Dr Yalu Wen

M.S., Michigan State University, 2011; Ph.D., Michigan State University, 2012

Senior Lecturer

In: Statistics » Faculty of Science

Biography

Yalu Wen joined the department in 11/2014. She obtained an MSc and PhD from Michigan State University in 2012.

Research | Current

My research interests primarily lie in statistical genetics. Specifically, I am interested in developing and evaluating new statistical genetic risk prediction models for both population-based and family-based studies using high-dimensional data. In parallel with this line of research, I am also interested in the development and application of new statistical methods for association analysis using next generation sequencing data.

Selected publications and creative works (Research Outputs)

Wen, Y., & Lu, Q. (2020). Multikernel linear mixed model with adaptive lasso for complex phenotype prediction. Statistics in medicine, 39 (9), 1311-1327. 10.1002/sim.8477
Li, J., Lu, Q., & Wen, Y. (2020). Multi-kernel linear mixed model with adaptive lasso for prediction analysis on high-dimensional multi-omics data. Bioinformatics, 36 (6), 1785-1797. 10.1093/bioinformatics/btz822
Li, J., Lu, Q., & Wen, Y. (2020). Multi-kernel linear mixed model with adaptive lasso for prediction analysis on high-dimensional multi-omics data. Bioinformatics (Oxford, England), 36 (6), 1785-1794. 10.1093/bioinformatics/btz822
Wang, X., & Wen, Y. (2020). A U-statistics for integrative analysis of multilayer omics data. Bioinformatics, online first10.1093/bioinformatics/btaa004
He, B., Gao, R., Lv, D., Wen, Y., Song, L., Wang, X., ... Wang, Z. (2019). The prognostic landscape of interactive biological processes presents treatment responses in cancer. EBioMedicine, 41, 120-133. 10.1016/j.ebiom.2019.01.064
Wen, Y., & Lu, Q. (2016). A Clustered Multiclass Likelihood-Ratio Ensemble Method for Family-Based Association Analysis Accounting for Phenotypic Heterogeneity. Genetic Epidemiology, 40 (6), 512-519. 10.1002/gepi.21987
URL: http://hdl.handle.net/2292/31153
Wen, Y., He, Z., Li, M., & Lu, Q. (2016). Risk Prediction Modeling of Sequencing Data Using a Forward Random Field Method. Scientific Reports, 6, 1-9. 10.1038/srep21120
URL: http://hdl.handle.net/2292/29564
Alaimo, K., Oleksyk, S. C., Drzal, N. B., Golzynski, D. L., Lucarelli, J. F., Wen, Y., & Velie, E. M. (2013). Effects of changes in lunch-time competitive foods, nutrition practices, and nutrition policies on low-income middle-school children's diets. Childhood Obesity, 9 (6), 509-523. 10.1089/chi.2013.0052