TechValidate Research on QIAGEN Digital Insights

Enable to explore public data for biomarker discovery and development

Improve efficiency of information capture, inspire new ideas, promote integrative research

Huge amount of good quality data already available that can be used as a benchmark for other solutions.

Standardized and cleaned up the public data from various sources, made them easy to visualize and compare across different data sets, including internal data.

Great for spot-checking expression of genes of interest across a range of disease conditions.

There are many datasets including psoriasis and atopic dermatitis tissues that I will be mining.

We use it for target credentialing and biological context of empirical experimental data.

Helps accessing the whole public data to learn about Expression and Regulation of genes in tissues and diseases of interest.

Huge value in aligning novel experimental datasets to a broad range of published literature, to explore synergies, understand mechanisms and look for potential therapeutic risks.

Omicsoft has nice tool (calling isoforms). Lands are very important dataset to validate some of our hypothesis.

Easy access to a huge amount of data without the need to invest many months or years establishing our own pipelines and checking outputs.

It enables quick look ups across transcriptomics studies with possibility to zoom in on particular subsets of interest, e.g. sample types, diseases, or genes of interest. So speedy!

The biofinformatics products that QIAGEN provides have allowed our lab to better integrate data from various studies together and have allowed for more efficient analysis.

It is a great way (IPA) to make use of large gene expression datasets instead of picking your favorite gene and ignoring the rest.

Improves work efficiency and saves a lot of time for analysis of data.

We have published several papers utilizing IPA software. The software is currently a standard tool for proteomics or RNA-seq analysis.

We have many groups use IPA. It is nearly a routine software for research

We were able to identify key pathways that our drug of interest perturbed, helping to elucidate disease biology and better understand the molecular changes upon ligand treatment.

IPA is an important software in our lab, we have a lot of RNAseq and single-cell sequencing projects. IPA enable us to convey all kinds of the downstream analysis on our data.

Undoubtedly improved our ability to diagnose previously undiagnosed patients with rare genetic diseases.

We use IPA daily, which helps us generate hypothesis and possible signaling pathway analysis.

IPA is widely used by both dry and wet lab scientists.

Plays a big role in our data interpretation.