Ø 国家自然科学基金重点项目：面向单细胞RNA测序数据的深度迁移模型与细胞通信网络研究（62131004）
Ø 国家自然科学基金面上项目：基于植物单细胞转录组和多组学数据分析及基因调控网络构建方法的研究（62272321）
Ø 国家自然科学基金青年基金项目：大型单细胞转录组数据降维与可视化（62102064）
Ø 国家自然科学基金青年基金项目：基于单细胞测序数据的药物反应预测研究（62201129）
Ø 国家自然科学基金地区基金项目：单细胞转录组与空间转录组数据整合方法研究（62261018）
邹权 （教授，电子科大）
魏乐义（教授，山东大学）
张子龙
（副教授，海南大学）
张永清
（副教授，成都信息工程大学）
齐忍（博士后，电子科大）
王嘉程（博士生，电子科大）
焦仕虎（科研助理，电子科大）
webSCST: an interactive web application for
single-cell RNA-seq data and spatial transcriptome data integration
scIMC:
a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods
1.
Ziwei Wang, Hui Ding, Quan Zou*.
Identifying Cell Types to Interpret scRNA-seq Data:
How, Why, and More Possibilities. Briefings in Functional Genomics. 2020, 19(4):286-291
2.
Ziwei Wang, Chi-chang Chang*, Quan Zou*. COVID-19 Related Research by Data Mining in Single Cell
Transcriptome Profiles. Journal of
Electronic Science and Technology. 2021, 19(1):1-5
3.
Ren Qi,
Anjun Ma, Qin Ma*, Quan Zou*.
Clustering and Classification Methods for Single-cell RNA-sequencing Data. Briefings in Bioinformatics. 2020,
21(4): 1196-1208.
4.
Ren Qi, Jin
Wu, Fei Guo, Lei Xu*, Quan Zou*. A
Spectral Clustering with Self-weighted Multiple Kernel Learning Method for
single-cell RNA-seq Data. Briefings in Bioinformatics. 2021, 22(4): bbaa216. (Codes)
5.
Zilong Zhang, Feifei
Cui, Chunyu Wang, Lingling Zhao*, Quan
Zou*. Goals and Approaches for Each Processing Step for Single-Cell RNA
Sequencing Data. Briefings in
Bioinformatics. 2021, 22(4): bbaa314. (codes)
6.
Zilong Zhang, Feifei
Cui, Chen Lin, Lingling Zhao, Chunyu Wang*, Quan Zou*. Critical
downstream analysis steps for single-cell RNA sequencing data. Briefings in Bioinformatics. 2021,22(5):bbab105. (codes)
7.
Zilong Zhang, Feifei
Cui, Murong Zhou, Song Wu*, Quan Zou*, Bo
Gao*. Single-cell RNA sequencing analysis identifies key genes in brain
metastasis from lung adenocarcinoma.
Current gene therapy. 2021, 21(4): 338-348
8.
Zilong Zhang, Feifei
Cui, Chen Cao, Qingsuo Wang*, Quan Zou*.
Single-cell RNA analysis reveals the potential risk of organ-specific cell
types vulnerable to SARS-CoV-2 infections. Computers in Biology and Medicine.
2022, 140: 105092
9.
Jiacheng Wang, Quan Zou*,
Chen Lin*. A comparison of deep learning-based pre-processing and clustering
approaches for single-cell RNA sequencing data. Briefings in Bioinformatics. 2022, 23(1):
bbab345
10. Ziwei Wang, Ying Zhang, Qun Li, Quan Zou*, Qing Liu*. A road map for
happiness: The psychological factors related cell types in various parts of
human body from single cell RNA-seq data analysis. Computers
in Biology and Medicine. 2022, 143:105286
11. Mengyuan Zhao, Wenying He, Jijun
Tang*, Quan Zou*, Fei Guo*. A hybrid deep learning framework for gene
regulatory network inference from single-cell transcriptomic data. Briefings
in Bioinformatics. 2022, 23(2): bbab568
12. Zilong Zhang, Feifei Cui,
Wei Su, Lijun Dou, Anqi Xu, Chen Cao, Quan Zou*.
webSCST: an interactive web application for
single-cell RNA-sequencing data and spatial transcriptomic data integration. Bioinformatics.
2022, 38(13):3488-3489. (web server)
13. Chichi Dai, Yi Jiang, Chenglin
Yin, Ran Su, Xiangxiang
Zeng, Quan Zou, Kenta Nakai*, Leyi Wei*. scIMC:
a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods. Nucleic Acids
Research. 2022, 50(9):4877-4899. (web server)
14. Yongqing Zhang, Maocheng Wang,
Zixuan Wang, Yuhang Liu, Shuwen
Xiong, Quan Zou*. MetaSEM: Gene regulatory
network inference from single-cell RNA data by Meta-learning. International
Journal of Molecular Sciences. 2023, 24: 2595