The adaptation of the bacterium Escherichia coli to carbon starvation is controlled by a large network of biochemical reactions involving genes, mRNAs, proteins, and signalling molecules. The dynamics of this network is difficult to analyze, notably due to a lack of quantitative information on parameter values. To overcome these limitations, the application of model reduction approaches based on QSS and PL approximations may result in models that are easier to handle mathematically and computationally. In particular, PL models allow the analysis of the qualitative dynamics of the network using only weak information on the ordering of parameters rather than their exact numerical values.We illustrate the use of these techniques, implemented in the computer tool Genetic Network Analyzer (GNA), in the case of the E. coli network.