Unveiling Senescence with SenCID

Researchers have developed a machine learning tool named SenCID to identify senescent cells in various biological samples using bulk and single-cell RNA sequencing data. Published in Cell Metabolism, the tool analyzes data from 602 samples across 52 senescence-related studies. SenCID distinguishes six major senescence identities, offering insights into their distinct functions, responses to treatments, and involvement in aging and diseases such as COVID-19. This breakthrough aids in the precision targeting of senescent cells, enhancing therapeutic interventions.