Modelling of macrophage gene expression in the interferon pathway

We propose a modeling approach based on Probabilistic Boolean Networks for the inference of genetic regulatory networks from gene expression time-course data in different biological conditions i.e. making use of the information contained in sets of genes and the interaction between genes rather than single-gene analyses. This model is a collection of traditional Probabilistic Boolean Networks. We also present an approach which is based on constrained prediction and Coefficient of Determination (COD) for the identification of the model from gene expression data. The modeling approach is applied in the context of pathway biology to the analysis of gene interaction networks.