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Journal ArticleDOI

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

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TLDR
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.
Abstract
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.

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References
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Journal ArticleDOI

DAVID: Database for Annotation, Visualization, and Integrated Discovery

TL;DR: DAMID is a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries that assists in the interpretation of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists

TL;DR: The DAVID Gene Functional Classification Tool uses a novel agglomeration algorithm to condense a list of genes or associated biological terms into organized classes of related genes or biology, called biological modules, for efficient interpretation of gene lists in a network context.
Journal ArticleDOI

Identifying biological themes within lists of genes with EASE

TL;DR: EASE is a customizable software application for rapid biological interpretation of gene lists that result from the analysis of microarray, proteomics, SAGE and other high-throughput genomic data and is robust to varying methods of normalization, intensity calculation and statistical selection of genes.
Journal ArticleDOI

DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists

TL;DR: 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 bio informatics databases.
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