Clarice Hong

Clarice Hong is an MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellow whose research focuses on understanding how different cell types are encoded by the same genome and how gene expression programs are robustly activated and maintained. Her doctoral research explored how cis-regulatory elements regulate gene expression using a variety of massively parallel reporter gene-based assays. Although this work generated sufficient data to build quantitative predictive models of gene expression, measuring only gene expression was not sufficient for understanding the mechanisms underlying cis-regulatory interactions. As a postdoctoral fellow, she will approach this question from the perspective of 3D genome structure, applying machine learning models trained on low-resolution 3D genome maps and epigenomic data to predict 3D contact maps at high resolution across the genome in a cell-type specific manner. This innovative approach could solve one of the biggest problems in obtaining high-resolution human genome maps, which typically require enormous sequencing at great cost. Her work holds the potential to unlock the complex, cell-type-specific rules of gene regulation using the powerful tools of machine learning methods.