DAVID: Database for Annotation, Visualization, and Integrated Discovery

Genome Biol. 2003;4(5):P3. Epub 2003 Apr 3.

Abstract

Background: 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.

Results: 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.

Conclusions: 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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Computational Biology / methods
  • Databases, Nucleic Acid*
  • Gene Expression Profiling / statistics & numerical data*
  • HIV-1 / growth & development
  • Humans
  • Internet
  • Leukocytes, Mononuclear / metabolism
  • Leukocytes, Mononuclear / virology
  • Macrophages / metabolism
  • Macrophages / virology
  • Oligonucleotide Array Sequence Analysis / methods