The increased use of RNA-seq for gene expression studies has driven an elevated need for easy-to-use bioinformatics tools for differential gene expression calculations and analysis coupled with expert-curated knowledge bases for pathway and biomarker discovery. However, limited expertise or access to bioinformatics solutions remains one of the main roadblocks for many research biologists.  
 
QIAGEN’s QIAseq RNA and miRNA library kits now provide complimentary access to the RNA-seq Analysis Portal, a comprehensive, integrated bioinformatics solution designed for biologists. The RNA-seq Analysis Portal includes sequence alignment, differential gene expression calculations with false discovery statistics, along with interpretation of gene expression results for top canonical pathways, upstream regulators and diseases. In addition, results from the RNA-seq Analysis Portal are immediately available in GeneGlobe to help researchers find real-time and digital PCR assays for subsequent biological verification and biomarker development. 

In this webinar, Dr. Samuel J. Rulli will introduce this new cloud-based solution and demonstrate how you can easily derive biological insights from RNA/miRNA NGS data without any additional software or hardware investments, installation or training.

About the speaker
Samuel Rulli, Ph.D., Associate Director, Global Product Management, Genomics
QIAGEN
Samuel Rulli is an R&D Scientist in qPCR applications at QIAGEN and has spent three years in the biotech industry as a qPCR specialist developing, evaluating, and teaching different qPCR technologies and applications. Dr. Rulli received his PhD in 2002 from Tulane University studying the gastric proton pump and did post-doctoral research at Johns Hopkins University and the National Cancer Institute in Frederick, MD. Trained as a molecular biologist, Dr. Rulli has worked on different assay detection technologies for gene expression and nucleic acid analysis.
Date of recording:Mittwoch, 23. Juni 2021
Duration:63 minutes
Categories
Webinar
Next Generation Sequencing