Emergent properties of a non-physiological computational model of tumour growth
- Published
- Accepted
- Subject Areas
- Computational Biology, Oncology, Computational Science
- Keywords
- cancer, evolution, computational model, carcinogenesis, tissue organisation field theory, somatic mutation theory, modelling, genetic algorithm
- Copyright
- © 2015 Pantziarka
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Emergent properties of a non-physiological computational model of tumour growth. PeerJ PrePrints 3:e1558v1 https://doi.org/10.7287/peerj.preprints.1558v1
Abstract
NEATG is a simple non-physiological tumour growth model which displays emergent properties which are analogous to a number of characteristics common to physical tumour growth. NEATG employs a novel dual-scale evolutionary algorithm which models both cell-autonomous and non-cell autonomous behaviours. The components of the model are outlined briefly, with reference to the core algorithm and data structures. Experimental results are presented which illustrate the behaviour of the model under different evolutionary scenarios, including homeostasis, tumour growth and a number of anti-tumour interventions. In particular the system is used to explore the impact of cytotoxic interventions, (analogous to high-dose chemotherapy), with respect to adaptive responses and evolutionary change. Finally, a number of avenues for further development of the system are discussed.
Author Comment
This is a submission to PeerJ for review.