Recently, the integration of bioinformatics to complex biological data sets has provided a network-based approach for delineating the host response. As cellular responses are mediated through the selective activation or repression of signaling pathways we sought to integrate our gene expression data into functional signaling networks. Functional networks were created from our biological data sets using Ingenuity Pathway Analysis (IPA) (Figure 3 ). Genes belonging to these functional networks were related to cell-to-cell signaling and interactions, hematological system development and function, immune cell trafficking, inflammatory response and cell movement. To expand on the biological significance of this analysis, and identify individual signaling pathways modulated following infection, we performed pathway over-representation analysis (ORA) with the online software tool InnateDB (www. innatedb.com) [28] and analyzed the 1 h and 6 h Ebola-infected vs. mock-infected comparative data sets. Integrated data was limited to the 2,025 genes identified above and fold-changes .1.5 and associated p-values.0.01 were chosen as parameters for pathway ORA. The resultant differentially regulated pathways with pvalues,0.1 are presented in Tables 1 and 2 .