In order to reconstruct high quality plant genome-scale metabolic model, the group works to establish deep learning algorithms to annotate proteins and enzymes function such as protein membrane permeability and enzyme specificity. We are working on reconstruction of plant genome-scale metabolic models to simulate plant metabolic fluctuation under stresses or engineering. Specifically, we are targeting key genes to improve plant resistance under stresses and the increase of natural product yield as synthetic chassis, based on a cycle of Model-prediction, Design, Build, Test and Model-improvement.       

The group currently has 12 members, including:1 Principal Investigator (PI), 2 senior researchers, 2 research assistants,1 Ph.D student, 6 master students.