References
- 1. A. R. A. Anderson and P. K. Maini, Special issue: Mathematical oncology, Bull. Math. Biol., vol. 280, pp. 945{953, 2018.
- 2. P. M. Altrock, L. L. Liu, and F. Michor, The mathematics of cancer: integrating quantitative models, Nat. Rev. Cancer, vol. 15, pp. 730{745, 2015.
- 3. M. P. Little, Cancer models, genomic instability and somatic cellular darwinian evolution, Biology Direct, vol. 5, pp. 1{19, 2010.
- 4. A. Konstorum, A. T. Vella, A. J. Adler, and R. C. Laubenbacher, Addressing current challenges in cancer immunotherapy with mathematical and computational modelling, J. R. Soc. Interface, vol. 14,p. 20170150, 2017.
- 5. M. Lachowicz, Individually-based Markov processes modeling nonlinear systems in mathematical biology, Nonlinear Anal. Real World Appl., vol. 12, pp. 2396{2407, 2011.
- 6. J. Banasiak and M. Lachowicz, Methods of small parameter in mathematical biology. Basel: Birkhauser, 2014.
- 7. N. Bellomo, A. Bellouquid, and E. De Angelis, The modelling of immune competition by generalized kinetic (boltzmann) models: review and research perspectives, Math. Comput. Modelling, vol. 37,pp. 65{86, 2003.
- 8. A. Bellouquid, E. De Angelis, and D. Knopoff, From the modeling of the immune hallmarks of cancerto a black swan in biology, Math. Models Methods Appl. Sci., vol. 23, pp. 949{978, 2013.
- 9. E. De Angelis, On the mathematical theory of post-darwinian mutations, selection, and evolution, Math. Models Methods Appl. Sci, vol. 24, pp. 2723{2742, 2014.
- 10. N. Bellomo, Modeling Complex Living Systems - A Kinetic Theory and Stochastic Game Approach. Basel: Birkhauser, 2008.
- 11. N. Bellomo, A. Bellouquid, L. Gibelli, and N. Outada, A Quest Towards a Mathematical Theory of Living Systems. Basel: Birkhaauser, 2017.
- 12. N. Bellomo, P. Degond, and E. Tadmor, eds., Active Particles Volume 1 - Advances in Theory, Models, and Applications. Basel: Birkhaauser, 2017.
- 13. A. D. Wentzell, A course in the theory of stochastic processes. McGraw-Hill International, 1981.
- 14. D. Hanahan and R. A. Weinberg, Hallmarks of cancer: The next generation, Cell, vol. 44, pp. 646{674, 2011.
- 15. A. Lasota and J. A. Yorke, Exact dynamical systems and the frobenius-perron operator, Trans. Amer. Math. Soc., vol. 273, pp. 375{384, 1982.
- 16. R. Rudnicki, Models of population dynamics and their applications in genetics, in From genetics tomathematics (M.Lachowicz and J. Mi_ekisz, eds.), pp. 103-147, New Jersey: World Sci., 2009.
- 17. M. Lachowicz, A class of microscopic individual models corresponding to the macroscopic logistic growth, Math. Methods Appl. Sci., vol. 41, pp. 8446{8454, 2018.
- 18. M. Lachowicz, A class of individual-based models, BIOMATH, vol. 7, p. 1804127, 2018.
- 19. N. Bellomo and B. Carbonaro, Toward a mathematical theory of living system focusing on developmental biology and evolution: A review and prospectives, Physics of Life Reviews, vol. 8, pp. 1{18, 2011.
- 20. S. De Lillo and N. Bellomo, On the modeling of collective learning dynamics, Appl. Math. Lett., vol. 24, pp. 1861{1866, 2011.
- 21. F. Michor, Y. Iwasa, and M. A. Nowak, Dynamics of cancer progression, Nature Reviews Cancer, vol. 4, pp. 197{205, 2004.
- 22. P. C. Nowell, Tumor progression: a brief historical perspective, Seminars in Cancer Biology, vol. 12, pp. 261{266, 2002.
- 23. R. A. Gatenby and T. L. Vincent, Evolutionary model of carcinogenesis, Cancer Research, vol. 63, pp. 6212{1620, 2003.
- 24. L. Arlotti, N. Bellomo, and M. Lachowicz, Kinetic equations modelling population dynamics, Trans-port Theory Statist. Phys., vol. 29, pp. 125{139, 2000.
- 25. M. Lachowicz, Links between microscopic and macroscopic descriptions, in Lecture Notes Math. 1940, Multiscale Problems in the Life Sciences. From Microscopic to Macroscopic (J. Banasiak, V. Capasso, M. A. J. Chaplain, M. Lachowicz, and J. Miekisz, eds.), pp. 201{268, Berlin: Springer, 2008.