Reversing age by reprogramming gene expression networks - Medical Xpress

To read out the effects in their overexpression screen, the team had developed a "transcriptomic aging model" that can quantify age and the degree of rejuvenation based on changes in the expression of genes involved in different processes. Trained with gene expression data obtained from 464 fibroblast samples from donors across a wide range of ages, the machine learning-driven model provides an accurate overview of cells' age and health. Every organ and tissue progressively loses function and integrity as it ages.