Dr. Chen’s primary research is driven by the need to develop powerful statistical methods to address the complex challenges posed by emerging technologies in data analysis and interpretation, particularly in the context of biological and biomedical studies such as epigenetics and cancer genomics. Dr. Chen has developed novel methodologies for a range of analytical problems, including change point detection for identifying somatic copy number aberrations, nonparametric Bayesian methods for integrating somatic mutation heterogeneity into gene expression analysis, Gaussian graphical models for eQTL analysis, and approaches for analyzing single-cell sequencing data. The ultimate goal of Dr. Chen’s work is to create methods that integrate genomic features into the prediction of clinical outcomes, with the potential to advance personalized disease diagnosis and prognosis.
Yale University
New Haven, CT, USA
PhD - Computational Biology
2014
Capturing cell-type-specific activities of cis-regulatory elements from peak-based single-cell ATAC-seq.
Capturing cell-type-specific activities of cis-regulatory elements from peak-based single-cell ATAC-seq. Cell Genom. 2025 Mar 12; 5(3):100806.
PMID: 40049167
m6A RNA modifications are measured at single-base resolution across the mammalian transcriptome.
m6A RNA modifications are measured at single-base resolution across the mammalian transcriptome. Nat Biotechnol. 2022 08; 40(8):1210-1219.
PMID: 35288668
Effective and scalable single-cell data alignment with non-linear canonical correlation analysis.
Effective and scalable single-cell data alignment with non-linear canonical correlation analysis. Nucleic Acids Res. 2022 02 28; 50(4):e21.
PMID: 34871454
Demystifying "drop-outs" in single-cell UMI data.
Demystifying "drop-outs" in single-cell UMI data. Genome Biol. 2020 08 06; 21(1):196.
PMID: 32762710
REPIC: a database for exploring the N6-methyladenosine methylome.
REPIC: a database for exploring the N6-methyladenosine methylome. Genome Biol. 2020 04 28; 21(1):100.
PMID: 32345346
RADAR: differential analysis of MeRIP-seq data with a random effect model.
RADAR: differential analysis of MeRIP-seq data with a random effect model. Genome Biol. 2019 12 23; 20(1):294.
PMID: 31870409
VIPER: variability-preserving imputation for accurate gene expression recovery in single-cell RNA sequencing studies.
VIPER: variability-preserving imputation for accurate gene expression recovery in single-cell RNA sequencing studies. Genome Biol. 2018 11 12; 19(1):196.
PMID: 30419955
Controlling for Confounding Effects in Single Cell RNA Sequencing Studies Using both Control and Target Genes.
Chen M, Zhou X. Controlling for Confounding Effects in Single Cell RNA Sequencing Studies Using both Control and Target Genes. Sci Rep. 2017 10 19; 7(1):13587.
PMID: 29051597
Genomic analysis of oesophageal squamous-cell carcinoma identifies alcohol drinking-related mutation signature and genomic alterations.
Chang J, Tan W, Ling Z, Xi R, Shao M, Chen M, Luo Y, Zhao Y, Liu Y, Huang X, Xia Y, Hu J, Parker JS, Marron D, Cui Q, Peng L, Chu J, Li H, Du Z, Han Y, Tan W, Liu Z, Zhan Q, Li Y, Mao W, Wu C, Lin D. Genomic analysis of oesophageal squamous-cell carcinoma identifies alcohol drinking-related mutation signature and genomic alterations. Nat Commun. 2017 05 26; 8:15290.
PMID: 28548104
SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling.
SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling. Genome Biol. 2017 04 08; 18(1):66.
PMID: 28390427
Alfred P. Sloan Research fellowship in Computational and Molecular Evolutionary Biology
the University of Chicago
2019
Junior Faculty Development Award
University of North Carolina - Chapel Hill
2015
Student Marshal
Yale Graduate School of Arts and Sciences
2014