Anusri Pampari

In multicellular organisms, different cell types exhibit vastly different functions despite sharing fundamentally the same DNA sequence. These differences stem from the cell-type specific activity (expression) of genes via a complex “gene regulatory” DNA code. Disruptions to this regulatory DNA code can result in dysregulation of gene expression in human cells, causing complex diseases such as initiation and metastases of cancer. However, the regulatory code of the genome remains relatively unexplored. My work will develop base-resolution deep learning models to accurately predict regulatory sequence from functional assays such as histone modification and chromatin accessibility profiles. I will use these models to elucidate the regulatory activity changes in thyroid cancer, which is the most common cancer of hormone producing tissue with high heritability and metastases frequency. I will further collaborate with experimentalists to validate the hypothesis generated by the model to derive potential regulatory mechanisms resulting in thyroid cancer.