Headshot portrait of Peyton Greenside - Morgridge Family SIGF Fellow
Bio-X SIGF Graduate Student Fellow

Awarded in 2015
Home Department: Biomedical Informatics
Faculty Advisors: Anshul Kundaje (Genetics, Computer Science) and Thomas Quertermous (Cardiovascular Medicine)

Research Title: Interpretable deep learning approaches to understand the genetic and regulatory basis of coronary artery disease

Research Description: The majority of genetic variants associated with disease phenotypes fall in Photo of Peyton Greenside.regions of the genome that do not code for proteins. A large barrier to understanding the genetic basis of disease is understanding the functional implications and mechanisms by which these non-coding variants disrupt normal cellular function. Using machine learning methods, Peyton is developing computational models to understand how non-coding variants lead to disease. She is particularly interested in learning gene regulatory programs that become altered in disease development and how variants identified through genome-wide association studies (GWAS) may alter these regulatory programs.


Peyton is co-founder and CSO of BigHat Biosciences.