Research organizations are becoming more reliant on quantitative approaches to determine how to recruit and promote researchers, allocate funding, and evaluate the impact of prior allocations. Many of these quantitative metrics are based on research publications. Publication metrics are not only important for individual careers, but also affect the progress of science as a whole via their role in the funding award process. Understanding the origin and intended use of popular publication metrics can inform an evaluative strategy that balances the usefulness of publication metrics with the limitations of what they can convey about the productivity and quality of an author, a publication, or a journal. This paper serves as a brief introduction to citation networks like Google Scholar, Web of Science Core Collection, Scopus, Microsoft Academic, and Dimensions. It also explains two of the most popular publication metrics: the h-index and the journal impact factor. The purpose of this paper is to provide practical information on using citation networks to generate publication metrics, and to discuss ideas for contextualizing and juxtaposing metrics, in order to help researchers in translational science and other disciplines document their impact in as favorable a light as may be justified.