GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.
GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.
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DOI：
10.1186/1471-2164-10-411
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发表时间：
2009-09-03
期刊：
影响因子：
4.4
通讯作者：
Okuno Y
中科院分区：
文献类型：
--
作者：
Feng C;Araki M;Kunimoto R;Tamon A;Makiguchi H;Niijima S;Tsujimoto G;Okuno Y
DNA微阵列技术为我们向在基因组规模上揭示基因功能的目标迈出了第一步。近年来，已经收集了大量的基因表达数据，其中大部分都可以在公共数据库中获得，例如基因表达总览(GEO)。到目前为止，大多数研究人员一直使用登录号(ID)或关键字通过网络浏览器从数据库中手动检索数据，但在检索此类数据时不考虑基因表达模式。连通性图谱是最近推出的，通过引入基因表达签名(由一组基因表示，根据其生物状态具有上调或下调标记)来比较基因表达数据，并可用作从有限的数据集中(代表1,309种化合物的约7,000个表达图谱)检测类似基因表达签名的网络工具。为了支持研究人员更有效地利用公开的基因表达数据，我们开发了一个网络工具，用于从公开的数据库中查找相似的基因表达数据并生成其共表达网络。GEM-Trend是一个搜索基因表达数据的网络工具，允许用户使用基因表达签名或基因表达比率数据作为查询从GEO搜索数据，并通过比较查询和GEO基因表达数据之间的基因表达模式来检索基因表达数据。这些比较方法是基于Lamb等人的非参数、基于等级的模式匹配方法。(Science，2006)，并对统计意义进行了额外计算。Web工具分别使用从GEO随机提取的基因表达比率数据和内部微阵列数据进行测试。结果验证了GEM-Trend检索与GEO查询生物相关的基因表达条目的能力。为了进一步分析，还提供了网络可视化界面，从而将基因和基因注释动态链接到外部数据库。GEM-Trend通过比较查询基因表达模式和GEO基因表达数据来检索基因表达数据。这可能是一个非常有用的资源来寻找相似的基因表达谱，并从公开可用的数据库中构建其基因共表达网络。GEM-Trend旨在方便用户使用，预计将支持知识发现。GEM-Trend可在上免费获取。
DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at .
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影响因子：
7
作者：
Lee, HK;Hsu, AK;Pavlidis, P
通讯作者：
Pavlidis, P
影响因子：
12.3
作者：
Newman, JC;Weiner, AM
通讯作者：
Weiner, AM
DOI：
10.1073/pnas.0932692100
发表时间：
2003-07-08
影响因子：
11.1
作者：
Sorlie, T;Tibshirani, R;Botstein, D
通讯作者：
Botstein, D
影响因子：
14.9
作者：
Edgar, R;Domrachev, M;Lash, AE
通讯作者：
Lash, AE
影响因子：
56.9
作者：
Stuart, JM;Segal, E;Kim, SK
通讯作者：
Kim, SK