The general research interest of Dr. Zhou is to develop and apply novel Bayesian statistical methods to better design biological and clinical studies and properly analyze data generated from such studies. Her methodological interest include Bayesian hierarchical models, model selection and model averaging. She has developed a novel Bayesian hierarchical model to classify missense mutations of disease genes. She has written a software for accurate minimum inhibitory concentration (MIC) estimation based on growth curves generated from Phoenix Automated Susceptibility Testing System. She currently works on projects to develop novel statistical methods for improved assessment of molecular signatures using microarrays and to develop comprehensive prognostic models for esophageal cancer using Bayesian approaches (funded by NIH/NCI). She has been collaborating extensively with researchers at WCMC with a focus on cancer related laboratory and clinical studies.