An important current challenge for the field of protein-protein interaction studies is how to best integrate the quantitative assessment of interaction levels with subcellular localization, functional classification via gene ontology enrichment, and published protein complex datasets, which can add depth and understanding to biological investigations. Here, we addressed this need by building VISTA (Visualization of Interactions in Space and Time Analysis tool). VISTA enables users to visualize dynamic interaction networks of one or many baits, automatically integrate subcellular localization information and functional annotations to modify networks, analyze trends in dynamic protein abundances across the network, and identify properties of proteins shared between multiple baits – all with their own data and with minimal manual workup. We demonstrate the utility of VISTA by defining the interactomes of two HCMV proteins, pUL37 and pUL13, over the full replication cycle of infection. These viral proteins provide examples of either temporally (i.e., pUL37) or spatially (pUL13) regulated interactions and functions. pUL37 is a critical HCMV protein known to inhibit cellular apoptosis. Despite its predominant localization to one sub-cellular compartment, the mitochondria, pUL37 functions are temporally-regulated throughout infection and only few protein interactions are known. pUL13 on the other hand is localized to different sub-cellular compartments at distinct stages of the infection and has no characterized functions or protein interactions. This viral protein is enriched at the plasma membrane early in infection, followed by a localization to the mitochondria and then to the virus assembly compartment. By examining these two proteins with differing temporal patterns of localization and function, we highlight the utility of VISTA in integrating and visualizing datasets, as well as provide new insights into the biology of HCMV infection.