研究目标：
对接国家生物医药产业创新发展战略,围绕医学、药物研发和生态学等领域若干核心统计问题创新融合多模态数据,揭示疾病发生发展机制以及药物干预机制,建立最优精准医疗策略:系统研究面向重大疾病及慢病康复监测的基因、影像等新型生物标志物等。
代表性论文：
[1] Shi, Xingjie; Yang, Yi; Ma, Xiaohui; Zhou, Yong; Guo, Zhenxing; Wang, Chaolong; Liu, J. Probabilistic cell/domain-type assignment of spatial transcriptomics data with SpatialAnno. Nucleic Acids Research. 2023, 52(22): e115.
[2] Liu, Wei; Liao, Xu; Luo, Ziye; Yang, Yi; Lau, Mai Chan; Jiao, Yuling; Shi, Xingjie; Zhai, Weiwei; Ji,Hongkai; Yeong, Joe; Liu, Jin. Probabilistic embedding, clustering, and alignment for integrating spatialtranscriptomics data with PRECAST. Nature Communications . 2023, 14 (1): 6585.
[3] Liu, Wei; Liao, Xu; Yang, Yi; Lin, Huazhen; Yeong, Joe; Zhou, Xiang;Shi, Xingjie; Liu, Jin. Jointdimension reduction and clustering analysis of single-cell RNA-seg and spatial transcriptomics data. Nucleic Acids Research. 2022.DOl: 10.1093/nar/gkac219.
[4] Ma, Huijuan; Peng, Limin; Huang, Chiung-Yu; Fu, Haoda. Heterogeneous individual Risk Modelingof Recurrent Events. Biometrika. 2021,108(1):183-198.
[5] Ye, Ting; Yi, Yanyao; Shao, Jun. inference on the average treatment effect under minimization andother covariate-adaptive randomization methods. Biometrika. 2022, 109(1): 33-47.