Efficient Handling of Large Signalling-Regulatory Networks by Focusing on Their Core Control
Considering the logical (Boolean or multi-valued) asynchronous framework, we delineate a reduction strategy for large signalling and regulatory networks. Consequently, focusing on the core network that drives the whole dynamics, we can check which attractors are reachable from given initial conditions, under fixed or varying environmental conditions.
More specifically, the dynamics of logical models are represented by (asynchronous) state transition graphs that grow exponentially with the number of model components. We introduce adequate reduction methods (preserving reachability of the attractors) and proceed with model-checking approaches.
Input nodes (that generally represent receptors) and output nodes (that constitute readouts of network behaviours) are each specifically processed to reduce the state space. The proposed approach is made available within GINsim, our software dedicated to the definition and analysis of logical models. The new GINsim functionalities consist in a proper reduction of output components, as well as the corresponding symbolic encoding of logical models for the NuSMV model checker. This encoding also includes a reduction over input components (transferring their values from states to transitions labels). Finally, we demonstrate the interest of the proposed methods through their application to a published large scale model of the signalling pathway involved in T cell activation.
KeywordsQualitative modelling Logical modelling Model checking Regulatory networks Signalling networks
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