胡耀华 - 软件

Matlab

• LpRGNI (Lp Regularization for Gene Network Inference)
  - LpRGNI是运用Lasso类方法(包括L0, L1和L(1/2)正则化方法), 结合高通量基因表达数据和转录因组学数据来预测基因调控网络的Matlab工具包.
  - 参考文献:
  

  • J. Qin, Y. Hu, F. Xu, H. K. Yalamanchili and J. Wang, Inferring gene regulatory networks by integrating ChIP-seq/chip and transcriptome data via LASSO-type regularization methods, Methods, 67: 294-303, 2014. [link]

• GSO (Group Sprase Optimization for Cell Fate Conversion Prediction)
  - GSO是运用L(2,0)组稀疏优化方法, 结合体量或者单细胞组学数据来预测主导细胞命运转换过程的关键转录因子的的Matlab工具包. [GitHub]
  - 参考文献:
  

  • J. Qin*, Y. Hu, J.-C. Yao, R. W. T. Leung, Y. Zhou, Y. Qin and J. Wang, Cell fate conversion prediction by group sparse optimization method utilizing single-cell and bulk OMICs data, accepted in Briefings in Bioinformatics, 2021. [link]

R

• GSparO (Group Sparse Optimization)
  - GSparO是运用proximal gradient algorithm求解组稀疏优化的L(p,q)正则化模型的R工具包.
  - 参考文献:
  

  • Y. Hu, C. Li, K. Meng, J. Qin and X. Yang, Group sparse optimization via L(p,q) regularization, Journal of Machine Learning Research, 18(30): 1-52, 2017. [link]

• GSO (Group Sprase Optimization for Cell Fate Conversion Prediction)
  - GSO是运用L(2,0)组稀疏优化方法, 结合体量或者单细胞组学数据来预测主导细胞命运转换过程的关键转录因子的的R工具包. [GitHub]
  - 参考文献:
  

  • J. Qin*, Y. Hu, J.-C. Yao, R. W. T. Leung, Y. Zhou, Y. Qin and J. Wang, Cell fate conversion prediction by group sparse optimization method utilizing single-cell and bulk OMICs data, accepted in Briefings in Bioinformatics, 2021. [link]

Webserver

• CrusTF (Crustacean Transcription Factors)
  - CrusTF是研究甲壳类动物进化和功能的转录因子的网络服务器.
  - 参考文献:
  

  • J. Qin, Y. Hu, K. Ma, X. Jiang, C. Ho, L. Tsang, L. Yi and K. Chu, CrusTF: A comprehensive resource for evolutionary and functional studies of crustacean transcription factors, BMC Genomics, 18(1): 908, 2017. [link]

• CORN (Condition Orientated Regulatory Networks)
  - CORN是条件特异(小分子/药物治疗和基因敲除)的基因转录调控子网络文库，配有信息展示与在线匹配工具.
  - 参考文献:
  

  • R. W. T. Leung#, X. Jiang#, X. Zong#, Y. Zhang, X. Hu, Y. Hu* and J. Qin*, CORN - Condition Orientated Regulatory Networks: bridging conditions to gene networks, Briefings in Bioinformatics, 23(6): bbac402, 2022. [link]