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GENT:正常和肿瘤组织的基因表达数据库。

GENT: gene expression database of normal and tumor tissues.

作者信息

Shin Gwangsik, Kang Tae-Wook, Yang Sungjin, Baek Su-Jin, Jeong Yong-Su, Kim Seon-Young

机构信息

Department of Bio and Information Technology, Graduate School, Chungbuk National University, 410 Seongbong-ro, Heungdeok-gu, Cheongju, Chungbuk, 361-763.

出版信息

Cancer Inform. 2011;10:149-57. doi: 10.4137/CIN.S7226. Epub 2011 May 9.

Abstract

BACKGROUND

Some oncogenes such as ERBB2 and EGFR are over-expressed in only a subset of patients. Cancer outlier profile analysis is one of computational approaches to identify outliers in gene expression data. A database with a large sample size would be a great advantage when searching for genes over-expressed in only a subset of patients.

DESCRIPTION

GENT (Gene Expression database of Normal and Tumor tissues) is a web-accessible database that provides gene expression patterns across diverse human cancer and normal tissues. More than 40000 samples, profiled by Affymetrix U133A or U133plus2 platforms in many different laboratories across the world, were collected from public resources and combined into two large data sets, helping the identification of cancer outliers that are over-expressed in only a subset of patients. Gene expression patterns in nearly 1000 human cancer cell lines are also provided. In each tissue, users can retrieve gene expression patterns classified by more detailed clinical information.

CONCLUSIONS

The large samples size (>24300 for U133plus2 and >16400 for U133A) of GENT provides an advantage in identifying cancer outliers. A cancer cell line gene expression database is useful for target validation by in vitro experiment. We hope GENT will be a useful resource for cancer researchers in many stages from target discovery to target validation. GENT is available at http://medicalgenome.kribb.re.kr/GENT/ or http://genome.kobic.re.kr/GENT/.

摘要

背景

一些癌基因,如ERBB2和EGFR,仅在一部分患者中过度表达。癌症异常值分析是在基因表达数据中识别异常值的计算方法之一。在搜索仅在一部分患者中过度表达的基因时,具有大样本量的数据库将具有很大优势。

描述

GENT(正常和肿瘤组织基因表达数据库)是一个可通过网络访问的数据库,提供不同人类癌症和正常组织中的基因表达模式。通过Affymetrix U133A或U133plus2平台在全球许多不同实验室进行分析的超过40000个样本,从公共资源中收集并合并成两个大数据集,有助于识别仅在一部分患者中过度表达的癌症异常值。还提供了近1000个人类癌细胞系中的基因表达模式。在每个组织中,用户可以检索按更详细临床信息分类的基因表达模式。

结论

GENT的大样本量(U133plus2大于24300,U133A大于16400)在识别癌症异常值方面具有优势。癌细胞系基因表达数据库对于通过体外实验进行靶点验证很有用。我们希望GENT将成为癌症研究人员从靶点发现到靶点验证的许多阶段的有用资源。可通过http://medicalgenome.kribb.re.kr/GENT/或http://genome.kobic.re.kr/GENT/访问GENT。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7331/3118449/f2bb100f644b/cin-1-2011-149f1.jpg

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