About Hongmei Zhang

Dr. Hongmei Zhang is the Bruns Endowed Professor. Her research focus is on statistical methodology development in variable selection, joint clustering, and Bayesian networks with application to phenotypic data and genetic and epigenetic data. She is the recipient of several NIH research grants for her collaborative work in cancer and allergic disease studies.

Education

• PhD, Statistics, Iowa State University, Ames, IA
• MS, Statistics, Iowa State University, Ames, IA
• MS, Mathematics, Truman State University, Kirksville, MO
• MS, Electronic Engineering, Nanjing Research Institute of Technology, Nanjing, China

Research Interests

• Variable selection
• Clustering
• Gaussian direct and undirected networks
• Sampling plans

Selected Publications

1. H Zhang*, J Duan*, L Han*, … Arshad, S. H. DNA methylation at birth and IgE trajectories from birth to adolescence, different patterns between White and Asian. Epigenomics, 2025, 1–10. https://doi.org/10.1080/17501911.2025.2453412
2. A Mukhopadhyay, MH Mondol, M Rahman, ..., H Zhang, AMN Titu. The direct and urinary electrolyte-mediated effects of ambient temperature on population blood pressure: A causal mediation analysis. Environment international. 2025 Jan 1;195:109208
3. X Mou, H Zhang, SH Arshad. Generalized Bayesian Kernel machine regression. Statistical Methods in Medical Research. 2024 Dec 12: https://doi.org/10.1177/09622802241280784
4. X Huang, H Zhang. Detecting responsible nodes in differential Bayesian networks. Statistics in Medicine. June 03, 2024.  https://doi.org/10.1002/sim.10125
   C Wu, X Mou, H Zhang. Gbdmr: identifying differentially methylated CpG regions in the human genome via generalized beta regressions. BMC bioinformatics. 2024 Mar 5;25(1):97
5. S Carra, H Zhang, …, RJ Kurukulaaratchy. Adult Outcomes of Childhood Wheezing Phenotypes Are Associated with Early-Life Factors. Journal of Personalized Medicine. 2024; 14(12):1171. https://doi.org/10.3390/jpm14121171
6. M L Taylor, …, H Zhang, …, X Huang. Single Vesicle Surface Protein Profiling and Machine Learning-Based Dual Image Analysis for Breast Cancer Detection. Nanomaterials. 2024. 14(21), 1739
7. M Abrar, H Zhang, Y Jiang. Suggested guidelines in reporting results from mediation analysis, standardized or unstandardized? PLOS ONE. 2024 Sep 18;19(9):e0310429
   Rajesh Melaram*, J Adefisoye, DE Warden, S Potter, H Arshad, H Zhang*, Pollen exposures in pregnancy and early life are associated with childhood asthma incidence. World Allergy Organization Journal. 2024 Oct 1;17(10):100976
8. Y Jiang, H Zhang, S Chen, S Ewart, JW Holloway, H Arshad, W Karmaus. Intergenerational DNA methylation transfer from parents to offspring. Scientific Report. 2024 Aug 27;14(1):19812
9. E Lindner, B Pendley, H Zhang. Evaluation of the performance characteristics of a new chemical sensor, device, or method. Sensors and Actuators: B. Chemical. 2024 Jun 6:136087
   Mohammad Abrar, Y Jiang, H Zhang, L Li, H Arshad. Epigenetic features in newborns associated with preadolescence lung function and asthma acquisition during adolescence. Epigenomes. 2024 Mar 22;8(2):12
10. J Burch, A Delage, H Zhang, A McLain, M Ray, A Miller, S Adams, JR Hébert. Sleep Disorders and Cancer Incidence: Examining Duration and Severity of Diagnosis among Veterans. Frontiers in Oncology, section Cancer Epidemiology and Prevention. 2024. Vol. 14, doi: 10.3389/fonc.2024.1336487

Research Funding (active)

1. Clusters of Epigenetic Networks at Birth and Asthma Incidence in Children (PI)
   Funding Source: NIH/NIAID
2. Surface exosome integrin profiling to predict organotropic metastasis of breast cancer (Co-I). PI: Huang, Hoang
   Funding Source: NIH/NCI
3. Public Health Informatics, Data, Equity, Analytics, and Systems (PH-IDEAS) approach to strengthen Shelby County Health Department Infrastructure, Workforce, and Data Systems (Co-I). PI: Taylor, Joshi
   Funding Source: CDC

Software Packages

1. Programs and Examples for Joint Clustering (Download files)

• Readme file
• DataSimulations.R
• DetermineMDIC.R
• JointClusteringSimuDataSeSp.R

2. Programs and example data sets for variable selection in semi-parametric models (Download Files)

• Readme file
• VarSelection.Linear.standard.R
• VarSelection.Linear.MH.R.
• VarSelection.Probit.R
• Linear. Example3.txt
• Probit.Example3.txt

3.  Methods and programs for cell type heterogeneity assessment. Visit the website for codes, instructions, and example data sets. External website >