We touch on the key highlights related to methods used & discoveries made in our published study across >26K samples.
We touch on the key highlights related to methods used & discoveries made in our published study across >26K samples.
To measure 120+ cytokines, chemokines, and immune- & neurology-related proteins from less than 25 μL of sample input.
Why PCA quality assessment workflows are critical to generating credible insights from high-dimensional omics data.
See how we used population-scale rLC-MS metabolomics data to develop an ML-based model to predict biological aging.
Detailing the rLC-MS method & its use to predict clinically relevant physiological states at scale in human populations.
This breakthrough mass spectrometry metabolomics study in >26,000 samples led to development of a metabolic aging clock.
Why careful metadata preprocessing is key ensure insights derived from downstream analysis are accurate & reproducible.
Why proteomics is critical to move beyond traditional known targets & biomarkers with mapping of non-canonical proteins.
Discussing how omics studies can answer more of the fundamental questions that drive successful drugs to market.
How metabolite biomarkers can speed GLP-1 agonist time-to-market & drive competitive advantages via novel insights.
