Paper Published in IEEE Transactions on Computational Biology and Bioinformatics

Posted on 27 January 2016

Recent Work on Biphasic Biological Models Accepted for Publishing in IEEE Journal

Recent work led by Kieran Alden has been accepted for publishing in the IEEE Journal Transactions on Computational Biology and Bioinformatics.

This paper focuses on using simulation as a tool for performing time lapse experiments, and uses our Secondary Lymphoid Organ development study as an exemplar of this approach. By performing analyses at multiple simulation timepoints, we have been able to suggest that SLO development may be biphasic, with different pathways being most influential in each. To encourage wider adoption of this approach, the paper describes how we have extended functionality in our Spartan package to permit this type of analysis on other models.

The full paper, entitled "Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models" will appear in pre-print version this week. The final version will be made available here once this is made available.

Paper Abstract:

Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behaviour
exhibited by a computational model at various simulated timepoints, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve-hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.