Reconstructing cell cycle and disease progression using deep learning
The interpretation of information-rich, high-throughput single-cell data is a challenge requiring sophisticated computational tools. Here the authors demonstrate a deep convolutional neural network that can classify cell cycle status on-the-fly.
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| Auteurs principaux: | , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2017
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/967a554eed1a48ca89b012f67075b3c9 |
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