Many scientists working on pathogens (viruses, bacteria, fungi, parasites) are betting heavily on data generated by longitudinal genomic-transcriptomic-proteomic studies to explain biochemical host-vector-pathogen interactions and thus to contribute to disease control. Availability of genome sequences of various organisms, from viruses to complex metazoans, led to the discovery of the functions of the genes themselves. The postgenomic era stimulated the development of proteomic and bioinformatics tools to identify the locations, functions, and interactions of the gene products in tissues and/or cells of living organisms. Because of the diversity of available methods and the level of integration they promote, proteomics tools are potentially able to resolve interesting issues specific not only to host-vector-pathogen interactions in cell immunobiology, but also to ecology and evolution, population biology, and adaptive processes. These new analytical tools, as all new tools, contain pitfalls directly related to experimental design, statistical treatment, and protein identification. Nevertheless, they offer the potency of building large protein-protein interaction networks for in silico analysis of novel biological entities named "interactomes," a way of modeling host-vector-pathogen interactions to define new interference strategies.