Predicting complex phenotypes from genomic information is still a challenge. We use an evolutionarily informed machine learning approach within and across species to predict genes affecting nitrogen utilization in crops and show this approach is also useful in mammalian systems.
Dr. Chia-Yi Cheng is an Assistant Professor in the Department of Life Science at National Taiwan University. Trained as a plant developmental and genetic scientist at the University of North Carolina at Chapel Hill, she dived into bioinformatics during her postdoctoral training at J. Craig Venter Institute and was the lead scientist of the latest Arabidopsis annotation Araport11. Later at New York University, she integrated her wet and dry bench expertise and utilized machine learning strategy to uncover important genetics underlying a complex trait, nitrogen use efficiency. In her laboratory, her research interest is to understand how plants integrate responses to multiple stresses and optimize fitness using genetics, systems biology, and machine learning approaches.