article Open AccessTop 1% cited
The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists
Genome biology · 2007 · Vol. 8(9) · pp. R183–R183
Da Wei Huang✉(Science Applications International Corporation (United States))Brad T. Sherman(Science Applications International Corporation (United States))Qina Tan(National Cancer Institute)Jack Collins(National Cancer Institute)W. Gregory Alvord(Data Management Services (United States))Jean Roayaei(National Cancer Institute)Robert D. Stephens(National Cancer Institute)Michael Baseler(Science Applications International Corporation (United States))H. Clifford Lane(National Institutes of Health)Richard A. Lempicki(National Cancer Institute)
Abstract
The DAVID Gene Functional Classification Tool http://david.abcc.ncifcrf.gov 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. This organization is accomplished by mining the complex biological co-occurrences found in multiple sources of functional annotation. It is a powerful method to group functionally related genes and terms into a manageable number of biological modules for efficient interpretation of gene lists in a network context.
Bioinformatics and Genomic NetworksGene expression and cancer classificationMachine Learning in BioinformaticsBiologyGeneComputational biologyAnnotationContext (archaeology)Biological networkHuman geneticsGene AnnotationGene regulatory networkGene nomenclature
MeSH terms
AlgorithmsData Interpretation, StatisticalGenetic TechniquesHumansModels, TheoreticalPattern Recognition, AutomatedSoftwareCluster AnalysisComputational BiologyOligonucleotide Array Sequence AnalysisGene Expression ProfilingGenomicsDatabases, Genetic
Funding
- U.S. Department of Health and Human Services
- National Institutes of Health
- National Cancer Institute
- National Institute of Allergy and Infectious Diseases
Citations
2,525
FWCI
15.15
field-weighted impact
References
38
Percentile
99%
vs. same field & year
Citations per year
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Genome biology · 2003 · 1,955 citations
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