Cellular-automaton simulation of tumor growth dynamics: from computational implementation to case analysis

Authors

  • Carlos A. Valentim
  • José A. Rabi
  • Sergio A. David

Abstract

Mathematical oncology explores the development and application of models to cancer-related phenomena [5]. As an important advantage, mathematical models can test and reproduce several scenarios, which could be either unfeasible or impossible through in vitro experiments. [...]

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Author Biographies

Carlos A. Valentim

Department of Biosystems Engineering, University of São Paulo at Pirassununga, Brazil.

José A. Rabi

Department of Biosystems Engineering, University of São Paulo at Pirassununga, Brazil.

Sergio A. David

Department of Biosystems Engineering, University of São Paulo at Pirassununga, Brazil.

References

Heiko Enderling et al. _Paradoxical dependencies of tumor dormancy and progression on basic cell kinetics_. In: Cancer Research 69.22 (2009), pp. 8814_8821. issn: 00085472. doi: 10.1158/0008-5472.CAN-09-2115.

Fleur Jeanquartier et al. _In silico modeling for tumor growth visualization_. In: BMC Sys- tems Biology 10.1 (2016), pp. 1_15. issn: 17520509. doi: 10.1186/s12918-016-0318-8. url: http://dx.doi.org/10.1186/s12918-016-0318-8.

John Metzcar et al. _A Review of Cell-Based Computational Modeling in Cancer Biology_. In: JCO Clinical Cancer Informatics 3 (2019), pp. 1_13. issn: 2473-4276. doi: 10.1200/ cci.18.00069.

Jan Poleszczuk and Heiko Enderling. _A High-Performance Cellular Automaton Model of Tu- mor Growth with Dynamically Growing Domains_. In: Applied Mathematics 05.01 (2014), pp. 144_152. issn: 2152-7385. doi: 10.4236/am.2014.51017. url: http://www.scirp.org/ journal/doi.aspx?DOI=10.4236/am.2014.51017.

Russell C. Rockne and Jacob G. Scott. _Introduction to Mathematical Oncology_. In: JCO Clinical Cancer Informatics 3 (2019), pp. 1_4. issn: 2473-4276. doi: 10.1200/CCI.19. 00010. url: http://ascopubs.org/doi/10.1200/CCI.19.00010.

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Published

2022-12-08

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Section

Resumos