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GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists.

Genome biology | Mar 29, 2007

We present GENECODIS, a web-based tool that integrates different sources of information to search for annotations that frequently co-occur in a set of genes and rank them by statistical significance. The analysis of concurrent annotations provides significant information for the biologic interpretation of high-throughput experiments and may outperform the results of standard methods for the functional analysis of gene lists. GENECODIS is publicly available at http://genecodis.dacya.ucm.es/.

Pubmed ID: 17204154 RIS Download

Mesh terms: Computational Biology | Genes, Fungal | Humans | Internet | Saccharomyces cerevisiae | Software

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GO

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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