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The amount of gene expression data in the public repositories, such as NCBI Gene Expression Omnibus (GEO) has grown exponentially, and provides a gold mine for bioinformaticians, but has not been easily accessible by biologists and clinicians. We developed an automated approach to annotate and analyze all GEO data sets, including 1,515 GEO data sets from(More)
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