Deep learning tackles single-cell analysis-a survey of deep learning for scRNA-seq analysis.

@article{Flores2021DeepLT,
  title={Deep learning tackles single-cell analysis-a survey of deep learning for scRNA-seq analysis.},
  author={Mario Flores and Zhentao Liu and Ting-He Zhang and Md. Hasib and Yu-Chiao Chiu and Zhenqing Ye and Karla Paniagua and Sumin Jo and Jianqiu Zhang and Shou-Jiang Gao and Yu-Fang Jin and Yidong Chen and Yufei Huang},
  journal={Briefings in bioinformatics},
  year={2021}
}
Since its selection as the method of the year in 2013, single-cell technologies have become mature enough to provide answers to complex research questions. With the growth of single-cell profiling technologies, there has also been a significant increase in data collected from single-cell profilings, resulting in computational challenges to process these massive and complicated datasets. To address these challenges, deep learning (DL) is positioned as a competitive alternative for single-cell… 

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References

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