This paper presents a new and general approach for analyzing the stability of a large class of biological networks, modeled as autonomous systems of differential equations, using real solving and solution classification. The proposed approach, based on the classical technique of linearization from the qualitative theory of ordinary differential equations yet with exact symbolic computation, is applied to analyzing the local stability of the Cdc2-cyclin B/Wee1 system and the Mos/MEK/p42 MAPK cascade, two well-known models for cell and protein signaling that have been studied extensively in the literature. We provide rigorous proofs and generalizations for some of the previous results established experimentally and report our new findings. Co...
Abstract. Analyzing qualitative behaviors of biochemical reactions using its associated network stru...
In this paper, we study qualitative behavior of a network of two genes repressing each other. More p...
The inference of large-scale gene regulatory networks from high-throughput data sets has revealed a ...
International audienceThis paper is concerned with stability analysis of biological networks modeled...
Abstract. We consider a class of systems of differential equations with quadratic nonlinear-ities. T...
We consider a class of systems of differential equations with quadratic nonlinearities. Th...
Abstract. The stability of biological models is an important test for es-tablishing their soundness ...
Parameter perturbations in dynamical models of biochemical networks affect the qualitative dynamical...
Background: The molecular circuitry of living organisms performs remarkably robust regulatory tasks,...
AbstractWe study stability properties of a class of piecewise affine systems of ordinary differentia...
Abstract—Stochastic differential equations are now commonly used to model biomolecular networks in s...
Advances in high‐resolution microscopy and other techniques have emphasized the spatio‐temporal natu...
The MAPK cascade is responsible for transmitting information in the cytoplasm of the cell and regula...
In this paper, we establish stability conditions for a special class of interconnected systems aris...
In this chapter, we describe general methods used to create dynamic computational models of kinase s...
Abstract. Analyzing qualitative behaviors of biochemical reactions using its associated network stru...
In this paper, we study qualitative behavior of a network of two genes repressing each other. More p...
The inference of large-scale gene regulatory networks from high-throughput data sets has revealed a ...
International audienceThis paper is concerned with stability analysis of biological networks modeled...
Abstract. We consider a class of systems of differential equations with quadratic nonlinear-ities. T...
We consider a class of systems of differential equations with quadratic nonlinearities. Th...
Abstract. The stability of biological models is an important test for es-tablishing their soundness ...
Parameter perturbations in dynamical models of biochemical networks affect the qualitative dynamical...
Background: The molecular circuitry of living organisms performs remarkably robust regulatory tasks,...
AbstractWe study stability properties of a class of piecewise affine systems of ordinary differentia...
Abstract—Stochastic differential equations are now commonly used to model biomolecular networks in s...
Advances in high‐resolution microscopy and other techniques have emphasized the spatio‐temporal natu...
The MAPK cascade is responsible for transmitting information in the cytoplasm of the cell and regula...
In this paper, we establish stability conditions for a special class of interconnected systems aris...
In this chapter, we describe general methods used to create dynamic computational models of kinase s...
Abstract. Analyzing qualitative behaviors of biochemical reactions using its associated network stru...
In this paper, we study qualitative behavior of a network of two genes repressing each other. More p...
The inference of large-scale gene regulatory networks from high-throughput data sets has revealed a ...