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 国家自然科学基金面上项目：基于单细胞多组学数据的细胞-药物反应预测深度强化学习模型的构建与研究（62372332）
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 国家自然科学基金青年基金项目：面向单细胞多组学数据的癌症基因调控网络预测（62301369）
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）
刘怡（博士生，电子科大）
钱昱罄（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
Machine
Learning Methods in Single-Cell Immune and Drug Response Prediction in
Frontiers of Genetics
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. 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.
3. 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
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
16.
Jing Jiang, Junlin Xu, Yuansheng Liu, Bosheng Song,
Xiulan Guo, Xiangxiang Zeng, Quan Zou*.
Dimensionality reduction and visualization of single-cell RNA-seq data with an
improved deep variational autoencoder. Briefings in Bioinformatics. 2023, 24(3):
bbad152. (codes)
17.
Yushan Qiu, Chang Yan, Pu Zhao, Quan Zou*.
SSNMDI: a novel joint learning model of semi-supervised non-negative matrix
factorization and data imputation for clustering of single-cell RNA-seq data. Briefings in
Bioinformatics. 2023, 24(3): bbad149
18.
Zixuan Wang, Yongqing Zhang, Yun
Yu, Junming Zhang, Yuhang Liu, Quan Zou*. Single-cell ATAC-seq
analysis by Transformer-based cell embedding. International
Journal of Molecular Sciences. 2023, 24(5): 4784
19.
Jiacheng Wang, Yaojia Chen, Quan
Zou*. Inferring gene regulatory network from single-cell transcriptomes
with graph autoencoder model. PLoS Genetics.
2023, 19(9): e1010942 (codes)
20.
Ren Qi, Quan Zou*. Editorial: Machine Learning
Methods in Single-Cell Immune and Drug Response Prediction. Frontiers in
Genetics. 2023, 19: 1233078
21.
Chaorui Yan, Yanxu Zhu, Miao Chen, Kainan Yang, Feifei
Cui*, Quan Zou*, Zilong Zhang*.
Integration tools for scRNA-seq data and spatial
transcriptomics sequencing data. Briefings
in Functional Genomics. Doi: 10.1093/bfgp/elae002
22.
Yushan Qiu, Lingfei Yang, Hao Jiang*, Quan Zou*. scTPC: a novel semi-supervised deep clustering model for scRNA-seq data. Bioinformatics.
2024, 40(5): btae293 (codes)
23.
Yushan Qiu, Dong Guo, Pu Zhao, Quan Zou*. scMNMF: a novel method for
single-cell multi-omics clustering based on matrix factorization. Briefings in Bioinformatics. 2024,
25(3): bbae228. (codes)
24.
Yuncong
Zhang, Yu Yang, Liping Ren, Meixiao Zhan, Taoping Sun*, Quan Zou*, Yang Zhang*. Predicting
intercellular communication based on metabolite-related ligand-receptor
interactions with MRCLinkdb. BMC Biology.
2024, 22: 152 (web site)