• 生物统计

• 机器学习与大数据分析

• 多组学数据整合分析

• 人工智能

1.   2025.01-2028.12，全转录组关联分析中跨种族多重遗传效应自适应定位的统计推断方法研究 (82473738)，国家自然科学基金面上项目，主持

2. 2019.01-2021.12, 网络结构驱动的多层面组学生物标记筛选策略与统计方法研究 (81803336)，国家自然科学基金青年基金,主持

3.    2018.03-2020.06, 系统流行病学中多层面组学交互网络回归模型的构建及其统计推断方法研究 (ZR2018BH033),山东省自然科学基金,主持

4.    2020.01-2022.06, 大数据背景下山东省空气质量对居民健康影响的效应评估与疾病经济负担研究 (20DTJJ01), 山东省社会科学规划研究青年项目, 主持

5.    2019.01-2021.12, 高维椭球 Copula 回归模型的变量选择及变点检测问题研究 (11801316)，国家自然科学基金青年基金，参与

6.    2016.01-2019.12, 系统流行病学中网络差异比较的统计分析方法研究 (81573259)，国家自然科学基金面上项目, 参与

部分论文 (* Corresponding author, ^# Co-first author)

Ji J, Hou Z, He Y, Liu L, Xue F, Chen H, Yuan Z. Differential network knockoff filter with application to brain connectivity analysis. Statistics in Medicine. 2024, 43(20):3830-3861.

Liu L, Yan R, Guo P, Ji J, Gong W, Xue F, Yuan Z, Zhou X. Conditional transcriptome-wide association study for fine-mapping candidate causal genes. Nature Genetics. 2024, 56(2):348-356.

Liu X, Yuan J, Zhou H, Wang Y, Tian G, Liu X, Wang X, Tang M, Meng X, Kou C, Yang Q, Li J, Zhang L, Ji J*, Zhang H*. Association between systemic lupus erythematosus and primary hypothyroidism: evidence from complementary genetic methods. Journal of Clinical Endocrinology & Metabolism. 2023, 108(4):941-949.

Liu L, Yang F, Fan Y, Kao C, Wang F, Yu L, He Y, Ji J*, Yu Z*. An Improved Training Algorithm Based on Ensemble Penalized Cox Regression for Predicting Absolute Cancer Risk. China CDC Weekly. 2023, 5(9):206.

Han J, Zhang L, Yan R, Ju T, Jin X, Wang S, Yuan Z, Ji J*. CoNet: Efficient Network Regression for Survival Analysis in Transcriptome-Wide Association Studies—With Applications to Studies of Breast Cancer. Genes. 2023,14(3):586.

Liu L, Zhai W, Wang F, Yu L, Zhou F, Xiang Y, Huang S, Zheng C, Yuan Z, He Y, Yu Z*, Ji J*. Using machine learning to identify gene interaction networks associated with breast cancer. BMC cancer. 2022, 22(1):1070.

Chen H^#, Guo Y, He Y, Ji J^#, Liu L, Shi Y, Wang Y, Yu L, Zhang X. Simultaneous Differential Network Analysis and Classification for Matrix-variate Data with application to Brain Connectivity. Biostatistics. 2022, 23(3)3: 967-989.  R package "SDNCMV".

Ji J, He Y, Xie L, Liu L. Brain Connectivity Alternation Detection via Matrix-variate Differential Network Model. Biometrics. 2021, 77:1409-1421.  R package "MVDN" available at https://github.com/jijiadong/MVDN.

He Y, Chen H, Sun H, Ji J*, Shi Y*, Zhang X, Liu L. High-dimensional Integrative Copula Discriminant Analysis for Multi-omics Data. Statistics in Medicine. 2020, 39(30): 4869-4884.

He Y, Sun H, Ji J*, Zhang X. Robust Feature Screening for Multi-response Trans-elliptical Regression Model with Ultrahigh-dimensional Covariates. Random Matrices: Theory and Applications. 2020, 9(4), 2150001.

He Y, Zhang L, Ji J*, Zhang X. Robust feature screening for elliptical copula regression model. Journal of Multivariate Analysis. 2019, 173: 568-582.

He Y, Ji J*, Xie L, Zhang X, Xue F. A new insight into underlying disease mechanism through semi-parametric latent differential network model. BMC bioinformatics. 2018, 19(17): 493.

Ji J, He D, Feng Y, He Y, Xue F, Xie L. JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data. Bioinformatics. 2017, 33(19):3080-3087.  R code available at https://github.com/jijiadong/JDINAC.

Ji J^#, Yuan Z^#, Zhang X, Xue F. A powerful score-based statistical test for group difference in weighted biological networks. BMC bioinformatics. 2016, 17: 86.

Yuan Z, Ji J, Zhang T, Liu Y, Zhang X, Chen W, Xue F. A novel chi-square statistic for detecting group differences between pathways in systems epidemiology. Statistics in Medicine. 2016, 35(29): 5512-5524.