DAVID gene ID conversion tool

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Abstract

Our current biological knowledge is spread over many independent bioinformatics databases where many different types of gene and protein identifiers are used. The heterogeneous and redundant nature of these identifiers limits data analysis across different bioinformatics resources. It is an even more serious bottleneck of data analysis for larger datasets, such as gene lists derived from microarray and proteomic experiments. The DAVID Gene ID Conversion Tool (DICT), a web-based application, is able to convert user's input gene or gene product identifiers from one type to another in a more comprehensive and high-throughput manner with a uniquely enhanced ID-ID mapping database.

Availability

http://david.abcc.ncifcrf.gov/conversion.jsp.

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Most cited references 9

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DAVID: Database for Annotation, Visualization, and Integrated Discovery.

Glynn Dennis, Brad T. Sherman, Douglas A Hosack … (2003)

Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.

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Entrez Gene: gene-centered information at NCBI

Donna R. Maglott, Jim Ostell, Kim D. Pruitt … (2004)

Entrez Gene (www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene) is NCBI's database for gene-specific information. It does not include all known or predicted genes; instead Entrez Gene focuses on the genomes that have been completely sequenced, that have an active research community to contribute gene-specific information, or that are scheduled for intense sequence analysis. The content of Entrez Gene represents the result of curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases, and from many other databases available from NCBI. Records are assigned unique, stable and tracked integers as identifiers. The content (nomenclature, map location, gene products and their attributes, markers, phenotypes, and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases) is updated as new information becomes available. Entrez Gene is a step forward from NCBI's LocusLink, with both a major increase in taxonomic scope and improved access through the many tools associated with NCBI Entrez.

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SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data.

Gail Binkley, Bradley Brown, J. Cherry … (2003)

The explosion in the number of functional genomic datasets generated with tools such as DNA microarrays has created a critical need for resources that facilitate the interpretation of large-scale biological data. SOURCE is a web-based database that brings together information from a broad range of resources, and provides it in manner particularly useful for genome-scale analyses. SOURCE's GeneReports include aliases, chromosomal location, functional descriptions, GeneOntology annotations, gene expression data, and links to external databases. We curate published microarray gene expression datasets and allow users to rapidly identify sets of co-regulated genes across a variety of tissues and a large number of conditions using a simple and intuitive interface. SOURCE provides content both in gene and cDNA clone-centric pages, and thus simplifies analysis of datasets generated using cDNA microarrays. SOURCE is continuously updated and contains the most recent and accurate information available for human, mouse, and rat genes. By allowing dynamic linking to individual gene or clone reports, SOURCE facilitates browsing of large genomic datasets. Finally, SOURCEs batch interface allows rapid extraction of data for thousands of genes or clones at once and thus facilitates statistical analyses such as assessing the enrichment of functional attributes within clusters of genes. SOURCE is available at http://source.stanford.edu.

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Author and article information

Journal

Journal ID (nlm-ta): Bioinformation

Journal ID (publisher-id): Bioinformation

Title: Bioinformation

Publisher: Biomedical Informatics Publishing Group

ISSN (Electronic): 0973-2063

Publication date Collection: 2008

Publication date (Electronic): 30 July 2008

Volume: 2

Issue: 10

Pages: 428-430

Affiliations

[1 ]Laboratory of Immunopathogenesis and Bioinformatics

[2 ]Advanced Biomedical Computing Center, SAIC-Frederick, Inc., National Cancer Institute at Frederick, MD 21702

[3 ]Clinical Services Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, MD 21702

[4 ]Laboratory of Immuno-regulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892

Author notes

[* ]Corresponding author: E-mail: rlempicki@ 123456mail.nih.gov

[$]

Both the authors contributed equally

Article

Publisher ID: 009200022008

DOI: 10.6026/97320630002428

PMC ID: 2561161

PubMed ID: 18841237

SO-VID: e00ddd03-adee-4189-9a01-a291bbf70360

License:

This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.

DAVID gene ID conversion tool

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Genetoberfest

Most cited references 9

DAVID: Database for Annotation, Visualization, and Integrated Discovery.

Entrez Gene: gene-centered information at NCBI

SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data.

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