Sensitivity analysis of a computational model of the IKK-NF-{\kappa}B-I{\kappa}B{\alpha}-A20 signal transduction network

TL;DR

This paper performs sensitivity analysis on a computational model of the NF-κB signaling pathway, ranking influential parameters, classifying response profiles, and constructing a simplified network to better understand immune response regulation.

Contribution

It introduces a comprehensive sensitivity analysis and classification of NF-κB responses, and develops a reduced model highlighting key regulatory components.

Findings

Identified key kinetic rate variables influencing NF-κB signaling.

Classified nuclear NF-κB response profiles into six, regrouped into three biologically relevant clusters.

Constructed a reduced signaling network based on parameter influence ranking.

Abstract

The NF-{\kappa}B signaling network plays an important role in many different compartments of the immune system during immune activation. Using a computational model of the NF-{\kappa}B signaling network involving two negative regulators, I{\kappa}B{\alpha} and A20, we performed sensitivity analyses with three different sampling methods and present a ranking of the kinetic rate variables by the strength of their influence on the NF-{\kappa}B signaling response. We also present a classification of temporal response profiles of nuclear NF-{\kappa}B concentration into six clusters, which can be regrouped to three biologically relevant clusters. Lastly, based upon the ranking, we constructed a reduced network of the IKK-NF-{\kappa}B-I{\kappa}B{\alpha}-A20 signal transduction.