Abstract
Cancer cells interact with tissue cells in a complex manner. Immune cells had that initially participated in eliminating cancer cells are often educated to become assisting cancer growth. Identifying causal relationship of cellular interactions that mediate cancer progression is crucial to understand how cancer cells grow, evolve, and persist. A mathematical model that describes dynamics of cancer cell population is constructed based on a given causal relationship among model ingredients. Mathematical modeling has been employed to explain cancer progression patterns in terms of dynamical system.
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Acknowledgements
This work is supported by JST-Mirai Program Grant Number JPMJMI19B1, the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid (S) 15H0570710 and (B) 18H0266210, and the Ministry of education, culture sports, science and technology-Japan (MEXT) Ambitious Tenure Track program in life science, Hokkaido University.
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Kumakura, D., Nakaoka, S. (2021). Exploring Similarity Between Embedding Dimension of Time-Series Data and Flows of an Ecological Population Model. In: Suzuki, T., Poignard, C., Chaplain, M., Quaranta, V. (eds) Methods of Mathematical Oncology. MMDS 2020. Springer Proceedings in Mathematics & Statistics, vol 370. Springer, Singapore. https://doi.org/10.1007/978-981-16-4866-3_4
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