Bradley Olinger

SenCat catalogs senescence markers across 14 human cell types using transcriptomic and proteomic profiling, revealing shared metabolic pathways and enabling machine learning-based identification of senescent cells.

This study develops a nanoparticle-based proteomic workflow for low-volume mouse serum, identifying aging-associated proteins and demonstrating its utility in longitudinal studies.