期刊
QUANTITATIVE BIOLOGY
卷 7, 期 4, 页码 247-254出版社
HIGHER EDUCATION PRESS
DOI: 10.1007/s40484-019-0189-2
关键词
single-cell; RNA-seq; deep learning; autoencoder
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.
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