ONCOMINE: a cancer microarray database and integrated data-mining platform.

By Daniel R. Rhodes, Jianjun Yu, K. Shanker, Nandan P. Deshpande, Radhika Varambally, Debashis Ghosh, T. Barrette, Akhilesh Pandey, Arul M. Chinnaiyan. Neoplasia, 2004

3,463 citations recorded by the source corpus.

DNA microarray technology has led to an explosion of oncogenomic analyses, generating a wealth of data and uncovering the complex gene expression patterns of cancer. Unfortunately, due to the lack of a unifying bioinformatic resource, the majority of these data sit stagnant and disjointed following publication, massively underutilized by the cancer research community. Here, we present ONCOMINE, a cancer microarray database and web-based data-mining platform aimed at facilitating discovery from genome-wide expression analyses. To date, ONCOMINE contains 65 gene expression datasets comprising nearly 48 million gene expression measurements form over 4700 microarray experiments. Differential expression analyses comparing most major types of cancer with respective normal tissues as well as a variety of cancer subtypes and clinical-based and pathology-based analyses are available for exploration. Data can be queried and visualized for a selected gene across all analyses or for multiple genes in a selected analysis. Furthermore, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-drug target pairs to facilitate the discovery of novel biomarkers and therapeutic targets.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/eb960b5d56ed1368991eaa4f40cb7afee66edb1f

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Citations in the corpus

A hierarchical network of transcription factors governs androgen receptor-dependent prostate cancer growth. (2007, methodology): “To generate hypotheses on which factors might be responsible, we searched gene expression profiles from several human prostate cancer studies available on the Oncomine database ( Rhodes et al., 2004 ) and found the three transcription factors FoxA1, GATA2, and Oct1 to be of potential interest on the”
UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses (2017, methodology): “Oncomine [35,36] provides an interactive platform for gene expression profiling, using TCGA and other published cDNA, Affymetrix, and Illumina microarray data.”
Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression. (2005, methodology): “We identified four tumor profiling data sets from the Oncomine compendium (Rhodes et al., 2004) that fulfilled the same criteria that we used in the prostate cancer analyses (see above).”
Sharing Detailed Research Data Is Associated with Increased Citation Rate (2007, background): “Covariates included trial size, clinical endpoint, microarray platform, inclusion in various public databases, release of raw data, mention of supplementary information, and reference within the Oncomine[34] repository.”
Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. (2007, background): “results for a gene of interest across collected data sets [4].”
CellMiner: a relational database and query tool for the NCI-60 cancer cell lines (2009, neutral): “Oncomine [23] and GeneX [24] are two such user-friendly tools for storage and analysis of datasets collected from the literature or submitted by individual users.”
The Estrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer (2014, neutral): “Median-rank statistics results are reported for analyses with the Oncomine datasets 57 .”
Computational approaches in target identification and drug discovery (2016, methodology): “Oncomine, is a cancer microarray database and web-based data-mining platform aimed at facilitating discovery fromgenome-wide expression analyses, providingwith query and visualization tools for selected ormultiple genes across all analyses [34].”
MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype (2007, result): “In addition, we find that the deregulation of genes in the miRNA biogenesis pathway that we observed is in agreement with a number of independent data sets [ 98 ] (Additional data file 11).”