Jason Ernst, PhD

Jason Ernst, Ph.D. 

Assistant Professor, Biological Chemistry; Computer Science

Bio

Jason Ernst, Ph.D., develops and applies computational methods to improve the analysis of genomic data collected from cells. Ernst’s novel computing approaches enable researchers to effectively analyze and interpret the massive amounts of data generated when cells are studied using high-throughput genomic technologies. High-throughput technologies use specialized machines to collect millions of data points in parallel. Ernst’s methods are leading to a better understanding of gene regulation and the epigenome, which is the network of chemical compounds that surround DNA and play a role in determining which genes are active in a given cell. With this information, Ernst and his collaborators are gaining key insights into regions of the genome associated with common diseases.

Ernst is developing computational approaches that utilize machine learning to analyze epigenomic and other high-throughput data to understand diseases associated with the non-coding portion of the human genome. Only one percent of the human genome codes, or contains instructions, for proteins. Non-coding DNA play an important role in regulating gene expression. The majority of genetic variations that are associated with human diseases occur in non-coding portions of the genome. Ernst collaborates with colleagues applying his approaches to understand diseases including schizophrenia, bipolar disorder, autism and melanoma.

Working with stem cell center collaborators, Ernst used genomic data to understand how four specialized proteins called transcription factors are able to change the identity of skin cells to create induced pluripotent stem cells, which have the ability to turn into any cell type in the body. As the result of this research, Ernst and his colleagues discovered the role these transcription factors play in this remarkable process and used the data generated to predict additional transcription factors that could boost the cell reprogramming process. This led to the discovery of a fifth transcription factor that accelerated and enhanced the transition to pluripotency and increased the efficiency of the cell reprogramming process by a hundredfold. These pre-clinical findings could dramatically improve the efficiency of cell reprogramming to a pluripotent state, which would significantly advance therapies that aim to use induced pluripotent stem cells to regenerate damaged or diseased tissue.

Ernst earned a doctorate from the School of Computer Science at Carnegie Mellon University and completed post-doctoral training at the Massachusetts Institute of Technology.

Publications

Honors & Affiliations

Affiliations

  • Jonsson Comprehensive Cancer Center
  • Editorial Board, Genome Research
  • International Society for Computational Biology
  • American Society for Human Genetics

Funding

Ernst’s work is funded by the National Science Foundation, the National Institutes of Health, and the Kure It Foundation.