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

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

Identyfikatory

DOI

10.3233/FI-2021-2021

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

gene regulatory networks; genetic regulation; biological systems; biological networks; escherichia coli; biological models

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2021
• Tom: Vol. 179, nr 2
• Strony: 205--225
• Opis fizyczny: Bibliogr. 34 poz., rys.

Twórcy

autor

Barbuti Roberto

• Dipartimento di Informatica, Università di Pisa, Italy

autor

Bove Pasquale

• Dipartimento di Informatica, Università di Pisa, Italy

autor

Gori Roberta

• Dipartimento di Informatica, Università di Pisa, Italy

autor

Gruska Damas

• Department of Applied Informatics, Comenius University in Bratislava, Slovak Republic

autor

Levi Francesca

• Dipartimento di Informatica, Università di Pisa, Italy

autor

Milazzo Paolo

• Dipartimento di Informatica, Università di Pisa, Italy

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).