Adversarial dense graph convolutional networks for single-cell classification.

Journal: Bioinformatics (Oxford, England)
Published Date: Feb 3, 2023

Abstract

MOTIVATION: In single-cell transcriptomics applications, effective identification of cell types in multicellular organisms and in-depth study of the relationships between genes has become one of the main goals of bioinformatics research. However, data heterogeneity and random noise pose significant difficulties for scRNA-seq data analysis.

Authors

  • Kangwei Wang
    School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.
  • Zhengwei Li
    Engineering Research Center of Mine Digitalization of Ministry of Education, China University of Mining and Technology, Xuzhou, China. zwli@cumt.edu.cn.
  • Zhu-Hong You
    Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, 830011, China. zhuhongyou@ms.xjb.ac.cn.
  • Pengyong Han
    Central Lab, Changzhi Medical College, Changzhi 046000, China.
  • Ru Nie
    School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China.

Keywords

External Resources

Popular Topics
Recent Journals