Insights into the behaviour of systems biology models from dynamic sensitivity and identifiability analysis: a case study of an NF-κB signalling pathway

Abstract

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Sensitivity analysis and robust experimental design of a signal transduction pathway system

“…(a) When the GSA is implemented within a narrow range around the nominal parameter values, the sensitivity ranking results from GSA using the modified Morris method agrees well with the results from LSA shown in our previous work [31,33]. This is particularly true for those sensitive parameters when they are clearly distinguished from the rest set of parameters.…”

“…These three parameters are all identified to be influential in our previous study of LSA [31,33]. The range of the initial IKK concentration after equilibration is set to [0.01, 1] μM.…”

“…See Table I for the states definition. The reactions and the parameter values can be found in our previous paper [33].…”

“…While Hoffmann's model measures the behavior of cell populations [28], Nelson's work analyses experimental data obtained from individual cells [29], and Lipniacki's model focuses on the role of A20, which is regulated by NF-κB and acts as an inhibitor of IKK [30]. The model used in this work is the Hoffmann's model, as described in [28,[31][32][33]. It includes 26 reaction species participating in 64 reactions, out of which the concentrations of 24 species are time varying and are defined as state variables in the model.…”

Sensitivity analysis of deterministic signaling pathways models

“…[18][19][20]) and their application to signaling pathways analysis (e.g. [17,21]). Usually, for signaling pathways models parameter values are randomly generated from one of two possible distributions:…”