Dr. Mingxuan Cai

Department of Biostatistics

City University of Hong Kong

Assistant Professor

Email: [email protected]

Qualifications

2018 PhD., Statistics, Department of Mathematics, The Hong Kong University of Science and Technology, China

2016 M.Phil, Statistics, Department of Mathematics, Hong Kong Baptist University, China

2012 B.S, Statistics and Operation Research, Department of Mathematics, Hong Kong Baptist University, China

Research Interests

Statistical machine learning

Scalable algorithms

Variable components and mixed-effects models

Publications (Selected）

1. Liu, Y., Zou, W., Li, Y., Wang, J., Cai, M., & Cai, H. (2026+). Cross-modal Denoising and Integration of Spatial Multi-omics Data with CANDIES. Accepted to Advanced Science.
2. Li, Y., Xiao, J., Ming, J., Zeng, Y., & Cai, M. (2025). Funmap: Integrating High-Dimensional Functional Annotations to Improve Fine-Mapping. Bioinformatics, 41(1), btaf017.
3. Yu, X., Hu, X., Wan, X., Zhang, Z., Wan, X., Cai, M., ... & Xiao, J. (2025). A Unified Framework for Cell-Type-Specific eQTL Prioritization by Integrating Bulk and scRNA-seq Data. The American Journal of Human Genetics, 112(2), 332–352.
4. Wang, Z., Zhang, F., Zheng, C., Hu, X., Cai, M., Yang, C. (2024). MFAI: A Scalable Bayesian Matrix Factorization Approach to Leveraging Auxiliary Information. Journal of Computational and Graphical Statistics (online version).
5. Hu, X., Cai, M., Xiao, J., Wan, X., Wang, Z., Zhao, H., & Yang, C. (2024). Benchmarking Mendelian Randomization Methods for Causal Inference Using Genome-Wide Association Study Summary Statistics. The American Journal of Human Genetics, 111(8), 1717–1735.
6. Wan, X., Xiao, J., Tam, S. S. T., Cai, M., Sugimura, R., Wang, Y., ... & Yang, C. (2023). Integrating Spatial and Single-Cell Transcriptomics Data Using Deep Generative Models with SpatialScope. Nature Communications, 14(1), 7848.
7. Yu, X., Xiao, J., Cai, M., Jiao, Y., Wan, X., Liu, J., & Yang, C. (2023). PALM: A Powerful and Adaptive Latent Model for Prioritizing Risk Variants with Functional Annotations. Bioinformatics, 39(2), btad068.
8. Cai, M., Wang, Z., Xiao, J., Hu, X., Chen, G., Yang, C.# (2023). XMAP: Cross-Population Fine-Mapping by Leveraging Genetic Diversity and Accounting for Confounding Bias. Nature Communications, 14, 6870.
9. Xiao, J., Cai, M., Yu, X., Hu, X., Chen, G., Wan, X., Yang, C. (2022). Leveraging the Local Genetic Structure for Trans-Ancestry Association Mapping. The American Journal of Human Genetics, 109(7), 1317–1337.
10. Xiao, J., Cai, M., Hu, X., Wan, X., Chen, G., Yang, C. (2022). XPXP: Improving Polygenic Prediction by Cross-Population and Cross-Phenotype Analysis. Bioinformatics, 38(7), 1947–1955.
11. Cai, M., Xiao, J., Zhang, S., Wan, X., Zhao, H., Chen, G., Yang, C. (2021). A Unified Framework for Cross-Population Trait Prediction by Leveraging the Genetic Correlation of Polygenic Traits. The American Journal of Human Genetics, 108(4), 632–655.
12. Cai, M., Chen, L., Liu, J., Yang, C. (2020). IGREX for Quantifying the Impact of Genetically Regulated Expression on Phenotypes. NAR Genomics and Bioinformatics, 2(1), lqaa010.
13. Cai, M., Dai, M., Ming, J., Peng, H., Liu, J., Yang, C. (2019). BIVAS: A Scalable Bayesian Method for Bi-Level Variable Selection. Journal of Computational and Graphical Statistics, 29(1), 40–52.

Profile Details

https://scholar.google.com/citations?hl=zh-CN&user=bK5JkV4AAAAJ

https://www.researchgate.net/profile/Mingxuan-Cai