Thesis Defense Announcement: Eric Schultz

The ability to predict gene expression is an essential test of our understanding, and improving our understanding of gene expression is crucial to future advances in the fields of human genetics, precision medicine, and evolutionary biology. Challengingly, the regulation of gene expression depends on a complex interplay of factors, including the gene's DNA sequence, the gene's three-dimensional structure, chemical modifications to the DNA (i.e., epigenetics), environmental factors, cell-type-specific transcription factor activity, etc. In this work, I present advances in a) our ability to efficiently model DNA structure using machine learning and physics-based modeling and b) our ability to predict gene expression from DNA sequence using machine learning. Ultimately, I present advances in our understanding of two of the factors that explain gene expression: DNA sequence and DNA structure.

Zoom Link: https://uchicago.zoom.us/j/92904318620?pwd=paYBVB3xBOKhbF9GkaGoRzd3N5WcT1.1&from=addon

(passcode 171411)