Department of Medicine
Mengjie Chen’s interests include the utilization of statistical methods to address the challenges of high-throughput technologies, particularly for data emerging from such biological and biomedical studies as epigenetic and cancer genomics–related research. She has developed novel methodologies for a variety of problems, including change point detection methods for identifying somatic copy number aberration, nonparametric Bayesian methods to integrate the heterogeneity in somatic mutations into gene expression analysis, Gaussian graphical models for eQTL analysis, and methods for the analysis of single-cell sequencing data. Her goal is to develop methods that can integrate genomic features into the prediction of clinical outcomes, which will potentially shed new light on personalized disease diagnosis and prognosis.
She graduated with an undergraduate degree in biotechnology from Huazhong University of Science and Technology in China and received her PhD in computation biology and bioinformatics from Yale University. Most recently, she was an assistant professor in the Department of Biostatistics and Genetics at the University of North Carolina at Chapel Hill.