Data science provides genomic guide to health and disease

By John Sullivan
January 04, 2018

This article is from the Winter 2018 EQuad News.

Scientific graphic of human body

What are the odds that a statistician would work beside doctors at top medical schools?

These days, pretty high.

Barbara Engelhardt, an assistant professor of computer science, specializes in Bayesian statistics, a method of weighting statistical analysis to interpret challenging data. Her research team develops methods to harness biomedical data with machine learning and statistical inference. The result offers doctors a better understanding of disease.

Her team is developing systems to predict the onset of sepsis and other conditions in hospital patients and to better understand the role of genetics in disease. Recently, Engelhardt was a leader of a multi-university consortium that studied genetic expression related to a variety of tissues in the body as a step toward creating a genetic map for healthy tissues.

“The ultimate goal is to understand gene expression and gene regulation in a diversity of different tissue types,” she said. “That is absolutely critical to understanding how dysregulation can lead to disease.”