Asthma is a complex polygenic disease involving the interaction of many genes. In this study, we investigated the allergic response in experimental asthma. First, we constructed a biological interaction network using the BOND (Biomolecular Object Network Databank) database of literature curated molecular interactions. Second, we mapped differentially expressed genes from microarray data onto the network. Third, we analyzed the topological characteristics of the modulated genes. Fourth, we analyzed the correlation between the topology and biological function using the Gene Ontology classifications. Our results demonstrate that nodes with high connectivity (hubs and superhubs) tend to have low levels of change in gene expression. The significance of our observations was confirmed by permutation testing. Furthermore, our analysis indicates that hubs and superhubs have significantly different biological functions compared with peripheral nodes based on Gene Ontology classification. Our observations have important ramifications for interpreting gene expression data and understanding biological responses. Thus, our analysis suggests that a combination of differential gene expression plus topological characteristics of the interaction network provides enhanced understanding of the biology in our model of experimental asthma.