BEERE (Biomedical Entity Expansion, Ranking, and Explorations) is a web-based data analysis tool to help biomedical researchers characterize any input list of genes/proteins, biomedical terms, or their combinations, i.e., “biomedical entities”, in the context of existing literature. Specifically, BEERE first aims to help users examine the credibility of known entity-to-entity associative or semantic relationships supported by database or literature references from the user input of a gene/term list. Then, it will help users uncover the relative importance of each entity—a gene or a term—within the user input by computing the ranking scores of all entities. Lastly, it will help users hypothesize new gene functions or genotype-phenotype associations by an interactive visual interface of constructed global entity relationship network. The output from BEERE includes: a list of the original entities matched with known relationships in databases; any expanded entities that may be generated from the analysis; the ranks and ranking scores reported with statistical significance for each entity; and an interactive graphical display of the gene or term’s network within data provenance annotations that link out to external data sources. The web server is free and open to all users with no login requirement and can be accessed at http://discovery.informatics.uab.edu/beere/.