While there is great interest in the scientific community to investigate drug targets and biomarkers from public immune-oncology data, such investigation is hindered by the difficulty in finding and combining related datasets to perform large-scale meta-analyses. This webinar will focus on how high-quality curated genomic repositories such as QIAGEN OmicSoft Lands immediately allows in-depth investigations across diverse data sources (GEO, CPTAC, TCGA, GTEx and more) to discover and validate candidate checkpoint inhibitor drug targets and biomarkers.

You will learn how to do the following in the graphical user interface and through APIs:

- Easily identify relevant samples using extensive manually curated clinical metadata

- Visualize and identify checkpoint inhibition biology related drug target and biomarkers expression patterns using expression data (RNA-seq, scRNA-seq, proteomics etc.)

- Reveal how the expression of a group of biomarkers (or genes/proteins of interest) correlates in normal and disease tissue