Post Doctoral Associate University of Georgia Athens, Georgia
Body of Abstract: Glycosyltransferases (GTs) catalyze the formation of glycosidic linkages to produce complex carbohydrates. This project involves the use of a multi-disciplinary, high-throughput (HTP) biochemical and computational biology approach to study carbohydrate metabolic processes in duckweed, a promising energy crop. The role of enzymatic microenvironments is being assessed through a combined proteomic and computational biology approach and this combined data will be used to populate a deep-learning framework to predict plant GT function. Functional validation achieved through this research will be used to assign gene function and study plant processes at the systems level to efficiently link genome sequence with gene function in a feedstock agnostic manner.