Qualitative modelling of regulated metabolic pathways: application to the tryptophan biosynthesis in <i>E.Coli</i>

Simão, Éder Maiquel; Rémy, Élisabeth; Thieffry, Denis; Chaouiya, Claudine

doi:10.1093/bioinformatics/bti1130

Cited by 75 publications

(47 citation statements)

References 15 publications

(20 reference statements)

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“…The regulation of the responses of a biological system to various perturbations can be described in terms of gene networks and metabolic networks, for example, in qualitative modeling of regulated metabolic pathways (e.g. Simao et al, 2005). Predictive whole-cell metabolic models Figure 1 Bottom-up and top-down approaches in systems biology.…”

Section: Modelingmentioning

confidence: 99%

Systems biology in animal sciences

Woelders

Pas

Bannink

et al. 2011

Animal

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Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.

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Section: Modelingmentioning

confidence: 99%

Systems biology in animal sciences

Woelders

Pas

Bannink

et al. 2011

Animal

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“…We have shown that rule-based modeling provides concise and elegant models for the fine-grained mechanism of transcriptional attenuation, a problem left open by previous work on discrete event modeling of the tryptophan operon (Simão et al 2005). The core ingredient for our model are rule schemas and n-ary chemical reactions.…”

Section: Simulationmentioning

confidence: 99%

Rule-based modeling of transcriptional attenuation at the tryptophan operon

Kuttler

Lhoussaine

Nebut

2009

Proceedings of the 2009 Winter Simulation Conference (WSC)

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To cite this version:Celine Kuttler, Cédric Lhoussaine, Mirabelle Nebut. Rule-based modeling of transcriptional attenuation at the tryptophan operon. ABSTRACTTranscriptional attenuation at E.coli's tryptophan operon is a prime example of RNA-mediated gene regulation. In this paper, we present a discrete stochastic model of the fine-grained control of attenuation, based on chemical reactions. Stochastic simulation of our model confirms results that were previously obtained by master or differential equations. Our approach is easier to understand than master equations, although mathematically well founded. It is compact due to rule schemas that define finite sets of chemical reactions. Moreover, our model makes intense use of reaction rules with more than two reactants. As we show, such n-ary rules are essential to concisely capture the control of attenuation. Our model could not adequately be represented in object-centered modeling languages based on the pi-calculus, because these are limited to binary interactions.

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“…To address these problems, we propose a new model for genetic regulatory networks based on Petri nets [21,18], a well developed formal framework for modelling and analysing complex concurrent systems [22,28]. A range of initial investigations into using Petri nets to model biological systems have appeared in the literature to date, including: Place/Transition nets [19,5,25,12]; stochastic nets [9,24]; high-level nets [11,6]; and hybrid nets [17]. The results we present significantly extend the related ideas presented in [5], both semantically and in the provision of automated tool support for model construction and analysis.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Analysing Genetic Networks: From Boolean Networks to Petri Nets

Steggles

Banks

Wipat

2006

Computational Methods in Systems Biology

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Abstract. In order to understand complex genetic regulatory networks researchers require automated formal modelling techniques that provide appropriate analysis tools. In this paper we propose a new qualitative model for genetic regulatory networks based on Petri nets and detail a process for automatically constructing these models using logic minimization. We take as our starting point the Boolean network approach in which regulatory entities are viewed abstractly as binary switches. The idea is to extract terms representing a Boolean network using logic minimization and to then directly translate these terms into appropriate Petri net control structures. The resulting compact Petri net model addresses a number of shortcomings associated with Boolean networks and is particularly suited to analysis using the wide range of Petri net tools. We demonstrate our approach by presenting a detailed case study in which the genetic regulatory network underlying the nutritional stress response in Escherichia coli is modelled and analysed.

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Qualitative modelling of regulated metabolic pathways: application to the tryptophan biosynthesis in E.Coli

Abstract: The software GINsim for the logical modelling of genetic regulatory networks together with the PN model of the regulated Trp biosynthesis pathway are available at: http://gin.univ-mrs.fr/GINsim.

Cited by 75 publications

References 15 publications

Systems biology in animal sciences

Systems biology in animal sciences

Rule-based modeling of transcriptional attenuation at the tryptophan operon

Modelling and Analysing Genetic Networks: From Boolean Networks to Petri Nets

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