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

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 co...

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Main Authors: Figueredo, Grazziela P., Siebers, Peer-Olaf, Aickelin, Uwe
Format: Article
Published: BioMed Central Ltd 2013
Online Access:https://eprints.nottingham.ac.uk/34049/
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author Figueredo, Grazziela P.
Siebers, Peer-Olaf
Aickelin, Uwe
author_facet Figueredo, Grazziela P.
Siebers, Peer-Olaf
Aickelin, Uwe
author_sort Figueredo, Grazziela P.
building Nottingham Research Data Repository
collection Online Access
description 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.
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spelling nottingham-340492020-05-04T16:36:25Z https://eprints.nottingham.ac.uk/34049/ Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective Figueredo, Grazziela P. Siebers, Peer-Olaf Aickelin, Uwe 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. BioMed Central Ltd 2013-04-17 Article PeerReviewed 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 (Spl. 6). S6. ISSN 1471-2105 http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-S6-S6 doi:10.1186/1471-2105-14-S6-S6 doi:10.1186/1471-2105-14-S6-S6
spellingShingle Figueredo, Grazziela P.
Siebers, Peer-Olaf
Aickelin, Uwe
Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
title Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
title_full Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
title_fullStr Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
title_full_unstemmed Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
title_short Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
title_sort investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective
url https://eprints.nottingham.ac.uk/34049/
https://eprints.nottingham.ac.uk/34049/
https://eprints.nottingham.ac.uk/34049/