Cargando…
Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists
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 likelih...
Autores principales: | , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2615629/ https://www.ncbi.nlm.nih.gov/pubmed/19033363 http://dx.doi.org/10.1093/nar/gkn923 |
_version_ | 1782163347338166272 |
---|---|
author | Huang, Da Wei Sherman, Brad T. Lempicki, Richard A. |
author_facet | Huang, Da Wei Sherman, Brad T. Lempicki, Richard A. |
author_sort | Huang, Da Wei |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2615629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-26156292009-03-30 Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists Huang, Da Wei Sherman, Brad T. Lempicki, Richard A. Nucleic Acids Res Survey and Summary 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. Oxford University Press 2009-01 2008-11-25 /pmc/articles/PMC2615629/ /pubmed/19033363 http://dx.doi.org/10.1093/nar/gkn923 Text en © 2008 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 | Survey and Summary Huang, Da Wei Sherman, Brad T. Lempicki, Richard A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
title | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
title_full | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
title_fullStr | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
title_full_unstemmed | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
title_short | Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
title_sort | bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists |
topic | Survey and Summary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2615629/ https://www.ncbi.nlm.nih.gov/pubmed/19033363 http://dx.doi.org/10.1093/nar/gkn923 |
work_keys_str_mv | AT huangdawei bioinformaticsenrichmenttoolspathstowardthecomprehensivefunctionalanalysisoflargegenelists AT shermanbradt bioinformaticsenrichmenttoolspathstowardthecomprehensivefunctionalanalysisoflargegenelists AT lempickiricharda bioinformaticsenrichmenttoolspathstowardthecomprehensivefunctionalanalysisoflargegenelists |