Mathematical Modeling of Dynamics of Cancer Invasion in Human Body Tissues

Author:

Kemunto Mogire Dinnah,Joash Kerongo,Bulinda Vincent

Publisher

SvedbergOpen

Reference18 articles.

1. Akhtar, A., Majid, H., Abdul, G., Zafar, A., Kottakkaran, S., Alharthi, M. and Wasim, J. (2021). Numerical Simulations and Analysis for Mathematical Model of Avascular Tumor Growth Using Gompertz Growth Rate Function. Published by Elsevier BV. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

2. Beerenwinkel, N., Roland, F., Schwarz, Gerstung, M. and Markowetz, F. (2015). Cancer Evolution: Mathematical Models and Computational Inference. Systematic Biology, 64(1), 2015, e25/https://doi.org/10.1093/sysbio/syu081

3. Brassel, M. and Bretin, E. (2011). A Modified Phase Field Approximation for Mean Curvature Flow with Conservation of the Volume, Math. Meth. Appl. Sci., 34(10), 1157-1180.

4. Elaine, L. et al. (2009). Mathematical Oncology. Multiparameter Computational Modelling of Tumour Invasion. DOI:10.1158/0008-5472.CAN-08-3438.Available online: www.aacrjournals.org

5. Fornier, B., Laporte, D., Lebaudy, A., Sahin, A., Pinson, B., Ceschin. J. and Sagot, I. (2011). Metabolic status rather than cell cycle signals control quiescence entry and exit. J Cell Biol. Mar 21;192(6), 949-57. doi: 10.1083/jcb.201009028. Epub 2011 Mar 14. PMID: 21402786; PMCID: PMC3063145.

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