title: Incremental and unifying modelling formalism for biological interaction networks.
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.
  
  
  CONCLUSIONS
  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.
authors.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
authors.forename: Anastasia
authors.initials: A
authors.lastname: Yartseva
authors.forename: Hanna
authors.initials: H
authors.lastname: Klaudel
authors.forename: Raymond
authors.initials: R
authors.lastname: Devillers
authors.forename: François
authors.initials: F
authors.lastname: Képès
mesh_terms: D000465:Algorithms; D000818:Animals; D010582:Bacteriophage lambda / Q000235:genetics / Q000378:metabolism; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D025461:Feedback, Physiological; D005786:Gene Expression Regulation; D005812:Genes, Switch / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D017711:Nonlinear Dynamics; D025941:Protein Interaction Mapping / Q000379:methods; D012680:Sensitivity and Specificity; D015398:Signal Transduction; D013269:Stochastic Processes; D049490:Systems Biology / Q000379:methods*; D014584:User-Computer Interface