Latest App Notes & Case Studies

A major challenge preventing transformative gene therapies from reaching patients is the lack of fit-for purpose potency assays, which are some of the most important assays in an analytical package but are often the most complex and high-risk.

While depleting abundant proteins can facilitate the detection of low-concentration biomarkers, such methods can be labor-intensive, costly and can result in sample loss. Discover how parallel accumulation, serial elution and fragmentation (PASEF) can support researchers to achieve accurate large-scale plasma proteomics.

Discover an automated solution for the consolidation and ranking of your metabolite structures. Explore a workflow that utilizes both EAD and CID data for the most confident characterization and streamlined data acquisition.

Discover an automated processing workflow that utilizes both EAD and CID data for the most confident characterization of pharmaceutical drug metabolites.

The ability to study transcript isoforms in detail could have a significant impact on our understanding of health and disease. However, most commonly, bulk sequencing is the selected method that only provides an average of the transcripts expressed across your sample of cells.

Developed for performance in human serum and plasma, the SomaScan Assay v4.1 can measure approximately 7,000 unique human protein analytes in small volumes of biological samples.

Download this app note to learn how you can select 20 individual CTCs in 10 minutes, this approach can be used for DNA, RNA or proteome analysis as well as how these target cells are selected and isolated in high purity from heterogenous backgrounds.

Metabolism has emerged as a key driver of T-cell antitumor function. This means that modulating metabolic programs of T cells can be used as a strategy to improve the antitumor efficacy of adoptive T-cell therapies.

The scale of research into potential gene therapies often means that work is distributed across multiple locations. Investigators must have confidence that the results obtained at one site are consistent with results obtained at other sites participating in the study.

Data-independent acquisition (DIA) has been shown to increase the quantitative reproducibility and accuracy of MS-based phosphoproteomics. This app note explores the impact of dia-PASEF on the speed and sensitivity of phosphoproteomics.