Oncomine 3.0: Genes, Pathways, and Networks in a Collection of 18,000 Cancer Gene Expression Profiles

Daniel R. Rhodes(University of Michigan–Ann Arbor), Shanker Kalyana‐Sundaram(University of Michigan–Ann Arbor), Vasudeva Mahavisno(University of Michigan–Ann Arbor), Radhika Varambally(University of Michigan–Ann Arbor), Jianjun Yu(University of Michigan–Ann Arbor), Benjamin Briggs(University of Michigan–Ann Arbor), Terrence R. Barrette(University of Michigan–Ann Arbor), Matthew J. Anstet, Colleen Kincead-Beal, Prakash Kulkarni, Sooryanaryana Varambally(University of Michigan–Ann Arbor), Debashis Ghosh(University of Michigan–Ann Arbor), Arul M. Chinnaiyan(University of Michigan–Ann Arbor)
Neoplasia
February 1, 2007
Cited by 2,161Open Access
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Abstract

DNA microarrays have been widely applied to cancer transcriptome analysis; however, the majority of such data are not easily accessible or comparable. Furthermore, several important analytic approaches have been applied to microarray analysis; however, their application is often limited. To overcome these limitations, we have developed Oncomine, a bioinformatics initiative aimed at collecting, standardizing, analyzing, and delivering cancer transcriptome data to the biomedical research community. Our analysis has identified the genes, pathways, and networks deregulated across 18,000 cancer gene expression microarrays, spanning the majority of cancer types and subtypes. Here, we provide an update on the initiative, describe the database and analysis modules, and highlight several notable observations. Results from this comprehensive analysis are available at http://www.oncomine.org.


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