Dr Yalu Wen

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

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Senior Lecturer

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

Identifiers

Contact details

Primary office location

SCIENCE CENTRE 303 - Bldg 303
Level 3, Room 324
38 PRINCES ST
AUCKLAND CENTRAL
AUCKLAND 1010
New Zealand

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