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Improvements to cardiovascular gene ontology.

Atherosclerosis | Jul 22, 2009

Gene Ontology (GO) provides a controlled vocabulary to describe the attributes of genes and gene products in any organism. Although one might initially wonder what relevance a 'controlled vocabulary' might have for cardiovascular science, such a resource is proving highly useful for researchers investigating complex cardiovascular disease phenotypes as well as those interpreting results from high-throughput methodologies. GO enables the current functional knowledge of individual genes to be used to annotate genomic or proteomic datasets. In this way, the GO data provides a very effective way of linking biological knowledge with the analysis of the large datasets of post-genomics research. Consequently, users of high-throughput methodologies such as expression arrays or proteomics will be the main beneficiaries of such annotation sets. However, as GO annotations increase in quality and quantity, groups using small-scale approaches will gradually begin to benefit too. For example, genome wide association scans for coronary heart disease are identifying novel genes, with previously unknown connections to cardiovascular processes, and the comprehensive annotation of these novel genes might provide clues to their cardiovascular link. At least 4000 genes, to date, have been implicated in cardiovascular processes and an initiative is underway to focus on annotating these genes for the benefit of the cardiovascular community. In this article we review the current uses of Gene Ontology annotation to highlight why Gene Ontology should be of interest to all those involved in cardiovascular research.

Pubmed ID: 19046747 RIS Download

Mesh terms: Cardiovascular Diseases | Chromosomes, Human, Pair 9 | Computational Biology | Databases, Factual | Databases, Protein | Genes | Genome | Genome-Wide Association Study | Genomics | Humans | Proteomics | Terminology as Topic | Vocabulary, Controlled

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This is a list of tools and resources that we have found mentioned in this publication.


AmiGO

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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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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European Bioinformatics Institute

A non-profit academic organization for research and services in bioinformatics that provides freely available data from life science experiments, performs basic research in computational biology, and offers an extensive user training programme, supporting researchers in academia and industry. The Institute manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures.

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MGI GO Browser

With the MGI GO Browser, you can search for a GO term and view all mouse genes annotated to the term or any subterms. You can also browse the ontologies to view relationships between terms, term definitions, as well as the number of mouse genes annotated to a given term and its subterms. The MGI GO browser directly accesses the GO data in the MGI database, which is updated nightly. Platform: Online tool

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Gene Ontology Tools

A collection of tools developed by the GO Consortium and by third parties. Tools are listed by category or alphabetically and continue to be improved and expanded.

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OBO

A collaboration involving developers of science-based ontologies who are establishing a set of principles for ontology development with the goal of creating a suite of orthogonal interoperable reference ontologies in the biomedical domain. In addition to a listing of OBO ontologies, this site provides a statement of the OBO Foundry principles, discussion fora, technical infrastructure, and other services to facilitate ontology development. Feedback is welcome and participation encouraged.

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