Medical librarians can expedite biomedical research by broadening the scope of their instruction curricula to include courses on the use of network visualization tools. With the dramatic increase in the number of databases, data sets, tools, and software being used to store, retrieve, and analyze proteomic, genomic, and metabolomic data, researchers are being forced to navigate an ever-complex information environment. Medical librarians can accelerate data analysis by learning about, conducting comparative analyses for, and providing instruction on these resources. Many libraries, such as the University of Florida's Health Science Center Libraries and Washington University's Bernard Becker Medical Library, offer instruction on biomedical databases and tools such as those provided by the National Center for Biotechnology Information (NCBI) [1, 2]. Instruction on network visualization tools is not as commonly provided by libraries. Network visualization is a method of data analysis that uses nodes to represent a data point, such as a gene, and edges (lines connecting nodes) to represent a relationship between two data points, such as an interaction between two genes (Figure 1, online only). Nodes and edges can have attributes associated with them that provide additional information, such as the chromosome on which a gene is located. Network visualization is an effective method for representing biologic relationships by succinctly highlighting properties and trends in complex systems. Networks also allow the integration of multiple different kinds of data such as gene expression, ontologies, and protein structures that have traditionally been stored in their own repositories [3]. Network analysis and network modeling techniques are being applied to biological networks in order to provide new hypotheses for biological systems, and as a result, a large number of tools for visualizing networks are constantly being developed, used, and reviewed [4]. Teaching biomedical resources such as network visualization tools, in addition to those developed by NCBI, is an area where medical librarians can make a significant impact. While resources like OpenHelix provide some instruction on these types of resources, these sources are limited, providing an important opportunity for libraries to expand the scope of their instruction curricula and to use instruction methods that allow broad participation by users. This paper discusses the evolution of a successful training class on a free and useful network visualization tool and the methods used to reach a wide-ranging audience.