Biography
Min Zhang, MD, PhD, is a professor in the Department of Epidemiology & Biostatistics and director of Biostatistics Shared Resource of the UCI Chao Family Comprehensive Cancer Center. Her research includes statistical inference for -omics data including genomic, epigenetic, transcriptomic, proteomic, and metabolomic data (e.g., bulk and single-cell RNA-Seq, single-cell ATAC-Seq, nuclear magnetic resonance spectra data, and mass spectrometry data); statistical methods for genome-wide association studies (GWAS, both family-based and population-based); genomic selection; integrative omics data analysis; machine learning; quantitative trait loci (QTL) mapping; molecular marker profiling; statistical and computational methods for biomarker identification; transcriptome-wide gene regulatory network construction. Prior to UCI, she was at Purdue University, where she was a Professor in the Department of Statistics for nearly 20 years and the Associate Director of Data Science at the NCI-designated Purdue University Center for Cancer Research.
Research Interests
Dr. Zhang's research interests include bioinformatics, statistical genetics and genomics, machine learning, genome-wide association studies, and RNA-seq data analysis.
Current Projects/Studies
- “Big Data Training for Cancer Research” 2019-2024. Role: PI.
- “Administrative Supplement to Big Data Training for Cancer Research” 2023-2024. Role: PI.
- “Modeling Functional Genomics of Susceptibility to the Persistent Effects of Environmental Toxins in an Early Rural Indiana Neurodegenerative Cohort” 2022-2027. Role: MPI (with Bowman, Yuan).
- “Administrative Supplement to Modeling Functional Genomics of Susceptibility to the Persistent Effects of Environmental Toxins in an Early Rural Indiana Neurodegenerative Cohort” 2023-2024. Role: MPI (with Bowman, Yuan).
- “Modeling Homeostasis of Human Blood Metabolites” 2020-2025. Role: MPI (with Raftery, Zhang).
Education
- PhD in Biological Statistics and Computational Biology from Cornell University, Ithaca, NY, 2005
- MS in Biometry, Cornell University, Ithaca, NY, 2003
- PhD in Neurophysiology, Peking University Health Science Center, Beijing, China, 1998
- MD, Hebei Medical University, Hebei, China, 1992
Honors and Awards
- 2022 Regina and Norman F. Carroll Research Award, College of Science, Purdue University
- 2020 Excellence in Research Award, Purdue University
- 2020 3rd Place, the HackingToCureMichael Hackathon
- 2017 Excellence in Research Award, Purdue University
- 2017 Engagement Award, College of Science, Purdue University
- 2011/2010/2009 Seed for Success Award, Purdue University
Publications
Liu D, Gowda GAN, Jiang Z, Alemdjrodo K, Zhang M*, Zhang D*, Raftery D* (* co-corresponding authors, 2024) Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts. Proceedings of the National Academy of Sciences (PNAS). 121(8):e2307430121. doi: 10.1073/pnas.2307430121.
Jiang Z, Chen C, Xu Z, Wang X, Zhang M, Zhang D (2023). SIGNET: transcriptome-wide causal inference for gene regulatory networks. Scientific Reports. 08 November 2023.
Liu D, Yang Z, Chandler K, Oshodi A, Zhang T, Ma J, Kusumanchi P, Huda N, Heathers L, Perez K, Tyler K, Ross R, Jiang Y, Zhang D*, Zhang M*, Liangpunsakul S*. (* co-corresponding authors, 2021). Serum metabolomic analysis reveals several novel biomarkers in association with excessive alcohol use – an exploratory study. Translational Research. (DOI: 10.1016/j.trsl.2021.10.008).
Chen C, Zhang D*, Hazbun T*, Zhang M*. (*co-corresponding authors, 2019). Inferring gene regulatory networks from a population of yeast segregants. Scientific Reports. 9(1):1197.
Chen C, Ren M, Zhang M, and Zhang D. (2018). A two-stage penalized least squares method for constructing large systems of structural equations. Journal of Machine Learning Research. 19.
Guan L, Wang Q, Wang L, Wu B, Chen Y, Liu F, Ye F, Zhang T, Li K, Yan B, Lu C, Su L, Jin G, Wang H, Tian H, Wang L, Chen Z, Wang Y, Chen J, Yuan Y, Cong W, Zheng J, Wang J, Xu X, Liu H, Xiao W, Han C, Zhang Y, Jia F, Qiao X, Genetic REsearch on schizophreniA neTwork-China and Netherland (GREAT-CN), Zhang D, and Zhang M*, and Ma H* (*co-corresponding authors, 2016). Common variants on 17q25 and gene-gene interactions conferring risk of schizophrenia in Han Chinese population and regulating gene expressions in human brain. Molecular Psychiatry. 21(9): 1244-1250.
Zhang M, Zhang D, and Wells MT. (2010). Generalized thresholding estimators for high-dimensional location parameters. Statistica Sinica, 20: 911-926.
Zhang M, Strawderman R, Cowen M, and Wells MT. (2006). Bayesian Inference for a two-part hierarchical model: an application to profiling providers in managed health care. Journal of the American Statistical Association, 101: 934-945.
