GenePattern 2.0 (original) (raw)
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- Published: 01 May 2006
Nature Genetics volume 38, pages 500–501 (2006)Cite this article
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To the Editor:
Whole-genome expression profiling has created a revolution in the way we study disease and basic biology. Since 1997, the number of published results based on an analysis of gene expression microarray data has grown from 30 to over 5,000 publications per year. Sophisticated mathematical methods have been developed for use in patient diagnosis and prognosis, identification of new drug targets and understanding biological mechanisms. However, these tools are often out of the direct reach of the biomedical researchers who can so critically benefit from them because they can be difficult to understand and use correctly. This challenge is even more relevant in the context of 'integrative' approaches, where a multitude of data sources and methods are combined in the analysis of a single problem.
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Figure 1: GenePattern pipelines.
References
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Article CAS Google Scholar - Gentleman, R. Stat. Appl. Genet. Mol. Biol. [online] 4, 2 (2005) <http://www.bepress.com/sagmb/vol4/iss1/art2>.
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Authors and Affiliations
- Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, 02142, Massachusetts, USA
Michael Reich, Ted Liefeld, Joshua Gould, Jim Lerner, Pablo Tamayo & Jill P Mesirov
Authors
- Michael Reich
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You can also search for this author inPubMed Google Scholar - Jim Lerner
You can also search for this author inPubMed Google Scholar - Pablo Tamayo
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Reich, M., Liefeld, T., Gould, J. et al. GenePattern 2.0.Nat Genet 38, 500–501 (2006). https://doi.org/10.1038/ng0506-500
- Issue Date: 01 May 2006
- DOI: https://doi.org/10.1038/ng0506-500