Dr. Jinbo Bi is leading a team funded by the National Science Foundation to design new algorithms and statistical analytics for refining complex phenotypes. The research grant is entitled, “An Integrative Approach to Identifying Highly Heritable Subtypes of Complex Phenotypes”. Many complex phenotypes are defined using low-level phenotypic features and are substantially heterogeneous. Current statistical methods are ineffective to address this phenotypic heterogeneity, so they lack the power in the detection of genetic variation associated with the phenotype. The new methods will identify composite traits that are defined by combinations of low-level features, and that are more homogeneous than the commonly-used trait measures. These composite traits are most informative in genetic analysis. Her new algorithms will be validated in the areas of genetic selection of agriculturally-important animals and plants, and in the analysis of human diseases. This project serves as a vehicle to train graduate students in the multidisciplinary methods involving computer science and biology, and allows them to apply the methods in a variety of biological fields.