Oncomine

Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. 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.


References in zbMATH (referenced in 7 articles )

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  1. Mathé, Ewy (ed.); Davis, Sean (ed.): Statistical genomics. Methods and protocols (2016)
  2. Natarajan, Loki; Pu, Minya; Messer, Karen: Statistical tests for the intersection of independent lists of genes: sensitivity, FDR, and type I error control (2012)
  3. Zeisel, Amit; Zuk, Or; Domany, Eytan: FDR control with adaptive procedures and FDR monotonicity (2011)
  4. Rouam, Sigrid; Moreau, Thierry; Broët, Philippe: Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes (2010) ioport
  5. Jeffries, Clark D.; Ward, William O.; Perkins, Diana O.; Wright, Fred A.: Discovering collectively informative descriptors from high-throughput experiments (2009) ioport
  6. Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin: Quantitative comparison of microarray experiments with published leukemia related gene expression signatures (2009) ioport
  7. Pitzer, Erik; Lacson, Ronilda; Hinske, Christian; Kim, Jihoon; Galante, Pedro A. F.; Ohno-Machado, Lucila: Towards large-scale sample annotation in gene expression repositories (2009) ioport