We're so glad you asked! Well this is yet another Gene Ontology enrichment tool, BUT with some useful features you'll not find elsewhere. This tool is protein-centric and provides multiple enrichment methods in order to provide biologically meaningful results. We support all UniProt identifiers (SwissProt and TrEMBL) as well as STRING identifiers. You can enrich for GO (molecular function, biological process, cellular component), UniProt keywords, KEGG pathways, PubMed publications, Reactome, Wiki Pathways, Interpro domains, PFAM domains, Brenda Tissues, and Disaeses. We're providing regular monthly updates. Speaking of which we're using textmining results which enables us to provide you with enrichment for Diseases, Tissues, PubMed publications, and Compartments (mapped to and reported as "Gene Ontology Cellular Component TEXTMINING", which is a separate category to "Gene Ontology Cellular Component" stemming from UniProt).

David Lyon

Christian von Mering

Lars Juhl Jensen

The resources used for this web-service are automatically updated on a monthly basis.
Last updated on 01 September 2023
Functional associations for the following categories are retrieved from UniProt: GO terms, UniProt Keywords, KEGG, Interpro, Pfam, and Reactome. Since these associations can simply be counted we apply a Fisher's exact test to find significantly enriched terms. Diseases, Brenda Tissues, Gene Ontology Cellular Component (Compartments), and PubMed publications stem from Jensenlab textming results. Since these protein to function associations are not binary, but result in a score between 0 and 5, we apply a Kolmogorov Smirnov test.

Please cite the following article when applying this method or using this service:
Avoiding abundance bias in the functional annotation of posttranslationally modified proteins.
Nature Methods, 2015
doi:10.1038/nmeth.3621

The software (published under BSD) is available at https://github.com/dblyon/agotool.git.
Feel free to contact [email protected] for support.