Notice: if BiNGO aborts without any error message, try running Cytoscape from cytoscape.bat (Windows) or (Linux, Mac) or modify Cytoscape’s default memory settings, see FAQ
Current version : BiNGO 2.44 (compatible with Cytoscape 2.7, 2.8)
New features: use the latest .obo ontology files from GO, use custom .obo files or use custom reference sets, save settings.
Notice: using default annotations and ontologies is no longer recommended for anything more than a quick-and-dirty analysis. Default annotations and ontologies date from August 2010 and will be updated irregularly. BiNGO now supports the use of annotation and ontology files downloaded from

If you use BiNGO in your research, please cite:
Maere S, Heymans K, Kuiper M (2005) BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in biological networks. Bioinformatics 21, 3448-3449. (PubMed)
BiNGO :  A Biological Network Gene Ontology tool.
BiNGO is a Java-based tool to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. BiNGO is implemented as a plugin for Cytoscape, which is a an open source bioinformatics software platform for visualizing and integrating molecular interaction networks. BiNGO maps the predominant functional themes of a given gene set on the GO hierarchy, and outputs this mapping as a Cytoscape graph. Gene sets can either be selected or computed from a Cytoscape network (as subgraphs) or compiled from sources other than Cytoscape (e.g. a list of genes that are significantly upregulated in a microarray experiment). The main advantage of BiNGO over other GO tools is the fact that it can be used directly and interactively on molecular interaction graphs. Another plus is that BiNGO takes full advantage of Cytoscape's versatile visualization environment. This allows you to produce customized high-quality figures.
Features include :
assessing overrepresentation or underrepresentation of GO categories
Graph or gene list input
batch mode : analyze several clusters simultaneously using same settings
Different GO and GOSlim ontologies
Wide range of organisms
Evidence code filtering
Hypergeometric or binomial test for overrepresentation
Multiple testing correction using Bonferroni (FWER) or Benjamini&Hochberg (FDR) correction
Interactive visualization of results mapped on the GO hierarchy. 
extensive results in tab-delimited text file format
make and use custom annotations, ontologies and reference sets
open source

To get a taste, please take a look at the tutorial section.
 You may want to try our other tools too:



Copyright (c) 2005-2010 Flanders Interuniversitary Institute for Biotechnology (VIB)