GeneFriends: a human RNA-seq-based gene and transcript co-expression database.
GeneFriends: a human RNA-seq-based gene and transcript co-expression database.
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DOI：
10.1093/nar/gku1042
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发表时间：
2015-01
影响因子：
14.9
通讯作者：
de Magalhães JP
中科院分区：
文献类型：
--
作者：
van Dam S;Craig T;de Magalhães JP
共表达网络已被证明是有效的分配假定的功能基因的基础上，其共同表达的合作伙伴的功能注释，在候选基因优先级的研究，并提高我们对调控网络的理解。越来越多的基因组重测序工作和全基因组关联研究经常发现含有新基因的位点，需要推断它们的功能和相互作用伙伴。为了促进这一点，我们扩展了GeneFriends，这是一个在线数据库，允许用户识别与一个或多个用户定义的基因共表达的基因。这种扩展需要一个基于RNA-seq的共表达图谱，其中包括基于微阵列的共表达图谱中不存在的基因和转录本，包括超过10000个非编码RNA。用户从GeneFriends获得的结果包括共表达网络以及共表达基因之间功能富集的总结。可以从该数据库中收集不同剪接变体和ncRNA（如microRNA和lincRNA）的新见解。此外，我们更新的工具允许候选转录本与疾病和过程使用内疚的关联方法。GeneFriends可从http://www.GeneFriends.org免费获得，可用于快速识别和排名与研究过程或疾病相关的候选靶标。
Co-expression networks have proven effective at assigning putative functions to genes based on the functional annotation of their co-expressed partners, in candidate gene prioritization studies and in improving our understanding of regulatory networks. The growing number of genome resequencing efforts and genome-wide association studies often identify loci containing novel genes and there is a need to infer their functions and interaction partners. To facilitate this we have expanded GeneFriends, an online database that allows users to identify co-expressed genes with one or more user-defined genes. This expansion entails an RNA-seq-based co-expression map that includes genes and transcripts that are not present in the microarray-based co-expression maps, including over 10 000 non-coding RNAs. The results users obtain from GeneFriends include a co-expression network as well as a summary of the functional enrichment among the co-expressed genes. Novel insights can be gathered from this database for different splice variants and ncRNAs, such as microRNAs and lincRNAs. Furthermore, our updated tool allows candidate transcripts to be linked to diseases and processes using a guilt-by-association approach. GeneFriends is freely available from http://www.GeneFriends.org and can be used to quickly identify and rank candidate targets relevant to the process or disease under study.
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影响因子：
4.3
作者：
Guan Y;Myers CL;Lu R;Lemischka IR;Bult CJ;Troyanskaya OG
通讯作者：
Troyanskaya OG
影响因子：
3.7
作者：
Bhat P;Yang H;Bögre L;Devoto A;Paccanaro A
通讯作者：
Paccanaro A
DOI：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
影响因子：
14.9
作者：
Kanehisa M;Goto S;Sato Y;Furumichi M;Tanabe M
通讯作者：
Tanabe M
影响因子：
3
作者：
Jupiter D;Chen H;VanBuren V
通讯作者：
VanBuren V