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We embrace an interdisciplinary approach to data science focused on networks and network representations, using mathematical models and statistical principles to develop computational tools for real-world data. With “nodes” representing objects of interest and “edges” that connect the nodes representing relationships or similarities, the concept of a network can be flexibly used across many applications. Our collaborations have included researchers in Biostatistics, Epidemiology, Infectious Diseases, Neuroscience, and Pharmacology.