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QuickGO: a web-based tool for Gene Ontology searching.


Pubmed ID: 19744993 RIS Download

Mesh terms: Computational Biology | Databases, Factual | Information Storage and Retrieval | Internet | Software | User-Computer Interface




Official Web-based tools for searching and browsing the Gene Ontology database, which consists of a controlled vocabulary of terms covering biological concepts, and a large number of genes or gene products whose attributes have been annotated using GO terms. It can be accessed online at the main installation or deployed locally. The Gene Ontology project is a major bioinformatics initiative with the aim of standardizing the representation of gene and gene product attributes across species and databases. AmiGO can be used to:
* search for a gene or gene product, or a list of gene or gene products, and view the GO term associations
* perform a sequence identity BLAST search and view the GO term associations for the genes or proteins returned
* search for GO terms and view the genes or gene products they are annotated to
* browse the GO ontology and view terms
* the slimmer tool can be used to map the granular annotations of the query set of genes to one or more high-level
* term enrichment tool is used to discover what a set of genes may have in common by examining annotations and finding significant shared GO terms.
* GOOSE is for advanced users who want to run custom SQL queries against the GO database.


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A community-based bioinformatics resource consisting of three structured controlled vocabularies (ontologies) for the annotation of gene products with respect to their molecular function, cellular component, and biological role in a species-independent manner. This initiative to standardize the representation of gene and gene product attributes across species and databases is an effort to address the need for consistent descriptions of gene products in different databases. The Gene Ontology project encourages input from the community into both the content of the GO and annotation using GO. There are three separate aspects to this effort: first, they write and maintain the ontologies themselves; second, they make cross-links between the ontologies and the genes and gene products in the collaborating databases; and third, they develop tools that facilitate the creation, maintenance and use of ontologies. The controlled vocabularies are structured so that users can query them at different levels: for example, uers can use GO to find all the gene products in the mouse genome that are involved in signal transduction, or users can zoom in on all the receptor tyrosine kinases. This structure also allows annotators to assign properties to gene products at different levels, depending on how much is known about a gene product.


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