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    季加东

    • 副研究员 硕士生导师
    • 性别:男
    • 所在单位:金融研究院
    • 办公地点:知新楼B1221
    • 联系方式:Tel:0531-88364298 Email:jiadongATsduDOTeduDOTcn

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    (* 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.


    Zhang L, Ju T, Jin X, Ji J, Han J, Zhou X, Yuan Z. Network regression analysis for binary and ordinal categorical phenotypes in transcriptome-wide association studies. Genetics. 2022, 222(4):iyac153.


    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.


    Fan Y, Kao C, Yang F, Wang F, Yin G, Wang Y, He Y, Ji J*, Liu L*. Integrated Multi-Omics Analysis Model to Identify Biomarkers Associated With Prognosis of Breast Cancer. Frontiers in oncology. 2022, 12.

    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. Biostatistics2022, 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.

    Lin W#Ji J#, Zhu Y, Li M, Zhao J, Xue F, Yuan Z. PMINR: pointwise mutual information-based network regression – with application to studies of lung cancer and Alzheimer’s disease. Frontiers in genetics. 2020, 11:556259.

    Zhu Y#Ji J#, Lin W, Li M, Liu L, Zhu H, Xue F, Li X, Zhou X, Yuan Z. MCC-SP: a powerful integration method for identification of causal pathways from genetic variants to complex disease. BMC Genetics. 2020, 21:90.

    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 Applications2020, 9(4), 2150001.

    Chen H, He Y, Ji J, Shi Y. The sparse group lasso for high-dimensional integrative linear discriminant analysis with application to alzheimer’s disease prediction. Journal of statistical computation and simulation. 2020. 90(17): 3218-3231.

    Gao N, Xu W, Ji J, Yang Y, Meng S, Tian X, Xu K. Lung function and systemic inflammation associated with short-term air pollution exposure among COPD patients in Beijing, China. Environmental Health. 2020,19:12.

    Liu Y, Du Z, Ji J, Li J, Bi D, Tang F. Bidirectional association between serum carcinoembryonic antigen and metabolic syndrome among the Chinese male population: two cohort studies. Lipids in Health and Disease. 2020,19(1):233.

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

    Chen H, He Y, Ji J*, Shi Y*. A Machine Learning Method for Identifying Critical Interactions Between Gene Pairs in Alzheimer's Disease Prediction. Frontiers in Neurology. 2019, 10:1162.

    Zhang X, Tang F, Ji J, Han W, Lu P. Risk Prediction of Dyslipidemia for Chinese Han Adults Using Random Forest Survival Model. Clinical Epidemiology. 2019, 14: 1047–1055.

    Gao N, Li C, Ji J, Yang Y, Wang S, Tian X, Xu KF. Short-term effects of ambient air pollution on chronic obstructive pulmonary disease admissions in Beijing, China (2013-2017). International Journal of Chronic Obstructive. 2019; 14: 297–309.

    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.

    Gao N, Zhang T, Ji J, Xu K, Tian X. The efficacy and adverse events of mTOR inhibitors in lymphangioleiomyomatosis: systematic review and meta-analysis. Orphanet Journal of Rare Diseases. 2018, 13:134.

    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.

    He Y, Zhang X, Ji J, Liu B. Joint Estimation of Multiple High Dimensional Gaussian Copula Graphical Models. Australian & New Zealand Journal of Statistics. 2017, 59(3):289-310.

    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 X, Xu J, Ma D, Xue F. A powerful weighted statistic for detecting group differences of directed biological networks. Scientific Reports. 2016, 6: 34159.

    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.

    Dider S, Ji J, Zhao Z, Xie L. Molecular Mechanisms Involved in the Side Effects of Fatty Acid Amide Hydrolase Inhibitors: A Structural Phenomics Approach to Proteome-wide Cellular Off-target Deconvolution and Disease Association. npj Systems Biology and Applications. 2016, 2:16023.

    Xu J, Yuan Z, Ji J, Zhang X, Li H, Wu X, Xue F, Liu Y. A powerful score-based test statistic for detecting gene-gene co-association. BMC genetics. 2016, 17: 31.

    Zhang X, Yuan Z, Ji J, Li H, Xue F. Network or regression-based methods for disease discrimination: a comparison study. BMC Medical Research Methodology. 2016, 16(1): 100.

    Li H, Yuan Z, Ji J, Xu J, Zhang T, Zhang X, Xue F. A novel Markov Blanket-based repeated-fishing strategy for capturing phenotype-related biomarkers in big omics data. BMC genetics. 2016, 17: 51.

    Gao N, Yuan Z, Tang X, Zhou X, Zhao M, Liu L, Ji J, Xue F, Ning G, Zhao J, Zhang H, Gao L. Prevalence of CHD-related metabolic comorbidity of diabetes mellitus in Northern Chinese adults: the REACTION study. J Diabetes Complications. 2016. 30(2): 199-205.

    Gao N, Yu Y, Zhang B, Yuan Z, Zhang H, Song Y, Zhao M, Ji J, Liu L, Xu C, Zhao J. Dyslipidemia in rural areas of North China: prevalence, characteristics, and predictive value. Lipids in Health and Disease. 2016, 15:154.

    Ji J, Yuan Z, Zhang X, Li F, Xu J, Liu Y, Li H, Wang J, Xue F. Detection for pathway effect contributing to disease in systems epidemiology with a case–control design. BMJ Open. 2015, 5(1): e006721.

    Li F, Zhao J, Yuan Z, Zhang X, Ji J, Xue F. A powerful latent variable method for detecting and characterizing gene-based gene-gene interaction on multiple quantitative traits. BMC genetics. 2013, 14(1): 89.