Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Checking properties of nets using transformation
Advances in Petri Nets 1985, covers the 6th European Workshop on Applications and Theory in Petri Nets-selected papers
Property Preserving Homomorphisms of Transition Systems
Proceedings of the Carnegie Mellon Workshop on Logic of Programs
Abstract interpretation and types for systems biology
Theoretical Computer Science
Automated symbolic reachability analysis: with application to delta-notch signaling automata
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Decision diagrams for the representation and analysis of logical models of genetic networks
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Petri net representation of multi-valued logical regulatory graphs
Natural Computing: an international journal
Logical modelling of haematopoietic cell fate reprogramming
Proceedings of the 9th International Conference on Computational Methods in Systems Biology
Parameter identification and model ranking of thomas networks
CMSB'12 Proceedings of the 10th international conference on Computational Methods in Systems Biology
Efficient handling of large signalling-regulatory networks by focusing on their core control
CMSB'12 Proceedings of the 10th international conference on Computational Methods in Systems Biology
Interconnection of asynchronous Boolean networks, asymptotic and transient dynamics
Automatica (Journal of IFAC)
Hi-index | 5.23 |
To cope with the increasing complexity of regulatory networks, we define a reduction method for multi-valued logical models. Starting with a detailed model, we use decision diagrams to compute reduced models by iteratively ''removing'' regulatory components. To keep a consistent dynamical behaviour, the logical rules associated with the targets of each removed node are actualised to account for the (indirect) effects of its regulators. This construction of reduced models preserves crucial dynamical properties of the original model, including stable states and more complex attractors. In this respect, the relationship between the attractor configuration of the original model and those of reduced models is formally established. We further analyse the issue of attractor reachability. Finally, we illustrate the flexibility and efficiency of the proposed reduction method by its application to a multi-valued model of the fly segment polarity network, which is involved in the control of segmentation during early embryogenesis.