中级

李冠巡

个人信息简介

姓名:李冠巡 学历:博士 职称:讲师 电子邮箱:guanxun@bnu.edu.cn

理学博士,现任北京师范大学文理学院统计系教师。


教育背景

2013.09-2017.06 北京航空航天大学,数学专业,理学学士

2017.09-2018.06   德州农工大学,数学专业,理学硕士

2018.09-2022.08   德州农工大学,数学专业,理学博士


工作经历

2022.09-2024.08 德州农工大学,博士后


研究方向

大规模统计假设检验;马尔可夫链蒙特卡洛采样;贝叶斯变量选择;大语言模型;单细胞RNA序列数据分析;微生物组数据分析。


发表论文

1. Li, G., Lu, Y., Chen, J. and Zhang, X., 2023. Robust Differential Abundance Analysis of Microbiome Sequencing Data . Genes, 14(11), p.2000.

2. Li, G. and Zhou, Q., 2024. Bayesian Multi-Task Variable Selection with an Application to Differential DAG Analysis. Journal of Computational and Graphical Statistics, 33(1), pp.35-46.

3. Yang, Y., Lin, Y.T., Li, G., Zhong, Y., Xu, Q. and Cai, J.J., 2023. Interpretable modeling of time-resolved single-cell gene–protein expression with CrossmodalNet. Briefings in Bioinformatics, 24(6), p.bbad342.

4. Yang, Y., Li, G., Zhong, Y., Xu, Q., Chen, B.J., Lin, Y.T., Chapkin, R.S. and Cai, J.J., 2023. Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks. Nucleic Acids Research, p.gkad450.

5. Yang, Y., Li, G., Zhong, Y., Xu, Q., Lin, Y.T., Roman-Vicharra, C., Chapkin, R.S. and Cai, J.J., 2023. scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs. Cell Systems, 14(4), pp.302-311.

6. Osorio, D., Zhong, Y., Li, G., Xu, Q., Yang, Y., Tian, Y., Chapkin, R.S., Huang, J.Z. and Cai, J.J., 2022. scTenifoldKnk: An efficient virtual knockout tool for gene function predictions via single-cell gene regulatory network perturbation. Patterns, 3(3), p.100434.

7. Xu, Q., Li, G., Osorio, D., Zhong, Y., Yang, Y., Lin, Y.T., Zhang, X. and Cai, J.J., 2022. scInTime: A Computational Method Leveraging Single-Cell Trajectory and Gene Regulatory Networks to Identify Master Regulators of Cellular Differentiation. Genes, 13(2), p.371.

8. Osorio, D., Zhong, Y., Li, G., Huang, J.Z. and Cai, J.J., 2020. scTenifoldNet: a machine learning workflow for constructing and comparing transcriptome-wide gene regulatory networks from single-cell data. Patterns, 1(9), p.100139.

9. Osorio, D., Yu, X., Zhong, Y., Li, G., Serpedin, E., Huang, J.Z. and Cai, J.J., 2019. Single-cell expression variability implies cell function. Cells, 9(1), p.14.


教学工作

本科生: 统计学导论(上机)