Narrative-based Computational Modelling of the Gp130/JAK/STAT Signalling Pathway

Appropriately formulated quantitative computational models can support researchers in understanding the dynamic behaviour of biological pathways and support hypothesis formulation and selection by “in silico” experimentation. An obstacle to widespread adoption of this approach is the requirement to formulate a biological pathway as machine executable computer code. We have proposed a novel, biologically intuitive, narrative-style modelling language for biologists to formulate the pathway which is then automatically translated into an executable format. We introduce this approach by presenting a computational model of the gp130/JAK/STAT signalling pathway derived from a biological narrative and show that the model reproduces the dynamic behaviour of the pathway derived by biological observation. We then “experiment” on the model by simulation and sensitivity analysis to define those parameters which dominate the dynamic behaviour of the pathway. The model predicts that nuclear compartmentalisation and phosphorylation status of STAT are key determinants of the pathway and that alternative mechanisms of signal attenuation exert their influence on different timescales. This is the preliminary version of a paper that was published in BMC Systems Biology, 3:40, 2009. The original publication is available at http://www.biomedcentral.com/1752-0509/3/40