When designing genetic circuits, the typical primitives used in major existing modelling formalisms are gene interaction graphs, where edges between genes denote either an activation or inhibition relation. However, when designing experiments, it is important to be precise about the low-level mechanistic details as to how each such relation is implemented. The rule-based modelling language Kappa allows to unambiguously specify mechanistic details such as DNA binding sites, dimerisation of transcription factors, or co-operative interactions. Such a detailed description comes with complexity and computationally costly executions. We propose a general method for automatically transforming a rule-based program, by eliminating intermediate species and adjusting the rate constants accordingly. To the best of our knowledge, we show the first automated reduction of rule-based models based on equilibrium approximations. Our algorithm is an adaptation of an existing algorithm, which was designed for reducing reaction-based programs; our version of the algorithm scans the rule-based Kappa model in search for those interaction patterns known to be amenable to equilibrium approximations (e.g. Michaelis-Menten scheme). Additional checks are then performed in order to verify if the reduction is meaningful in the context of the full model. The reduced model is efficiently obtained by static inspection over the rule-set. The tool is tested on a detailed rule-based model of a λ-phage switch, which lists 92 rules and 13 agents. The reduced model has 11 rules and 5 agents, and provides a dramatic reduction in simulation time of several orders of magnitude.
This research was supported by the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. 291734, and the SNSF Early Postdoc.Mobility Fellowship, the grant number P2EZP2_148797.
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HSB: Hybrid Systems Biology
2015-09-04 – 2015-09-05
Beica A, Guet CC, Petrov T. Efficient reduction of kappa models by static inspection of the rule-set. In: Vol 9271. Springer; 2016:173-191. doi:10.1007/978-3-319-26916-0_10
Beica, A., Guet, C. C., & Petrov, T. (2016). Efficient reduction of kappa models by static inspection of the rule-set (Vol. 9271, pp. 173–191). Presented at the HSB: Hybrid Systems Biology, Madrid, Spain: Springer. https://doi.org/10.1007/978-3-319-26916-0_10
Beica, Andreea, Calin C Guet, and Tatjana Petrov. “Efficient Reduction of Kappa Models by Static Inspection of the Rule-Set,” 9271:173–91. Springer, 2016. https://doi.org/10.1007/978-3-319-26916-0_10.
A. Beica, C. C. Guet, and T. Petrov, “Efficient reduction of kappa models by static inspection of the rule-set,” presented at the HSB: Hybrid Systems Biology, Madrid, Spain, 2016, vol. 9271, pp. 173–191.
Beica A, Guet CC, Petrov T. 2016. Efficient reduction of kappa models by static inspection of the rule-set. HSB: Hybrid Systems Biology, LNCS, vol. 9271, 173–191.
Beica, Andreea, et al. Efficient Reduction of Kappa Models by Static Inspection of the Rule-Set. Vol. 9271, Springer, 2016, pp. 173–91, doi:10.1007/978-3-319-26916-0_10.