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Encoding Threshold Boolean Networks into Reaction Systems for the Analysis of Gene Regulatory Networks

Barbuti Roberto, Bove Pasquale, Gori Roberta, Gruska Damas, Levi Francesca, Milazzo Paolo

Fundamenta Informaticae

2021

Vol. 179, nr 2

205--225

Gene regulatory networks represent the interactions among genes regulating the activation of specific cell functionalities and they have been successfully modeled using threshold Boolean networks. In this paper we propose a systematic translation of threshold Boolean networks into reaction systems. Our translation produces a non redundant set of rules with a minimal number of objects. This translation allows us to simulate the behavior of a Boolean network simply by executing the (closed) reaction system we obtain. This can be very useful for investigating the role of different genes simply by “playing” with the rules. We developed a tool able to systematically translate a threshold Boolean network into a reaction system. We use our tool to translate two well known Boolean networks modelling biological systems: the yeast-cell cycle and the SOS response in Escherichia coli. The resulting reaction systems can be used for investigating dynamic causalities among genes.

Studying Opacity of Reaction Systems through Formula Based Predictors

Gori Roberta, Gruska Damas, Milazzo Paolo

Fundamenta Informaticae

2019

Vol. 165, nr 3-4

303--319

Reaction systems are a qualitative formalism for modeling systems of biochemical reactions. They describe the evolution of sets of objects representing biochemical molecules. One of the main characteristics of Reaction systems is the non-permanency of the objects, namely objects disappear if not produced by any enabled reaction. Reaction systems execute in an environment that provides new objects at each step. Causality properties of reaction systems can be studied by using notions of formula based predictor. In this context, we define a notion of opacity that can be used to study information flow properties for reaction systems. Objects will be partitioned into high level (invisible) and low level (visible) ones. Opacity ensures that the presence (or absence) of high level objects cannot be guessed observing the low level objects only. Such a property is shown to be decidable and computable by exploiting the algorithms for minimal formula based predictors.