Reasoning and hypothesizing about signaling networks
Reasoning and hypothesizing about signaling networks
Engineering an Incremental ASP Solver
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Metabolic Network Expansion with Answer Set Programming
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Modeling Protein Interaction Networks with Answer Set Programming
BIBM '09 Proceedings of the 2009 IEEE International Conference on Bioinformatics and Biomedicine
Clasp: a conflict-driven answer set solver
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Process algebras in systems biology
SFM'08 Proceedings of the Formal methods for the design of computer, communication, and software systems 8th international conference on Formal methods for computational systems biology
International Journal of Data Mining and Bioinformatics
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Recently, many approaches to model regulatory networks have been proposed in the systems biology domain. However, the task is far from being solved. In this paper, we propose an Answer Set Programming (ASP)-based approach to model interaction networks. We build a general ASP framework that describes the network semantics and allows modelling specific networks with little effort. ASP provides a rich and flexible toolbox that allows expanding the framework with desired features. In this paper, we tune our framework to mimic Boolean network behaviour and apply it to model the Budding Yeast and Fission Yeast cell cycle networks. The obtained steady states of these networks correspond to those of the Boolean networks.