Title :

Structural simplification of chemical reaction networks preserving deterministic semantics

Author(s) :

Madelaine, Guillaume [Auteur]
BioComputing
Université de Lille
Lhoussaine, Cedric [Auteur]
BioComputing
Université de Lille
Niehren, Joachim [Auteur]
Linking Dynamic Data [LINKS]
BioComputing

Conference title :

Computational Methods in Systems Biology (CMSB)

Conference organizers(s) :

Jérémie BOURDON
Olivier ROUX

City :

Nantes

Country :

France

Start date of the conference :

2015-09-16

Book title :

Lecture Notes in Computer Science

Journal title :

Lecture Notes in Computer Science

Publisher :

Springer

English keyword(s) :

chemical reaction network
deterministic semantics
structural simplification
equivalence
system biology

HAL domain(s) :

Informatique [cs]/Bio-informatique [q-bio.QM]

English abstract : [en]

We study the structural simplification of chemical reaction networks preserving the deterministic kinetics. We aim at finding simplification rules that can eliminate intermediate molecules while preserving the dynamics of ...
Show more >We study the structural simplification of chemical reaction networks preserving the deterministic kinetics. We aim at finding simplification rules that can eliminate intermediate molecules while preserving the dynamics of all others. The rules should be valid even though the network is plugged into a bigger context. An example is Michaelis-Menten's simplification rule for enzymatic reactions. In this paper, we present a large class of structural simplification rules for reaction networks that can eliminate intermediate molecules at equilibrium, without assuming that all molecules are at equilibrium, i.e. in a steady state. We prove the correctness of our simplification rules for all contexts that preserve the equilibrium of the eliminated molecules. Finally, we illustrate at a concrete example network from systems biology that our simplification rules may allow to drastically reduce the size of reaction networks in practice.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Des modèles de population aux populations de modèles: observation, modélisation et contrôle de l'expression génique au niveau de la cellule unique

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL