Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists.
Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists.
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DOI：
10.1093/nar/gkn923
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发表时间：
2009-01
影响因子：
14.9
通讯作者：
Lempicki, Richard A.
中科院分区：
文献类型：
--
作者：
Huang, Da Wei;Sherman, Brad T.;Lempicki, Richard A.
在大多数情况下，来自新兴的高通量基因组学，蛋白质组学和生物信息学扫描方法的大基因列表的功能分析，仍然是一个具有挑战性和艰巨的任务。基因注释富集分析是一种很有前途的高通量策略，它增加了研究人员识别与其研究最相关的生物过程的可能性。本次调查收集了目前社区中可用的大约68种生物信息学富集工具。工具根据其底层的丰富算法被独特地分为三大类。全面的收集、独特的工具分类和相关的问题/议题将提供一个更全面和最新的观点，以更简单的工具类别而不是逐个工具的方式来了解优势、缺陷和最新趋势。因此，该调查将帮助工具设计者/开发者和有经验的最终用户了解特定工具类别/工具的底层算法和相关细节，使他们能够为自己的特定研究兴趣做出最佳选择。
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.
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影响因子：
3
作者：
Beisvag V;Jünge FK;Bergum H;Jølsum L;Lydersen S;Günther CC;Ramampiaro H;Langaas M;Sandvik AK;Laegreid A
通讯作者：
Laegreid A
影响因子：
14.9
作者：
Al-Shahrour F;Minguez P;Tárraga J;Medina I;Alloza E;Montaner D;Dopazo J
通讯作者：
Dopazo J
影响因子：
14.9
作者：
UniProt Consortium
通讯作者：
UniProt Consortium
影响因子：
5.8
作者：
Al-Shahrour, F;Díaz-Uriarte, R;Dopazo, J
通讯作者：
Dopazo, J
影响因子：
5.8
作者：
Berriz, GF;King, OD;Roth, FP
通讯作者：
Roth, FP