Continuous network models of gene expression in knock-out experiments: A preliminary study

In this work we simulate gene knock-out experiments in networks in which variable domains are continuous and variables can vary continuously in time. This model is more realistic than other well-known switching networks such as Boolean Networks. We show that continuous networks can reproduce the results obtained by Random Boolean Networks (RBN). Nevertheless, they do not reproduce the whole range of activation values of actual experimental data. The reasons for this behavior very close to that of RBN could be found in the specific parameter setting chosen and lines for further investigation are discussed.