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Life Technologies Releases New Research Tool
Product News

Life Technologies Releases New Research Tool

Life Technologies Releases New Research Tool
Product News

Life Technologies Releases New Research Tool


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Knowledge of driver mutations is essential to research and development in the pharmaceutical industry for the identification of novel populations and discovery of new cancer drug targets.

Gene over-expression is one of the prevalent cancer driver events, but cancer transcriptome expression data generated in labs around the world are difficult to collect, combine, and analyze to better understand cancer biology.

Now, with the Life Technologies Oncomine NGS RNA-Seq Gene Expression Browser, researchers can immediately assess the frequency of molecular events across thousands of samples from the Oncomine NGS (Next-Generation Sequencing) collection, including tumor datasets from The Cancer Genome Atlas (TCGA).

The Oncomine NGS RNA-Seq Gene Expression Browser will be demonstrated at the Life Technologies booth #1415 during the AACR 105th Annual Meeting 2014 at the San Diego Convention Center, April 5 - 9.

The current Browser extends the Oncomine NGS Power Tools product offering, which includes the Mutation Browser, Fusion Browser and the Integrative Analysis Browser.

“Next-generation sequencing data is more accurate and has greater depth than data from older technologies for gene expression, such as microarrays,” said Dan Rhodes, vice president of bioinformatics for Life Sciences Solutions at Thermo Fisher Scientific. “But researchers struggle with how to take advantage of these data in order to gain the in depth knowledge required. Oncomine NGS Power Tools offer users solid data and analysis methods from a bioinformatics group with proven ability to harness and analyze large quantities of data.”

The new Oncomine Browser compiles the largest existing set of quality tumor RNA-Seq transcriptome expression data from publicly available sources.

The Browser enables researchers to identify potential cancer driver mutations via a simple, intuitive web-based application.

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