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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.

Show MeSH
Differential equations obtained by an automatic translation of the MIN model in Figure 4. Functions f and g come, on one hand, from the MIN topology and the information on the stoichiometry of the reaction, and on the other hand, from the reaction attribute. At this stage, the coherence of both informations should be checked by an expert. In these equations f and g have a definite signature reflecting the impact of the catalyzers and inhibitors on the reactions.
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Figure 12: Differential equations obtained by an automatic translation of the MIN model in Figure 4. Functions f and g come, on one hand, from the MIN topology and the information on the stoichiometry of the reaction, and on the other hand, from the reaction attribute. At this stage, the coherence of both informations should be checked by an expert. In these equations f and g have a definite signature reflecting the impact of the catalyzers and inhibitors on the reactions.

Mentions: A MIN model detailed enough to be directly translated to ODEs is presented in Figure 4. For each chemical species in Figure 4 we can write a differential equation summing its consumption and production in chemical reactions the species is participating (see Figure 12). If the additional information is available and encoded in MIN in attributes such as ki and Kaff, they will be used in the translation to ODEs procedure. If this information is not available, a free constant denoted in a standard way will be generated. The stoichiometric coefficients give the αi power coefficients in the formula, and the kj reaction rates come form the corresponding reaction attributes.


Incremental and unifying modelling formalism for biological interaction networks.

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

Differential equations obtained by an automatic translation of the MIN model in Figure 4. Functions f and g come, on one hand, from the MIN topology and the information on the stoichiometry of the reaction, and on the other hand, from the reaction attribute. At this stage, the coherence of both informations should be checked by an expert. In these equations f and g have a definite signature reflecting the impact of the catalyzers and inhibitors on the reactions.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 12: Differential equations obtained by an automatic translation of the MIN model in Figure 4. Functions f and g come, on one hand, from the MIN topology and the information on the stoichiometry of the reaction, and on the other hand, from the reaction attribute. At this stage, the coherence of both informations should be checked by an expert. In these equations f and g have a definite signature reflecting the impact of the catalyzers and inhibitors on the reactions.
Mentions: A MIN model detailed enough to be directly translated to ODEs is presented in Figure 4. For each chemical species in Figure 4 we can write a differential equation summing its consumption and production in chemical reactions the species is participating (see Figure 12). If the additional information is available and encoded in MIN in attributes such as ki and Kaff, they will be used in the translation to ODEs procedure. If this information is not available, a free constant denoted in a standard way will be generated. The stoichiometric coefficients give the αi power coefficients in the formula, and the kj reaction rates come form the corresponding reaction attributes.

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