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Qlucore and Nebion collaboration aims to enhance gene expression analysis

Qlucore and Nebion have started a collaboration to provide scientists with an end-to-end solution for gene expression analysis, by combining Qlucore Omics Explorer and Genevestigator into a single end to end software package.

In 2018 Qlucore and Nebion will collaborate closely to support the research community in the combined use of Qlucore Omics Explorer and Genevestigator for advanced gene expression analyses. Both companies announced that they will host targeted seminars and webinars for research biologists in order to demonstrate how to utilise these tools for data exploration and analysis.

‘We are delighted to announce the close collaboration between Nebion and Qlucore and educate biologists in how they can benefit from using the combination of these powerful and user-friendly tools for data analysis and interpretation’, says Carl-Johan Ivarsson President of Qlucore.

Qlucore Omics Explorer and Genevestigator are complementary tools which, when used together, provide scientists with a range of options from data storage, pre-processing, analysis, interpretation to comparison with public datasets.

Specifically, the combination enables users to analyse expression datasets in full detail, characterise gene lists and interpret results in a broad biological context. Qlucore and Nebion thereby provide a straightforward solution to streamline efforts in translational medicine and drug discovery.

The amount of gene expression data being produced in labs around the globe is exploding, particularly from the use of RNA-Sequencing. Decreasing costs for data generation have made these technologies accessible to the broader research community. However, the data produced is complex and challenging for labs without the relevant bioinformatics skills. Consequently, there is a strong need for tools that facilitate advanced expression data analysis for scientists.

For Dr Philip Zimmermann, CEO of Nebion, ‘this collaboration demonstrates how advanced statistics and search engine technology can help making expression data analysis easier and more meaningful. The combination of our tools will allow biologists to see both the details of their study and the broader picture by integration with curated public studies.’

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