Project Summary

Aging is a process that affects every human body. While we are gradually recognizing the different pathways involved in the aging process, one open question relates to the distribution of noisy or variable expression across the transcriptome. Do genes get more variable during the aging process that results in de-regulation, or do certain genes get too stable and static as cells age? We posit that it’s a combination of the two, and where these too-noisy, too-static genes are distributed within a pathway is the key to predicting the healthy agers from the poor ones. Using stem cells, this projects aims to develop models that quantify the noise occurring in gene expression as single cells age, and develop statistical classifiers that predict healthy aging profiles.

Research Group

Mar Group


Single cell RNA-seq, stem cells, aging, transcriptional regulation, Bayesian methods, machine learning.

Project members

Associate Professor Jessica Mar

Group Leader
Mar Group