Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database information

DAVID (The Database for Annotation, Visualization and Integrated Discovery)

General information

Description: The Database for Annotation, Visualization and Integrated Discovery (DAVID ) v6.8 comprises a full Knowledgebase update to the sixth version of our original web-accessible programs. DAVID now provides a comprehensive set of functional annotation tools for investigators to understand biological meaning behind large list of genes.
Year founded: 2003
Last update: 2019
Version: version6.8
Accessibility:
Manual:
Accessible
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Country/Region: United States
Data type:
DNA
Data object:
Database category:
Major organism:
Keywords:

Contact information

University/Institution: National Cancer Institute
Address: P.O. Box B or Bldg. 310 Laboratory of Human Retrovirology and Immunoinformatics Applied/Developmental Research Directorate Frederick National Laboratory for Cancer Research Frederick, MD 21702
City:
Province/State:
Country/Region: United States
Contact name (PI/Team): DAVID Bioinformatic Team
Contact email (PI/Helpdesk): weizhong.chang@nih.gov

Record metadata

Created on: 2018-01-26
Curated by:
Lina Ma [2019-12-25]
Dong Zou [2019-12-02]
Rabail Raza [2018-12-27]
Mengyu Pan [2018-09-20]
Tongkun Guo [2018-02-24]

Ranking

All databases:
1/4516 (100%)
Gene genome and annotation:
1/1203 (100%)
1
Total Rank
20,236
Citations
1,556.62
z-index

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Publications

19131956
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. [PMID: 19131956]
Huang da W, Sherman BT, Lempicki RA.

DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

Nat Protoc. 2009:4(1) | 13852 Citations (from Europe PMC, 2020-01-18)
19033363
Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. [PMID: 19033363]
Huang da W, Sherman BT, Lempicki RA.

Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

Nucleic Acids Res. 2009:37(1) | 5686 Citations (from Europe PMC, 2020-01-18)
17980028
DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis. [PMID: 17980028]
Sherman BT, Huang da W, Tan Q, Guo Y, Bour S, Liu D, Stephens R, Baseler MW, Lane HC, Lempicki RA.

BACKGROUND: Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis.
DESCRIPTION: The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner.
CONCLUSION: The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

BMC Bioinformatics. 2007:8() | 243 Citations (from Europe PMC, 2020-01-18)
17576678
DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. [PMID: 17576678]
Huang DW, Sherman BT, Tan Q, Kir J, Liu D, Bryant D, Guo Y, Stephens R, Baseler MW, Lane HC, Lempicki RA.

All tools in the DAVID Bioinformatics Resources aim to provide functional interpretation of large lists of genes derived from genomic studies. The newly updated DAVID Bioinformatics Resources consists of the DAVID Knowledgebase and five integrated, web-based functional annotation tool suites: the DAVID Gene Functional Classification Tool, the DAVID Functional Annotation Tool, the DAVID Gene ID Conversion Tool, the DAVID Gene Name Viewer and the DAVID NIAID Pathogen Genome Browser. The expanded DAVID Knowledgebase now integrates almost all major and well-known public bioinformatics resources centralized by the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of diverse gene/protein identifiers and annotation terms from a variety of public bioinformatics databases. For any uploaded gene list, the DAVID Resources now provides not only the typical gene-term enrichment analysis, but also new tools and functions that allow users to condense large gene lists into gene functional groups, convert between gene/protein identifiers, visualize many-genes-to-many-terms relationships, cluster redundant and heterogeneous terms into groups, search for interesting and related genes or terms, dynamically view genes from their lists on bio-pathways and more. With DAVID (http://david.niaid.nih.gov), investigators gain more power to interpret the biological mechanisms associated with large gene lists.

Nucleic Acids Res. 2007:35(Web Server issue) | 743 Citations (from Europe PMC, 2020-01-18)