This post is authored by Gnosis Data Analysis I.K.E.
We are proud to announce a new release for BioSignature Discoverer, the plugin specifically devised for identifying collection of biomarkers in omics data.
The new version of the plug-in comes with several important improvements, including:
- A sophisticated data analysis pipeline featuring several additional state-of-the-art statistical and machine-learning algorithms
- More precise estimation of biomarkers diagnostic/prognostic capabilities, especially for low sample sizes
- Faster computational performance, with the additional possibility of parallelizing the computations across several cores
- More informative reports and graphics for getting immediate insights into your results
The new release immediately follows the first scientific publication demonstrating the applicability of BioSignature Discoverer in practice:
Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower.
This work employs BioSignature Discoverer for identifying biomarkers characterizing leaf senescence in sunflower plants. The biomarkers allow a net separation across the senescence stages of the plants, and were identified by integratively analyzing transcriptomics and metabolomics information.
About Gnosis Data Analysis
Gnosis Data Analysis I.K.E. is a university spin-off of the University of Crete whose mission is empowering companies and research institutions with powerful data analysis solutions and services.
For more details about the BioSignature Discoverer plug-in, please visit the dedicated plug-in page.
For more information about Gnosis Data Analysis, please visit their website.