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

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 DA...

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Detalles Bibliográficos
Autores principales: Huang, Da Wei, Sherman, Brad T., Tan, Qina, Kir, Joseph, Liu, David, Bryant, David, Guo, Yongjian, Stephens, Robert, Baseler, Michael W., Lane, H. Clifford, Lempicki, Richard A.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933169/
https://www.ncbi.nlm.nih.gov/pubmed/17576678
http://dx.doi.org/10.1093/nar/gkm415
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author Huang, Da Wei
Sherman, Brad T.
Tan, Qina
Kir, Joseph
Liu, David
Bryant, David
Guo, Yongjian
Stephens, Robert
Baseler, Michael W.
Lane, H. Clifford
Lempicki, Richard A.
author_facet Huang, Da Wei
Sherman, Brad T.
Tan, Qina
Kir, Joseph
Liu, David
Bryant, David
Guo, Yongjian
Stephens, Robert
Baseler, Michael W.
Lane, H. Clifford
Lempicki, Richard A.
author_sort Huang, Da Wei
collection PubMed
description 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.
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spelling pubmed-19331692007-07-31 DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists Huang, Da Wei Sherman, Brad T. Tan, Qina Kir, Joseph Liu, David Bryant, David Guo, Yongjian Stephens, Robert Baseler, Michael W. Lane, H. Clifford Lempicki, Richard A. Nucleic Acids Res Articles 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. Oxford University Press 2007-07 2007-06-18 /pmc/articles/PMC1933169/ /pubmed/17576678 http://dx.doi.org/10.1093/nar/gkm415 Text en © 2007 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Huang, Da Wei
Sherman, Brad T.
Tan, Qina
Kir, Joseph
Liu, David
Bryant, David
Guo, Yongjian
Stephens, Robert
Baseler, Michael W.
Lane, H. Clifford
Lempicki, Richard A.
DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
title DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
title_full DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
title_fullStr DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
title_full_unstemmed DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
title_short DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
title_sort david bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1933169/
https://www.ncbi.nlm.nih.gov/pubmed/17576678
http://dx.doi.org/10.1093/nar/gkm415
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