Hongmei Zhang

Hongmei Zhang, PhD, MS

Professor and Director, Division of Epidemiology, Biostatistics, and Environmental Health, and Program Coordinator for Biostatistics

224 Robison Hall
Office Hours
By appointment only

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.


  • 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
  • Bayesian network
  • Sampling plans

Selected Publications

  1. H Zhang, A Kaushal*, N Soto-Ramirez, AH Ziyab, S Ewart, JW Holloway, W Karmaus, H Arshad. Acquisition, Remission, and Persistence of Eczema, Asthma, and Rhinitis in Children. Clinical and Experimental Allergy (accepted).
  2. H Zhang, Y Zou*, W Terry*, W Karmaus, H Arshad. Joint clustering with correlated variables. The American Statistician (accepted).
  3. A Kaushal*, H Zhang, W Karmaus, M Ray, MA Torres, AK Smith, S Wang. Comparison of different cell type correction methods for genome-scale epigenetics studies. BMC Bioinformatics. Vol. 18, 216. 2017.
  4. N Soto-Ramirez, S Kar, H Zhang, W Karmaus. Infant feeding patterns and eczema in children in the first 6 years of life. Clinical and Experimental Allergy. Vol. 47, 1285–1298. 2017.
  5. A Chan, W Terry*, H Zhang, W Karmaus, S Ewart, J Holloway, G Roberts, R Kurukulaaratchy, H Arshad. Filaggrin Mutations Increase Allergic Airway Disease in Childhood and Adolescence Through Interactions with Eczema and Aeroallergen Sensitization. Clinical and Experimental Epidemiology. doi: 10.1111/cea.13077. 2017. [Epub ahead of print].
  6. W Karmaus, N Soto-Ramirez, H Zhang. Infant feeding pattern in the first six months of age in USA: A follow-up study. International Breastfeeding Journal. Vol. 12. doi: 10.1186/s13006-017-0139-4. eCollection. 2017.
  7. JF Felix, ...., H Zhang, ..., SJ London. Cohort profile: Pregnancy And Childhood Epigenetics (PACE) Consortium. International Journal of Epidemiology. doi: 10.1093/ije/dyx190. 2017. [Epub ahead of print].
  8. S Chen, N Mukherjee, VD Janjanam, SH Arshad, RJ Kurukulaaratchy, JW Holloway, H Zhang, W Karmaus. Consistency and variability of DNA methylation in women during puberty, young adulthood and pregnancy. Vol. 9. Genetics and Epigenetics. DOI: 10.1177/1179237X17721540. 2017.
  9. GC Sharp, ..., H Zhang, ..., CL Relton. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: Findings from the Pregnancy and Childhood Epigenetics (PACE) consortium. Human Molecular Genetics, ddx290, https://doi.org/10.1093/hmg/ddx290. 2017.
  10. A Kaushal*, H Zhang, W Karmaus, TM Everson, CJ Marsit, MR Karagas, S Tsai, H Wen, S Wang, Genome-wide DNA methylation at birth in relation to in utero arsenic exposure and the associated health in later life. Environmental Health. Vol. 16:50. 2017.
  11. A Ziyab, S Ewart, GA Lockett, H Zhang, H Arshad, J Holloway, W Karmaus. Expression of the filaggrin gene in umbilical cord blood predicts eczema risk in infancy: a birth cohort study. Clinical and Experimental Allergy. DOI: 10.1111/cea.12956. 2017.
  12. SH Arshad, W Karmaus, H Zhang, JW Holloway. Multi-generational cohorts in asthma and allergy. Journal Allergy and Clinical Immunology. Vol. 139: 415-421. 2017.
  13. S Ahn, S Kim, H Zhang. Changes in Depressive Symptoms among Older Adults with Multiple Chronic Conditions: Role of Positive and Negative Social Support. International Journal of Environmental Research and Public Health. Vol. 14 (1). 2017.
  14. K Burwell-Naney, SM Wilson, SL Tarver, ER Svendsen, C Jiang, OA Ogunsakin, H Zhang, DA Campbell, H Fraser-Rahim. Baseline Air Quality Assessment of Goods Movement Activities Prior to the Port of Charleston Expansion: A Community-University Collaborative. Environmental Justice. Vol. 10(1): 1-10. doi:10.1089/env.2016.0018. 2017.
  15. S Han*, H Zhang, W Karmaus, G Roberts, H Arshad. Adjusting background noise in cluster analyses of longitudinal data. Computational Statistics and Data Analysis. DOI: 10.1016/j.csda.2016.11.009. 2016.
  16. M Ray*, X Tong*, GA Lockett, H Zhang, W Karmaus. An efficient approach to screening epigenome-wide data. BioMed Research International. Vol. 2016, Article ID 2615348, 16 pages. 2016.
  17. S Han*, H Zhang, R Homayouni, W Karmaus. An efficient Bayesian approach for Gaussian Bayesian network structure learning. Communications in Statistics - Simulation and Computation. 10.1080/03610918.2016.1143103. 2016.
  18. M Ray, J Kang, H Zhang, Identifying Activation Centers with Spatial Cox Point Processes Using FMRI Data, in IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 13, 1130-1141. 2016.

*denotes co-authors are students or post-doctoral fellow under Dr. Zhang's supervision.

Research Funding (active)

  1. Does epigenetic methylation explain the gender-switch in adolescent asthma? (PI). Funding Source: NIAID/NIH (R01).
  2. Effect of Prenatal Compounds on Adult Lung Function via Neonatal DNA (Co-I). PI: Wilfried Karmaus. Funding Source: NHLBI/NIH (R01).
  3. Epigenome-wide association study of childhood asthma (Co-I). PIs: Hasan Arshad, Bjoern Peters, Pandurangan Vijayanand. Funding Source: NIAID/NIH (R01).
  4. Epigenetics of severe asthma (Co-I). PIs: Hasan Arshad, Bjoern Peters, Pandurangan Vijayanand. Funding Source: NHLBI/NIH (R01).
  5. Title: Joint patterns of multi-genetic/epigenetic factors via non-parametric clustering and their association with allergic diseases (Co-). PI: Meredith Ray. Funding Source: NIAID/NIH (R03).

Software Packages

1)  Programs and example data sets for variable selection in semi-parametric models:
a.  Readme file
b.  VarSelection.Linear.standard.R
c.  VarSelection.Linear.MH.R.
d.  VarSelection.Probit.R
e.  Linear. Example3.txt
f.  Probit.Example3.txt
Click here to download the files listed above.

2)  Methods and programs for cell type heterogeneity assessment. Click here to access the website for codes, instructions, and example data sets.