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

Kieran Alden*, Paul S. Andrews, Henrique Veiga-Fernandes, Jon Timmis, Mark Coles

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)


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.

Original languageEnglish
Pages (from-to)99-107
Number of pages9
JournalNatural Computing
Issue number1
Publication statusPublished - Mar 2015
Externally publishedYes


  • Model composition
  • Peyer’s patches
  • Simulation
  • Statistical analysis


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