Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective

Figueredo, Grazziela P., Siebers, Peer-Olaf and Aickelin, Uwe (2013) Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective. BMC Bioinformatics, 14 (Su . ISSN 1471-2105

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Abstract

Many advances in research regarding immuno-interactions with cancer were developed with the help of ordinary

differential equation (ODE) models. These models, however, are not effectively capable of representing problems

involving individual localisation, memory and emerging properties, which are common characteristics of cells and

molecules of the immune system. Agent-based modelling and simulation is an alternative paradigm to ODE

models that overcomes these limitations. In this paper we investigate the potential contribution of agent-based

modelling and simulation when compared to ODE modelling and simulation. We seek answers to the following

questions: Is it possible to obtain an equivalent agent-based model from the ODE formulation? Do the outcomes

differ? Are there any benefits of using one method compared to the other? To answer these questions, we have

considered three case studies using established mathematical models of immune interactions with early-stage

cancer. These case studies were re-conceptualised under an agent-based perspective and the simulation results

were then compared with those from the ODE models. Our results show that it is possible to obtain equivalent

agent-based models (i.e. implementing the same mechanisms); the simulation output of both types of models

however might differ depending on the attributes of the system to be modelled. In some cases, additional insight

from using agent-based modelling was obtained. Overall, we can confirm that agent-based modelling is a useful

addition to the tool set of immunologists, as it has extra features that allow for simulations with characteristics

that are closer to the biological phenomena.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/1004139
Additional Information: Proceedings of the 10th International Conference on Artificial Immune Systems (ICARIS), Cambridge, UK, 18-21 July 2011.
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1186/1471-2105-14-S6-S6
Depositing User: Aickelin, Professor Uwe
Date Deposited: 07 Aug 2013 10:35
Last Modified: 04 May 2020 20:20
URI: https://eprints.nottingham.ac.uk/id/eprint/2066

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