A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspi
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SURVEY PAPER
A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models Roberto Barbuti1 · Roberta Gori1 · Paolo Milazzo1 · Lucia Nasti1 Received: 14 March 2020 / Accepted: 13 August 2020 © The Author(s) 2020
Abstract Gene Regulatory Networks (GRNs) represent the interactions among genes regulating the activation of specific cell functionalities, such as reception of (chemical) signals or reaction to environmental changes. Studying and understanding these processes is crucial: they are the fundamental mechanism at the basis of cell functioning, and many diseases are based on perturbations or malfunctioning of some gene regulation activities. In this paper, we provide an overview on computational approaches to GRN modelling and analysis. We start from the biological and quantitative modelling background notions, recalling differential equations and the Gillespie’s algorithm. Then, we describe more in depth qualitative approaches such as Boolean networks and some computer science formalisms, including Petri nets, P systems and reaction systems. Our aim is to introduce the reader to the problem of GRN modelling and to guide her/him along the path that goes from classical quantitative methods, through qualitative methods based on Boolean network, up to some of the most relevant qualitative computational methods to understand the advantages and limitations of the different approaches. Keywords Gene regulatory networks · Boolean networks · Petri nets · Reaction systems · Membrane systems
1 Introduction Gene Regulatory Networks (GRNs) [81] are the mechanism that allows cells to react to environmental changes such as the availability of a new nutrient or the reception of a (chemical) signal from other cells. A cell activates a new function by starting synthesizing different proteins. Indeed, proteins are the actuators of cell functions and each protein plays a rather specific role. The synthesis of proteins is based on genes, through the transcription (synthesis of Roberto Barbuti, Roberta Gori, PaoloMilazzo and Lucia Nasti contributed equally. * Paolo Milazzo [email protected] Roberto Barbuti [email protected] Roberta Gori [email protected] Lucia Nasti [email protected] 1
Dipartimento di Informatica, Università di Pisa, Pisa, Italy
RNA from DNA) and translation (synthesis of proteins from RNA) processes. The activation of a new cell function corresponds to the activation of the transcription and translation mechanisms. With a little simplification, each gene can be considered in active or inactive state depending on whether the corresponding protein is expressed (i.e. synthesized) or not. This allows mapping cell functionalities to specific configurations of genes activation. Since each cell functionality is often associated to a large number of genes, its activation has to be properly coordinated. This is obtained through a distributed process in which genes mutually regulate their activation. Interactions among genes via proteins
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