Reactive Models for Biological Regulatory Networks

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Abstract

A reactive model, as studied by D. Gabbay and his collaborators, can be regarded as a graph whose set of edges may be altered whenever one of them is crossed. In this paper we show how reactive models can describe biological regulatory networks and compare them to Boolean networks and piecewise-linear models, which are some of the most common kinds of models used nowadays. In particular, we show that, with respect to the identification of steady states, reactive Boolean networks lie between piecewise linear models and the usual, plain Boolean networks. We also show this ability is preserved by a suitable notion of bisimulation, and, therefore, by network minimisation.

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Figueiredo, D., & Barbosa, L. S. (2019). Reactive Models for Biological Regulatory Networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11415 LNCS, pp. 74–88). Springer Verlag. https://doi.org/10.1007/978-3-030-19432-1_5

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