Courses Taught
- MATH 644: Statistics Engnrs&Scientists
- MATH 734: Statistical Computing
- MATH 734/834: Statistical Computing
- MATH 736/836: Advanced Statistical Modeling
- MATH 741/841: Survival Analysis
- MATH 796/896: Spc Top/Statistical Computing
- MATH 796/997: Topics
- MATH 834: Statistical Computing
- MATH 835: Statistical Mthds for Research
- MATH 836: Advanced Statistical Modeling
- MATH 946: Adv Theory of Statistics II
Selected Publications
Adediran, E., Lowell, K., Kastrisios, C., Rice, G., & Zhang, Q. (2024). Exploring Ancillary Parameters for Quantifying Interpolation Uncertainty in Digital Bathymetric Models. Marine Geodesy, 47(4), 289-323. doi:10.1080/01490419.2024.2338730
Zhang, Q., Yang, Z., & Yang, J. (2024). Dissecting the colocalized GWAS and eQTLs with mediation analysis for high-dimensional exposures and confounders.. Biometrics, 80(2). doi:10.1093/biomtc/ujae050
Zhang, Q., Coury, R., & Tang, W. (2024). Prediction of conversion from mild cognitive impairment to Alzheimer's disease and simultaneous feature selection and grouping using Medicaid claim data.. Alzheimers Res Ther, 16(1), 54. doi:10.1186/s13195-024-01421-y
Veasna, K., Feng, Z., Zhang, Q., & Knezevic, M. (2023). Machine learning-based multi-objective optimization for efficient identification of crystal plasticity model parameters. Computer Methods in Applied Mechanics and Engineering, 403, 115740. doi:10.1016/j.cma.2022.115740
Yang, Z., Xu, G., Zhang, Q., Obata, T., & Yang, J. (2022). Genome-wide mediation analysis: an empirical study to connect phenotype with genotype via intermediate transcriptomic data in maize. GENETICS, 221(2). doi:10.1093/genetics/iyac057
Zhang, Y., Schmidt, J. W., Arthur, T. M., Wheeler, T. L., Zhang, Q., & Wang, B. (2022). A Farm-to-Fork Quantitative Microbial Exposure Assessment of beta-Lactam-Resistant Escherichia coli among US Beef Consumers. MICROORGANISMS, 10(3). doi:10.3390/microorganisms10030661
Papale, L. A., Madrid, A., Zhang, Q., Chen, K., Sak, L., Keles, S., & Alisch, R. S. (2022). Gene by environment interaction mouse model reveals a functional role for 5-hydroxymethylcytosine in neurodevelopmental disorders. GENOME RESEARCH, 32(2), 266-279. doi:10.1101/gr.276137.121
ENCODE Project Consortium., Moore, J. E., Purcaro, M. J., Pratt, H. E., Epstein, C. B., Shoresh, N., . . . Weng, Z. (2020). Expanded encyclopaedias of DNA elements in the human and mouse genomes.. Nature, 583(7818), 699-710. doi:10.1038/s41586-020-2493-4
ENCODE Project Consortium., Snyder, M. P., Gingeras, T. R., Moore, J. E., Weng, Z., Gerstein, M. B., . . . Myers, R. M. (2020). Perspectives on ENCODE.. Nature, 583(7818), 693-698. doi:10.1038/s41586-020-2449-8
Li, J., Lai, Y., Zhang, C., & Zhang, Q. (2020). TGCnA: temporal gene coexpression network analysis using a low-rank plus sparse framework.. J Appl Stat, 47(6), 1064-1083. doi:10.1080/02664763.2019.1667311
