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Incremental and unifying modelling formalism for biological interaction networks.

Yartseva A, Klaudel H, Devillers R, Képès F - BMC Bioinformatics (2007)

Bottom Line: We also show how to extract from our model a classical ODE description of the dynamics of a system.This approach provides an additional level of description between the biological and mathematical ones.It yields, on the one hand, a knowledge expression in a form which is intuitive for biologists and, on the other hand, its representation in a formal and structured way.

View Article: PubMed Central - HTML - PubMed

Affiliation: IBISC - Université d'Evry Val d'Essonne, Tour Evry 2, 523 place des Terrasses de l'Agora, F-91000 Evry, France. iartseva@gmail.com

ABSTRACT

Background: An appropriate choice of the modeling formalism from the broad range of existing ones may be crucial for efficiently describing and analyzing biological systems.

Results: We propose a new unifying and incremental formalism for the representation and modeling of biological interaction networks. This formalism allows automated translations into other formalisms, thus enabling a thorough study of the dynamic properties of a biological system. As a first illustration, we propose a translation into the R. Thomas' multivalued logical formalism which provides a possible semantics; a methodology for constructing such models is presented on a classical benchmark: the lambda phage genetic switch. We also show how to extract from our model a classical ODE description of the dynamics of a system.

Conclusion: This approach provides an additional level of description between the biological and mathematical ones. It yields, on the one hand, a knowledge expression in a form which is intuitive for biologists and, on the other hand, its representation in a formal and structured way.

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The multivalued logical approximation of the level of activity of biological objects. The axes represent input (abscissa) and output (ordinate) protein concentrations. The dashed thin sigmoid curve represents [CI] – the measured concentration of the protein CI at the equilibrium point. This curve is approximated by the thick dashed multivalued logical function with the threshold θ1. The solid curve corresponds to the influence of [CI] on [CRO] and its approximation by the multivalued logical function with the threshold θ2. In this case the activity of the protein CI has three logical levels: 0, 1 and 2, indicated in the bottom part and separated by the thresholds.
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Figure 6: The multivalued logical approximation of the level of activity of biological objects. The axes represent input (abscissa) and output (ordinate) protein concentrations. The dashed thin sigmoid curve represents [CI] – the measured concentration of the protein CI at the equilibrium point. This curve is approximated by the thick dashed multivalued logical function with the threshold θ1. The solid curve corresponds to the influence of [CI] on [CRO] and its approximation by the multivalued logical function with the threshold θ2. In this case the activity of the protein CI has three logical levels: 0, 1 and 2, indicated in the bottom part and separated by the thresholds.

Mentions: The multivalued logical approach is designed to express the interdependency between activity levels (often concentrations) of biological objects, e.g., proteins. It applies when this interdependency can be represented by a sigmoidal curve, which is approximated by a multivalued logical function. This function can distinguish between different levels of activity of a biological object, so it may be multivalued (see Figure 6). The multivalued logical model (MLM) consists of two parts: a directed graph of interactions and a table of dynamic parameters.


Incremental and unifying modelling formalism for biological interaction networks.

Yartseva A, Klaudel H, Devillers R, Képès F - BMC Bioinformatics (2007)

The multivalued logical approximation of the level of activity of biological objects. The axes represent input (abscissa) and output (ordinate) protein concentrations. The dashed thin sigmoid curve represents [CI] – the measured concentration of the protein CI at the equilibrium point. This curve is approximated by the thick dashed multivalued logical function with the threshold θ1. The solid curve corresponds to the influence of [CI] on [CRO] and its approximation by the multivalued logical function with the threshold θ2. In this case the activity of the protein CI has three logical levels: 0, 1 and 2, indicated in the bottom part and separated by the thresholds.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2200675&req=5

Figure 6: The multivalued logical approximation of the level of activity of biological objects. The axes represent input (abscissa) and output (ordinate) protein concentrations. The dashed thin sigmoid curve represents [CI] – the measured concentration of the protein CI at the equilibrium point. This curve is approximated by the thick dashed multivalued logical function with the threshold θ1. The solid curve corresponds to the influence of [CI] on [CRO] and its approximation by the multivalued logical function with the threshold θ2. In this case the activity of the protein CI has three logical levels: 0, 1 and 2, indicated in the bottom part and separated by the thresholds.
Mentions: The multivalued logical approach is designed to express the interdependency between activity levels (often concentrations) of biological objects, e.g., proteins. It applies when this interdependency can be represented by a sigmoidal curve, which is approximated by a multivalued logical function. This function can distinguish between different levels of activity of a biological object, so it may be multivalued (see Figure 6). The multivalued logical model (MLM) consists of two parts: a directed graph of interactions and a table of dynamic parameters.

Bottom Line: We also show how to extract from our model a classical ODE description of the dynamics of a system.This approach provides an additional level of description between the biological and mathematical ones.It yields, on the one hand, a knowledge expression in a form which is intuitive for biologists and, on the other hand, its representation in a formal and structured way.

View Article: PubMed Central - HTML - PubMed

Affiliation: IBISC - Université d'Evry Val d'Essonne, Tour Evry 2, 523 place des Terrasses de l'Agora, F-91000 Evry, France. iartseva@gmail.com

ABSTRACT

Background: An appropriate choice of the modeling formalism from the broad range of existing ones may be crucial for efficiently describing and analyzing biological systems.

Results: We propose a new unifying and incremental formalism for the representation and modeling of biological interaction networks. This formalism allows automated translations into other formalisms, thus enabling a thorough study of the dynamic properties of a biological system. As a first illustration, we propose a translation into the R. Thomas' multivalued logical formalism which provides a possible semantics; a methodology for constructing such models is presented on a classical benchmark: the lambda phage genetic switch. We also show how to extract from our model a classical ODE description of the dynamics of a system.

Conclusion: This approach provides an additional level of description between the biological and mathematical ones. It yields, on the one hand, a knowledge expression in a form which is intuitive for biologists and, on the other hand, its representation in a formal and structured way.

Show MeSH