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Adopting an agent-based modelling approach, we have developed a simulator that captures the development of lymphoid organs in the gut: Peyer's Patches. With this tool, we have shown that we can create cell behaviour that is statistically similar to that observed in cell culture systems, and have generated testable biological hypotheses concerning the cellular interactions leading to the development of these organs: necessary for triggering adaptive immune responses. We describe the simulator in the tabs below.

The methodology used to create the simulator is explored in our Frontiers in Immunology paper (http://www.frontiersin.org/Inflammation/abstract/22737), the results in our Science Signalling paper (http://stke.sciencemag.org/cgi/content/summary/sigtrans;5/235/ra55), and statistical analyses in our PLoS Computational Biology paper (http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002916).


Domain


The domain model captures an abstraction of the biological domain. The state diagrams, created using a modified version of Unified Modelling language, provide a description of the states in which the identified agents (cell type) may exist within (the boxes), and the biological event that must take place for that agent to transition into the next state (the arrow). This does not contain any simulation-specific detail.

An Activity Diagram also forms part of this model, representing the low-level interactions between the cells (LTin, LTi, LTo Cell) which lead to the formation of PP. Cellular behaviours are described in boxes, decisions points indicated by diamonds and lines. Arrows indicate potential changes to cellular behaviour.

Domain Diagrams can be seen in the Frontiers in Immunology methods paper (http://www.frontiersin.org/Inflammation/abstract/22737)

Platform

The Platform model details how the states and interactions captured in the domain model are coded into the simulation. The expected behaviour, which emerges from interactions between components in the system, is specifically not present in the platform model. Behaviour emerges from the simulation and are not coded into the simulation. In the platform model, how each cell behaves and how interactions are encoded is detailed. As this includes a variety of factors from the domain model a number of assumptions are made and documented.

Again all diagrams and specifications can be seen in the Frontiers in Immunology methods paper (http://www.frontiersin.org/Inflammation/abstract/22737)

Assumptions


Although in theory including all current understanding of a system is possible, such a model would be very difficult to construct and is unlikely to significantly improve the model. Therefore, the domain model is an abstraction of the biological system, with suitable assumptions made where necessary and clearly documented for later scrutiny.

Further parameters are identified in forming the Platform Model and described, and as in the domain model the numerical values of some parameters are unknown. These parameters may capture the behaviour of component parts such as adhesion molecules, cytokines, and chemokines. Despite the importance of these factors, the number of molecules expressed by the different cell types, the level of chemokine expression required to induce cellular chemotaxis and the diffusion distribution of chemokines and cytokines in the localised environment all are currently unknown. Thus further assumptions are made based on known biology and documented.

Link to PPSim Assumptions Table (PDF in PPSim folder on Dropbox)

Simulator

The simulator has been created in Java and utilises the MASON Simulation toolkit. This is run from the command line utilising the instructions that can be downloaded below.

Three links: PPSim Simulator, PPSim Parameters file,  and PPSim Instructions

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