GENT: Gene Expression Database of Normal and Tumor Tissues

Author:

Shin Gwangsik12,Kang Tae-Wook34,Yang Sungjin12,Baek Su-Jin35,Jeong Yong-Su6,Kim Seon-Young345

Affiliation:

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

2. NGIC inc. 381 Beonji, Mannyeon-dong, Seo-gu, Daejeon 302-834

3. Medical Genomics Research Center, University of Science and Technology, KRIBB

4. Korean Bioinformation Center, University of Science and Technology, KRIBB

5. Department of Functional Genomics, University of Science and Technology, KRIBB

6. Department of Genetic Engineering, College of Life Science and Graduate School of Biotechnology, Kyung Hee University, Yongin-si, Gyeonggi-do, 446–701, Republic of Korea.

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/ .

Publisher

SAGE Publications

Subject

Cancer Research,Oncology

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