The article introduces REVIGO, a web server designed to summarize and visualize long lists of Gene Ontology (GO) terms. High-throughput biological experiments often yield large and redundant lists of GO terms, making interpretation challenging. REVIGO addresses this issue by clustering semantically similar GO terms into representative subsets and providing multiple visualization methods, including scatterplots, graph-based visualizations, treemaps, and tag clouds. The clustering algorithm uses semantic similarity measures to identify clusters, and the visualization methods help in understanding the relationships and subdivisions within the GO term sets. The tool is freely available and can be accessed at http://revigo.irb.hr/. The authors also compare REVIGO with other software tools, highlighting its advantages in terms of implementation, interoperability, and visualization methods.The article introduces REVIGO, a web server designed to summarize and visualize long lists of Gene Ontology (GO) terms. High-throughput biological experiments often yield large and redundant lists of GO terms, making interpretation challenging. REVIGO addresses this issue by clustering semantically similar GO terms into representative subsets and providing multiple visualization methods, including scatterplots, graph-based visualizations, treemaps, and tag clouds. The clustering algorithm uses semantic similarity measures to identify clusters, and the visualization methods help in understanding the relationships and subdivisions within the GO term sets. The tool is freely available and can be accessed at http://revigo.irb.hr/. The authors also compare REVIGO with other software tools, highlighting its advantages in terms of implementation, interoperability, and visualization methods.