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Regulatory networks are complex networks. This paper addresses the challenge of modelling these networks. The Boolean representation is chosen and supported as a suitable representation for an abstract approach. In in-silico experiments, two different bio-inspired techniques are applied to the reverse engineering of a Boolean regulatory network: as a search method a Genetic Algorithm is applied and...
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