On the Complexity - Sensitivity Trade-off for the NF-κB Pathway Modeling

An important aspect of systems biology research is the so-called "reverse engineering" of cellular metabolic dynamics from measured input-output data. This allows researchers to estimate and validate both the pathway's structure as well as the kinetic constants. In this paper, a regularization based method which performs model structure selection is developed and applied to the problem of analyzing how existing pathway knowledge can be used as a prior investigate the model change complexity/sensitivity trade-off. Specifically, a 1-norm prior on parameter deviations from an existing model of the I kappa B-NF-kappa B pathway is combined with new experimental data and an analysis is performed to determine which are the most relevant components to alter.