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      GENT: Gene Expression Database of Normal and Tumor Tissues

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          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/.

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          Most cited references9

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          NCBI GEO: archive for high-throughput functional genomic data

          The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as ‘Minimum Information About a Microarray Experiment’ (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.
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            Is Open Access

            ArrayExpress update—from an archive of functional genomics experiments to the atlas of gene expression

            ArrayExpress http://www.ebi.ac.uk/arrayexpress consists of three components: the ArrayExpress Repository—a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse—a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas—a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200 000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently—ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.
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              A global map of human gene expression.

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                Author and article information

                Journal
                Cancer Inform
                101258149
                Cancer Informatics
                Libertas Academica
                1176-9351
                09 May 2011
                2011
                : 10
                : 149-157
                Affiliations
                [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
                [4 ]Korean Bioinformation Center
                [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
                Author notes
                [#]

                These two authors contributed equally to this work.

                Corresponding author email: kimsy@ 123456kribb.re.kr
                Article
                cin-1-2011-149
                10.4137/CIN.S7226
                3118449
                21695066
                ca6cd9a2-4416-4832-9b7a-3bfa62c4ecac
                © the author(s), publisher and licensee Libertas Academica Ltd.

                This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.

                History
                Categories
                Database Review

                Oncology & Radiotherapy
                gene expression,cancer,human tissues,affymetrix
                Oncology & Radiotherapy
                gene expression, cancer, human tissues, affymetrix

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