首页> 中文期刊> 《定量生物学:英文版》 >Emerging deep learning methods for single-cell RNA-seq data analysis

Emerging deep learning methods for single-cell RNA-seq data analysis

         

摘要

Deep learning is making major breakthrough in several areas of bioinformatics.Anticipating that this will occur soon for the single-cell RNA-seq data analysis,we review newly published deep learning methods that help tackle computational challenges.Autoencoders are found to be the dominant approach.However,methods based on deep generative models such as generative adversarial networks (GANs) are also emerging in this area.

著录项

  • 来源
    《定量生物学:英文版》 |2019年第4期|247-254|共8页
  • 作者

    Jie Zheng; Ke Wang;

  • 作者单位

    上海理工大学;

    上海理工大学;

  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    机译:单细胞;RNA-SEQ;深度学习;自动化器;
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