![[Created with Vim]](img/created-with-vim.png "Created with Vim")
![[Viewable With Any Browser]](img/w3c_ab.png "Viewable With Any Browser")
![[Valid CSS!]](img/vcss.png "Valid CSS!")
![[Valid XHTML 1.1!]](img/valid-xhtml11.png "Valid XHTML 1.1!")
![[Get Firefox!]](http://sfx-images.mozilla.org/affiliates/Buttons/88x31/get.gif "Get Firefox!")
webmaster
We present an approach to compose dynamic models of gene regulatory networks from simple computational elements. Each such element is termed a gene gate and defines an input/outputrelationship corresponding to the fixing and production of transcription factors. We illustrate the approach by gene gates whose output is repressed upon transcription factor binding and study the dynamics of the simplest three circuits that can be built from repressed gates alone: the autoinhibitory loop, the bistable switch and the repressilator. The proposed gene gate kinetics can be mapped onto rate equations and stochastic processes. In the deterministic case, switching of the bistable switch and oscillations in the repressilator require cooperativity in transcription factor binding. By contrast, the stochastic versions of both circuits generate switching and oscillatory time-series without cooperativity, and do so over wide ranges of parameters.
Type checking and type inference are important concepts and methods of programming languages and software engineering. In this talk, we investigate the application of these concepts to systems biology. More specifically, we consider the Systems Biology Markup Language SBML and the Biochemical Abstract Machine BIOCHAM with their repositories of models of biochemical systems. We study three type systems: one for checking or inferring the functions of proteins in a reaction model, one for checking or inferring the activation and inhibition effects of proteins in a reaction model, and another one for checking or inferring the topology of locations. We show that the framework of abstract interpretation elegantly applies to the formalization of these abstractions and to the implementation of linear time type inference algorithms. Through some examples, we show that the analysis of biochemical models by type inference provides accurate and useful information, and that such a mathematical formalization of the abstractions used in systems biology already provides some guidelines for the extension of biochemical reaction rule languages. Interestingly, it also leads to a relative notion of modularity w.r.t. different abstractions.
On modélise les interactions des gènes dans plusieurs cellules localisées sur une grille infinie de dimension 2, puis on montre que la présence d'un circuit positif est une condition nécéssaire pour l'existence d'un état stable.