团队愿景 (Vision)

本研究组利用深度学习与人工智能算法结合单细胞等测序技术数据，致力于对细胞的数字化建模和分析，揭示细胞的功能复杂性与异常机制。研究重点是从单个细胞中提取多组学多模态生物信息，构建细胞的计算模型。研究内容包括：细胞类型的鉴定和分类、基因调控网络的建模和分析、细胞发育和分化的机制研究、生物进化和适应的机制研究、复杂疾病（癌症）的机制研究等。

团队组成 (Members)

PI：陈向 博士
研究生：21 级余俊楠，22 级马永康，23 级刘小宇，23 级杨子涵
本科生：21 级聂艺洋（保研河海大学），21 级曾家伟（考研湖南科技大学），21 级曾嘉诚（考研湖南科技大学）
欢迎 👏 未来的你加入本研究组！如果有意，请发送邮件到 chenxofhit[at]gmail[dot]com 介绍自己的基本情况、优势以及对未来工作的展望。

团队新闻 (News)（时间正序）

1，热烈祝贺本组的科研论文被CCF B类国际会议IEEE BIBM 2023 接收！报道：https://chenxofhit.xyz/posts/scgcnclustering/
2，热烈祝贺本组本科生曾家伟毕业设计“基于 Transformer 模型的细胞类型注释方法研究”获湖南科技大学优秀本科生毕业设计二等奖！
3，热烈祝贺本组的科研论文被CCF B类国际会议IEEE BIBM 2024 接收！报道：https://chenxofhit.xyz/posts/stgclf/
4，主持横向项目“农村产权交易中心平台建设”作为校企合作典型被湘潭市政府网站报道：https://www.xiangtan.gov.cn/109/171/174/content_1343296.html

团队制度 (Rules)

学生义务

1，不养懒人，以产出为导向，研一学生每月至少提交一次代码到仓库；研二研三学生每月至少提交两次代码到仓库。
2，回复消息、展开工作需及时响应、知行合一。
3，遵守学校学院基本的考勤出勤制度。

导师义务

1，定期参与学生研究工作的讨论(硕士学生每两周至少讨论一次，交流时间在 45min；本科学生每月至少讨论一次，交流时间在 30min)。
2，发放补贴，补贴跟产出挂钩。日常划水或者不深度参与团队项目，导师没有义务给予补贴。

团队成果

Conferences-会议论文（时间倒序）

  • [C] Xiang Chen, Junnan Yu, and Min Li. stGCLF: a versatile deep graph contrastive learning framework for spatial transcriptomics analysis. In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal, 2024 pp. 497-502.doi: 10.1109/BIBM62325.2024.10822862. (CCF B 类国际会议)
  • [C] Xiang Chen, Junnan Yu, Li Peng, and Min Li. A deep graph convolution network with attention for clustering scRNA-seq data. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Istanbul, Turkiye, 2023 pp. 320-323. doi: 10.1109/BIBM58861.2023.10385323. (CCF B 类国际会议) Cite
  • [C] Shuai Zhang, Xiang Chen, Li Peng. scIAMC:Single-Cell Imputation via adaptive matrix completion. IEEE EdgeCom 2023.
  • [C] Tao Huang, Xiang Chen, Li Peng. ESR：Optimizing Gene Feature Selection for scRNA-seq data. IEEE CSCloud 2023.
  • [C] Xiang Chen, Fang-Xiang Wu, Jin Chen, and Min Li. DoRC: Discovery of rare cells from ultra-large scRNA-seq data. In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), San Diego, CA, USA, 2019, pp. 111-116, doi: 10.1109/BIBM47256.2019.8983250. (CCF B 类国际会议)
  • [C] Xiang Chen, Wei Bu, Xiangqian Wu, et al. “A novel method for automatic hard exudates detection in color retinal images[C]”//Machine Learning and Cybernetics (ICMLC), 2012 International Conference on. IEEE, 2012, 3:1175-1181. (EI)

Journals-期刊论文（时间倒序）

  • [J] Li Peng , Yuan Tu , Li Huang , Yang Li , Xiangzheng Fu , and Xiang Chen. DAESTB: Inferring associations of small molecule-miRNA via a scalable tree boosting model based on deep autoencoder.Briefings in Bioinformatics. 2022. (SCI IF=11, JCR 1 区) Cite
  • [J] Li Peng, Cheng Yang , Li Huang , Xiang Chen, Xiangzheng Fu and Wei Liu. RNMFLP:Predicting circRNA-disease associations based on robust non-negative matrix factorization and label propagation. Briefings in Bioinformatics. 2022. (CA, SCI IF=11, JCR 1 区) Cite
  • [J]Xiang Chen, Min Li, Ruiqing Zheng, Siyu Zhao, Fang-Xiang Wu, Yaohang Li, and Jianxin Wang. A novel method of gene regulatory network structure inference from gene knock-out expression data. Tsinghua Science and Technology 24, no. 4 (2019): 446-455. (SCI IF=2.3, JCR 2 区 )
  • [J] Xiang Chen, Min Li, Ruiqing Zheng, Fang-Xiang Wu, and Jianxin Wang. D3GRN: a data driven dynamic network construction method to infer gene regulatory networks. BMC genomics 20, no. 13 (2019): 1-8. (SCI IF=3.5, JCR 1 区)
  • [J] Ruiqing Zheng, Min Li, Xiang Chen, Fang-Xiang Wu, Yi Pan, and Jianxin Wang. BiXGBoost: a scalable, flexible boosting-based method for reconstructing gene regulatory networks. Bioinformatics 35, no. 11 (2019): 1893-1900. (SCI IF=5.6, JCR 1 区)
  • [J] Ruiqing Zheng, Min Li, Xiang Chen, Siyu Zhao, Fang-Xiang Wu, Yi Pan, Jianxin Wang. An ensemble method to reconstruct gene regulatory networks based on multivariate adaptive regression splines. IEEE/ACM Transactions on Computational Biology and Bioinformatics. doi: 10.1109/TCBB.2019.2900614. (SCI IF=0.9, JCR 1 区)
  • [J] Ruiqing Zheng, Zhenlan Liang, Xiang Chen, Yu Tian, Min Li. An Adaptive Sparse Subspace Clustering for Cell Type Identification. Frontiers in Genetics. doi: 10.3389/fgene.2020.00407.(SCI IF=3.2, JCR 1 区)
  • [J] Hui Jiang, Mengyun Yang, Xiang Chen, Min Li, Yaohang Li, and Jianxin Wang. miRTMC: A miRNA Target Prediction Method Based on Matrix Completion Algorithm[J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS.2020, DOI:10.1109/JBHI.2020.2987034. (SCI IF=5.1, JCR 1 区)
  • [J] Min Li, Jianxin Wang, Xiang Chen, et al. “A local average connectivity-based method for identifying essential proteins from the network level[J]”. Computational biology and chemistry, 2011, 35(3): 143-150. (SCI)
  • [J] Wei Bu, Xiangqian Wu, Xiang Chen, et al. “Hierarchical Detection of Hard Exudates in Color Retinal Images[J]”. JSW, 2013, 8(11): 2723-2732. (EI)

最后更新：2025-1-15