In this paper, we address the problem of modeling biological regulatory networks thanks to the stochastic π-calculus. We propose a method which extends a ...
Abstract. In this paper, we address the problem of modeling biological regulatory networks thanks to the stochastic π-calculus. We propose a.
In this paper, we address the problem of modeling biological regulatory networks thanks to the stochastic π-calculus. We propose a method which extends a ...
In this paper, we address the problem of modeling biological regulatory networks thanks to the stochastic π -calculus. We propose a method which extends a ...
A framework allowing to model and analyse efficiently Gene Regulatory Networks (GRNs) in their temporal and stochastic aspects is introduced and a ...
Feb 18, 2014 · Abstract. In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks (GRNs) in their tem-.
Moving to the network level, we develop a general model of gene regulatory networks using affinity patterns and an expanded Hill kinetic law. We illustrate the ...
Goal: temporal parameters synthesis for hybrid models of GRN. Contrib: introduction of temporal and stochastic parameters within π-calculus models of GRN. 2 ...
Gene regulation processes are inherently stochastic. Accurately modeling this stochasticity is a complex and important goal in molecular system biology.
Missing: Calculus. | Show results with:Calculus.
ple, mathematical modeling of gene regulatory network dynamics can provide a theoretical foundation for understanding cell heterogeneity and gene expression ...
Missing: Calculus. | Show results with:Calculus.