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      NCBI GEO: mining millions of expression profiles—database and tools

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          Abstract

          The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30 000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

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          Most cited references11

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          Coexpression analysis of human genes across many microarray data sets.

          We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function. Copyright 2004 Cold Spring Harbor Laboratory Press
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            Is Open Access

            Bioinformatics

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              Database resources of the National Center for Biotechnology Information: update

              In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website. NCBI resources include Entrez, PubMed, PubMed Central, LocusLink, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SARS Coronavirus Resource, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov .
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                1 January 2005
                17 December 2004
                : 33
                : Database Issue
                : D562-D566
                Affiliations
                National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD, USA
                Author notes
                [*]

                To whom correspondence should be addressed. Tel: +301 435 3449; Fax: +301 480 0109; Email: edgar@ 123456ncbi.nlm.nih.gov

                [a]

                Present address: Alex E. Lash, Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

                [a]

                Present address: Wataru Fujibuchi, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan

                [a]

                The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use permissions, please contact journals.permissions@ 123456oupjournals.org .

                [a]

                © 2005, the authors

                Article
                gki022
                10.1093/nar/gki022
                539976
                15608262
                c4036679-7255-4c89-ad9e-29b9cf93451f
                Copyright © 2005 Oxford University Press
                History
                : 2 September 2004
                : 21 September 2004
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                Genetics
                Genetics

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