Yuqing Zhang

Yuqing ZhangPh.D. Candidate, Bioinformatics, BUSM
Johnson Lab

Education

B.S. Applied Mathematics, Peking University, Beijing, China, 2015
M.S. Bioinformatics, Boston University, Boston MA, 2017

Contact Information

Email: yuqingz@bu.edu

Research Interests

Statistical models for batch effect diagnosis and adjustment. I develop methods to detect batch effect in genomic data, and design novel algorithms to address batch effect for various data types and situations.

Data heterogeneity in statistical learning with genomic data. Heterogeneity in genomic data is caused by complicated biological and technical factors. I generate realistic simulations in attempt to understand how these factors affect the validation of prediction models, and how to reduce the impact of heterogeneity on prediction.

Publications

Zhang, Y., Bernau, C., Parmigiani, G., & Waldron, L. (2018). The impact of different sources of heterogeneity on loss of accuracy from genomic prediction models. Biostatistics (Oxford, England).

Zhang, Y., Jenkins, D. F., Manimaran, S., & Johnson, W. E. (2018). Alternative empirical Bayes models for adjusting for batch effects in genomic studies. BMC bioinformatics19(1), 262.

Griffin, P. J., Zhang, Y., Johnson, W. E., & Kolaczyk, E. D. (2018). Detection of multiple perturbations in multi‐omics biological networks. Biometrics74(4), 1351-1361.