The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes.
The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes.
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DOI：
10.1093/nar/gkq1259
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发表时间：
2011-01
影响因子：
14.9
通讯作者：
Irizarry RA
中科院分区：
文献类型：
--
作者：
McCall MN;Uppal K;Jaffee HA;Zilliox MJ;Irizarry RA
各种数据库利用可公开获得的大量微阵列数据来解决从跨组织差异表达到同源基因表达的各种生物学问题。尽管这些数据库具有实用价值，但它们依赖于表达的相对测量，无法解决最根本的问题--哪些基因在给定的细胞类型中表达。基因表达条形码是第一个为131种人类和89种小鼠组织类型(包括患病组织)的大多数注释基因提供可靠绝对表达测量的数据库。这是由一种新的算法实现的，该算法利用来自GEO和ArrayExpress公共存储库的信息来建立统计模型，允许将来自单个微阵列的数据转换为对每个基因的已表达/未表达的调用。对于选定的平台，用户可以在几秒钟内上传数据并获得结果。用于创建我们的资源的原始数据、精选注释和代码也可以在http://rafalab.jhsph.edu/barcode.上找到
Various databases have harnessed the wealth of publicly available microarray data to address biological questions ranging from across-tissue differential expression to homologous gene expression. Despite their practical value, these databases rely on relative measures of expression and are unable to address the most fundamental question—which genes are expressed in a given cell type. The Gene Expression Barcode is the first database to provide reliable absolute measures of expression for most annotated genes for 131 human and 89 mouse tissue types, including diseased tissue. This is made possible by a novel algorithm that leverages information from the GEO and ArrayExpress public repositories to build statistical models that permit converting data from a single microarray into expressed/unexpressed calls for each gene. For selected platforms, users may upload data and obtain results in a matter of seconds. The raw data, curated annotation, and code used to create our resource are also available at http://rafalab.jhsph.edu/barcode.
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影响因子：
3.3
作者：
Yanai, I;Graur, D;Ophir, R
通讯作者：
Ophir, R
影响因子：
14.9
作者：
Parkinson H;Kapushesky M;Kolesnikov N;Rustici G;Shojatalab M;Abeygunawardena N;Berube H;Dylag M;Emam I;Farne A;Holloway E;Lukk M;Malone J;Mani R;Pilicheva E;Rayner TF;Rezwan F;Sharma A;Williams E;Bradley XZ;Adamusiak T;Brandizi M;Burdett T;Coulson R;Krestyaninova M;Kurnosov P;Maguire E;Neogi SG;Rocca-Serra P;Sansone SA;Sklyar N;Zhao M;Sarkans U;Brazma A
通讯作者：
Brazma A
DOI：
10.1073/pnas.012025199
发表时间：
2002-04-02
影响因子：
11.1
作者：
Su, AI;Cooke, MP;Hogenesch, JB
通讯作者：
Hogenesch, JB
影响因子：
10.7
作者：
Xing, Yi;Ouyang, Zhengqing;Wong, Wing Hung
通讯作者：
Wong, Wing Hung
影响因子：
14.9
作者：
Edgar, R;Domrachev, M;Lash, AE
通讯作者：
Lash, AE