A sensitivity analysis of general stoichiometric networks is considered. The results are presented as a generalization of Metabolic Control Analysis, which has been concerned primarily with system sensitivities at steady state. An expression for time-varying sensitivity coefficients is given, and the Summation and Connectivity Theorems are generalized. The results are compared to previous treatments. The analysis is accompanied by a discussion of the computation of the sensitivity coefficients and an application to a model of phototransduction
One of the key challenges in systems biology is the analysis of often complex biochemical reacation ...
Background Stochastic modeling and simulation provide powerful predictive methods for the intrinsic ...
Temperature affects all enzymes simultaneously in a metabolic system. The enzyme concentration in a ...
A frequency domain approach to sensitivity analysis was formulated by Ingalls [1] based on stoichiom...
We study two specific measures of quality of chemical reaction networks, Precision and Sensitivity. ...
Determining the sensitivity of certain system states or outputs to variations in parameters facilita...
Background: Stochastic modeling and simulation provide powerful predictive methods for the intrinsic...
Sensitivity analysis for stochastic chemical reaction networks with multiple time-scales Ankit Gupta...
Determining the sensitivity of certain system states or outputs to variations in parameters facilita...
AbstractWe identify a connection between the structural features of mass-action networks and the rob...
One of the key challenges in systems biology is the analysis of often complex biochemical reacation ...
Stochastic models for chemical reaction networks have become very popular in recent years. For such ...
<div><p>Existing sensitivity analysis approaches are not able to handle efficiently stochastic react...
In biological cells, chemical reaction pathways lead to complex network systems like metabolic netwo...
Metabolic response coefficients describe how variables in metabolic systems, like steady state conce...
One of the key challenges in systems biology is the analysis of often complex biochemical reacation ...
Background Stochastic modeling and simulation provide powerful predictive methods for the intrinsic ...
Temperature affects all enzymes simultaneously in a metabolic system. The enzyme concentration in a ...
A frequency domain approach to sensitivity analysis was formulated by Ingalls [1] based on stoichiom...
We study two specific measures of quality of chemical reaction networks, Precision and Sensitivity. ...
Determining the sensitivity of certain system states or outputs to variations in parameters facilita...
Background: Stochastic modeling and simulation provide powerful predictive methods for the intrinsic...
Sensitivity analysis for stochastic chemical reaction networks with multiple time-scales Ankit Gupta...
Determining the sensitivity of certain system states or outputs to variations in parameters facilita...
AbstractWe identify a connection between the structural features of mass-action networks and the rob...
One of the key challenges in systems biology is the analysis of often complex biochemical reacation ...
Stochastic models for chemical reaction networks have become very popular in recent years. For such ...
<div><p>Existing sensitivity analysis approaches are not able to handle efficiently stochastic react...
In biological cells, chemical reaction pathways lead to complex network systems like metabolic netwo...
Metabolic response coefficients describe how variables in metabolic systems, like steady state conce...
One of the key challenges in systems biology is the analysis of often complex biochemical reacation ...
Background Stochastic modeling and simulation provide powerful predictive methods for the intrinsic ...
Temperature affects all enzymes simultaneously in a metabolic system. The enzyme concentration in a ...