Nucleic Acids Research, 2005, Vol. 33, Database issue D562-D566
© 2005, the authors
Nucleic Acids Research, Vol. 33, Database issue © Oxford University Press 2005; all rights reserved
NCBI GEO: mining millions of expression profilesdatabase and tools
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD, USA
* To whom correspondence should be addressed. Tel: +301 435 3449; Fax: +301 480 0109; Email: edgar{at}ncbi.nlm.nih.gov
Present addresses: Alex E. Lash, Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
Wataru Fujibuchi, Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan
Received September 2, 2004; Accepted September 21, 2004
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.
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{at}oupjournals.org.
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T. F. Ducey, M. B. Carson, J. Orvis, A. P. Stintzi, and D. W. Dyer Identification of the Iron-Responsive Genes of Neisseria gonorrhoeae by Microarray Analysis in Defined Medium J. Bacteriol., July 15, 2005; 187(14): 4865 - 4874. [Abstract] [Full Text] [PDF] |
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S. H. Chen, Y. Babichev, N. Rodrigues, D. Voskas, L. Ling, V. P. K. H. Nguyen, and D. J. Dumont Gene expression analysis of Tek/Tie2 signaling Physiol Genomics, July 14, 2005; 22(2): 257 - 267. [Abstract] [Full Text] [PDF] |
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A. Boorsma, B. C. Foat, D. Vis, F. Klis, and H. J. Bussemaker T-profiler: scoring the activity of predefined groups of genes using gene expression data Nucleic Acids Res., July 1, 2005; 33(suppl_2): W592 - W595. [Abstract] [Full Text] [PDF] |
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