Scientifically, I am interested in machine learning, statistical modeling, genomics, and biomedical informatics, especially as they relate to human health. My current research focuses on developing and applying new computational tools and frameworks to improve diagnostic rates for people with suspected Mendelian disorders. I am developing new approaches to detect defects in RNA splicing from patient RNA-seq or to predict such changes directly from patient exome or genome sequencing.
Prior to starting my MD-PhD, I studied at University of Alabama for four years, receiving an M.A. in Mathematics and a B.S. in Mathematics and Physics. My master's thesis investigated the application of probabilistic graphical models to metabolomics data. I also spent two summers at University of North Carolina Chapel Hill creating computational physics simulations of the yeast mitotic spindle.
Random forest analysis of untargeted metabolomics data suggests increased use of omega fatty acid oxidation pathway in Drosophila melanogaster larvae fed a medium chain fatty acid rich high-fat diet.
Van Hove JLK.
Variant non ketotic hyperglycinemia is caused by mutations in LIAS, BOLA3 and the novel gene GLRX5.