My research goal is to use machine learning algorithms, informed by systems biology, structural biology and genomics, to identify molecular mechanisms of rare genetic diseases. I have developed a digenic classifier (DiGePred), trained on known cases of digenic disease, that predicts the potential for a given pair of genes, simultaneously harboring rare variants, to lead to a digenic disease in a patient. We are applying the classifier on gene pairs from patients of the Undiagnosed Diseases Network (UDN) to find cases of digenic disease. I am also working on structural biology methods to calculate the destabilization potential around every amino acid on every protein structure. This will allow us to lend more context to predicted protein destabilization (ddG) scores arising from single amino acid substitutions, and to help us better interpret the functional effects of rare missense variants.