Determination, Optimization and Taxonomy of Regulatory Networks: The Example of Arabidopsis thaliana Flower Morphogenesis

This paper aims at warning modellers in systems biology against several traps encountered in the modelling of Boolean thresholded automata networks, i.e. the Hopfield-like networks that are often used in the context of neural and genetic networks. It introduces a new manner based on inverse methods to conceive such models. Using these techniques, we re-visit the model of regulatory network of Arabidopsis thaliana morphogenetic network. In this context, we discuss about the non-uniqueness of models, on a possible taxonomy of the set of valid models and on the sense of the relative size of the basin of attractions within or between these models.

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