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Utilising a simulation platform to understand the effect of domain model assumptions

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Utilising a simulation platform to understand the effect of domain model assumptions. / Alden, Kieran; Andrews, Paul S.; Veiga-Fernandes, Henrique; Timmis, Jon; Coles, Mark.

In: Natural Computing, Vol. 14, No. 1, 03.2015, p. 99-107.

Research output: Contribution to journalArticlepeer-review

Harvard

Alden, K, Andrews, PS, Veiga-Fernandes, H, Timmis, J & Coles, M 2015, 'Utilising a simulation platform to understand the effect of domain model assumptions', Natural Computing, vol. 14, no. 1, pp. 99-107. https://doi.org/10.1007/s11047-014-9428-7

APA

Alden, K., Andrews, P. S., Veiga-Fernandes, H., Timmis, J., & Coles, M. (2015). Utilising a simulation platform to understand the effect of domain model assumptions. Natural Computing, 14(1), 99-107. https://doi.org/10.1007/s11047-014-9428-7

Vancouver

Alden K, Andrews PS, Veiga-Fernandes H, Timmis J, Coles M. Utilising a simulation platform to understand the effect of domain model assumptions. Natural Computing. 2015 Mar;14(1):99-107. https://doi.org/10.1007/s11047-014-9428-7

Author

Alden, Kieran ; Andrews, Paul S. ; Veiga-Fernandes, Henrique ; Timmis, Jon ; Coles, Mark. / Utilising a simulation platform to understand the effect of domain model assumptions. In: Natural Computing. 2015 ; Vol. 14, No. 1. pp. 99-107.

Bibtex - Download

@article{b2facc5b9f734c34a5ab34198bff9964,
title = "Utilising a simulation platform to understand the effect of domain model assumptions",
abstract = "Computational and mathematical modelling approaches are increasingly being adopted in attempts to further our understanding of complex biological systems. This approach can be subjected to strong criticism as substantial aspects of the biological system being captured are not currently known, meaning assumptions need to be made that could have a critical impact on simulation response. We have utilised the CoSMoS process in the development of an agent-based simulation of the formation of Peyer's patches (PP), gut-associated lymphoid organs that have a key role in the initiation of adaptive immune responses to infection. Although the use of genetic tools, imaging technologies and ex vivo culture systems has provided significant insight into the cellular components and associated pathways involved in PP development, interesting questions remain that cannot be addressed using these approaches, and as such well justified assumptions have been introduced into our model to counter this. Here we focus not on the development of the model itself, but instead demonstrate how the resultant simulation can be used to assess how these assumptions impact the simulation response. For example, we consider the impact of our assumption that the migration rate of lymphoid tissue cells into the gut remains constant throughout PP development. We demonstrate that an analysis of the assumptions made in the construction of the domain model may either increase confidence in the model as a representation of the biological system it captures, or may suggest areas where further biological experimentation is required.",
keywords = "Model composition, Peyer's patches, Simulation, Statistical analysis",
author = "Kieran Alden and Andrews, {Paul S.} and Henrique Veiga-Fernandes and Jon Timmis and Mark Coles",
year = "2015",
month = mar,
doi = "10.1007/s11047-014-9428-7",
language = "English",
volume = "14",
pages = "99--107",
journal = "Natural Computing",
issn = "1567-7818",
publisher = "Springer Netherlands",
number = "1",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Utilising a simulation platform to understand the effect of domain model assumptions

AU - Alden, Kieran

AU - Andrews, Paul S.

AU - Veiga-Fernandes, Henrique

AU - Timmis, Jon

AU - Coles, Mark

PY - 2015/3

Y1 - 2015/3

N2 - Computational and mathematical modelling approaches are increasingly being adopted in attempts to further our understanding of complex biological systems. This approach can be subjected to strong criticism as substantial aspects of the biological system being captured are not currently known, meaning assumptions need to be made that could have a critical impact on simulation response. We have utilised the CoSMoS process in the development of an agent-based simulation of the formation of Peyer's patches (PP), gut-associated lymphoid organs that have a key role in the initiation of adaptive immune responses to infection. Although the use of genetic tools, imaging technologies and ex vivo culture systems has provided significant insight into the cellular components and associated pathways involved in PP development, interesting questions remain that cannot be addressed using these approaches, and as such well justified assumptions have been introduced into our model to counter this. Here we focus not on the development of the model itself, but instead demonstrate how the resultant simulation can be used to assess how these assumptions impact the simulation response. For example, we consider the impact of our assumption that the migration rate of lymphoid tissue cells into the gut remains constant throughout PP development. We demonstrate that an analysis of the assumptions made in the construction of the domain model may either increase confidence in the model as a representation of the biological system it captures, or may suggest areas where further biological experimentation is required.

AB - Computational and mathematical modelling approaches are increasingly being adopted in attempts to further our understanding of complex biological systems. This approach can be subjected to strong criticism as substantial aspects of the biological system being captured are not currently known, meaning assumptions need to be made that could have a critical impact on simulation response. We have utilised the CoSMoS process in the development of an agent-based simulation of the formation of Peyer's patches (PP), gut-associated lymphoid organs that have a key role in the initiation of adaptive immune responses to infection. Although the use of genetic tools, imaging technologies and ex vivo culture systems has provided significant insight into the cellular components and associated pathways involved in PP development, interesting questions remain that cannot be addressed using these approaches, and as such well justified assumptions have been introduced into our model to counter this. Here we focus not on the development of the model itself, but instead demonstrate how the resultant simulation can be used to assess how these assumptions impact the simulation response. For example, we consider the impact of our assumption that the migration rate of lymphoid tissue cells into the gut remains constant throughout PP development. We demonstrate that an analysis of the assumptions made in the construction of the domain model may either increase confidence in the model as a representation of the biological system it captures, or may suggest areas where further biological experimentation is required.

KW - Model composition

KW - Peyer's patches

KW - Simulation

KW - Statistical analysis

U2 - 10.1007/s11047-014-9428-7

DO - 10.1007/s11047-014-9428-7

M3 - Article

C2 - 25722664

VL - 14

SP - 99

EP - 107

JO - Natural Computing

JF - Natural Computing

SN - 1567-7818

IS - 1

ER -