42–71.
15. Su, Y., Jia, C., and Chen, Y., Optimal control model of tumor treatment with Oncolytic virus and MEK inhibitor, Biomed Res Int. (2016), 1–8.
16. Zurakowski, R., and Wodarz, D., Model-driven approaches for in vitro combination therapy using ONYX-015 replicating oncolytic adenovirus, J. Theor. Biol. 245 (2007), 1–8.
Send comment about this article