Mingxuan CAI

Department of Biostatistics, City University of Hong Kong

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Email: mingxcaiATcityu.edu.hk

Address: YEUNG-G5752, City University of Hong Kong

I am an Assistant Professor at the Department of Biostatistics, City University of Hong Kong. I obtained my PhD degree from The Hong Kong University of Science and Technology supervised by Prof. Can Yang. My broad area of interest lies in statistical machine learning and data science with applications in genetics and genomics data. I have been working on scalable statistical methods for high dimensional regression problems, integrative analysis of multi-omics data, and cross-population genetics for association mapping and polygenic risk prediction.

My GitHub page

My GooGle Scholar citation

selected publications

  1. Bioinformatics
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    Funmap: integrating high-dimensional functional annotations to improve fine-mapping
    Yuekai Li, Jiashun Xiao, Jingsi Ming, Yicheng Zeng, and Mingxuan Cai
    Bioinformatics, 2025
  2. JCGS
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    MFAI: A scalable Bayesian matrix factorization approach to leveraging auxiliary information
    Zhiwei Wang, Fa Zhang, Cong Zheng, Xianghong Hu, Mingxuan Cai, and Can Yang
    Journal of Computational and Graphical Statistics, 2024
  3. Nat Commun
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    XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias
    Mingxuan Cai, Zhiwei Wang, Jiashun Xiao, Xianghong Hu, Gang Chen, and Can Yang
    Nature Communications, 2023
  4. AJHG
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    Leveraging the local genetic structure for trans-ancestry association mapping
    Jiashun Xiao, Mingxuan Cai, Xinyi Yu, Xianghong Hu, Xiang Wan, Gang Chen, and Can Yang
    The American Journal of Human Genetics, 2022
  5. Bioinformatics
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    XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis
    Jiashun Xiao, Mingxuan Cai, Xianghong Hu, Xiang Wan, Gang Chen, and Can Yang
    Bioinformatics, Jan 2022
  6. AJHG
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    A unified framework for cross-population trait prediction by leveraging the genetic correlation of polygenic traits
    Mingxuan Cai, Jiashun Xiao, Shunkang Zhang, Xiang Wan, Hongyu Zhao, Gang Chen, and Can Yang
    The American Journal of Human Genetics, Jan 2021
  7. NARGAB
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    IGREX for quantifying the impact of genetically regulated expression on phenotypes
    Mingxuan Cai, Lin S Chen, Jin Liu, and Can Yang
    NAR genomics and bioinformatics, Jan 2020
  8. JCGS
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    BIVAS: a scalable Bayesian method for bi-level variable selection with applications
    Mingxuan Cai, Mingwei Dai, Jingsi Ming, Heng Peng, Jin Liu, and Can Yang
    Journal of Computational and Graphical Statistics, Jan 2020