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Mengjie Chen is an Associate Professor in the Department of Medicine at the University of Chicago. With a PhD in Computational Biology from Yale University, he focuses on developing powerful statistical methods to address complex challenges in biological and biomedical data analysis, especially concerning epigenetics and cancer genomics. His research interests include Cancer Genomics, Single Cell Sequencing Analysis, and Statistical Genomics. Over the years, he has devised novel methodologies for various analytical problems, such as change point detection for identifying somatic copy number aberrations and nonparametric Bayesian methods integrated with somatic mutation heterogeneity for gene expression analysis. Additionally, he has created Gaussian graphical models for eQTL analysis and approaches for analyzing single-cell sequencing data. Ultimately, his work aims to create methods that integrate genomic features to predict clinical outcomes, which have the potential to advance personalized disease diagnosis and prognosis.
University of Chicago • Chicago, IL
Engaged in research and teaching in the fields of cancer genomics and statistical genomics.
Department of Philosophy