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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.

Comparison of selected performances of biological and electronic information processing structures

Moškon M., Zimic N., Stražar M., Mraz M.

Przegląd Elektrotechniczny

2013

R. 89, nr 2a

166--169

We present the information processing perspective on biological systems. Several metrics, similar to the ones used in digital electronic circuits, are introduced. These metrics allow us to compare biological information processing structures with their electronic counterparts, to define the ones with the best dynamical properties, analyse their compatibility and most importantly, automatize their design. Regarding the metric values obtained and used on a simple example, target applications of synthetic information processing biological structures are discussed.

W artykule opisano zagadnienie przepływu informacji w systemach biologicznych. Zastosowano tu odwzorowanie na elementach i obwodach elektronicznych, co pozwoliło na analizę ich własności, w tym dynamicznych oraz zautomatyzowanie projektowania takich modeli. Zawarto także omówienie otrzymanych wyników badań.