Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.
Skip to main content

CXCL13Sim is a hybrid multiscale simulator that captures the migration of B cells in response to the chemokine CXCL13 within a lymph node follicle. In the tabs below we provide the source code for the simulator, an argumentation structure to present information used to inform the design, development and validation of the simulator. In addition we present the CXCL13emulator, a neural-network based software tool in R, that we use to enrich the analysis of the original simulator.

Software Platform

The simulator has been created in Java and utilises the MASON Simulation toolkit and Java3D. The computer code has been provided below with information about the simulator provided in a .pdf file. There is also a link to download the simulator from bitbucket.

Link to download simulator: https://bitbucket.org/ycil/cxcl13sim/overview

Argumentation Structures

The design and implementation decisions made when constructing a simulator are influenced by the overarching scientific objectives of the work, with simulation results interpreted in this context. To argue that the simulator fulfils its remit, acceptance tests, key design decisions, and information used to inform the design, development and validation of the model and simulation are presented as arguments over evidence using a visual notation derived from goal structuring notation and can be opened using the ARTOO tool (http://php.york.ac.uk/fs/elec551/artoo/argumentation.html). This diagrammatic tool facilitates transparency of model design and analysis, capturing the reasoning behind the inclusion or exclusion of each biological feature and recording assumptions, as well as pointing to evidence supporting model-derived conclusions.

Emulator Platform

To evaluate the CXCL13 simulator, and translate results back to the biological domain, we perform a suite of statistical analyses. However, many analyses may become intractable due to time and resource limitations. To address this we apply emulation to enrich understanding of the CXCL13 simulator, showing that a neural network can quickly and accurately reproduce the key emergent properties of the simulator allowing us to perform additional analyses that were previously too resource intensive to perform. In the folder below we provide an example script to run the emulator using the statistical analysis software R.