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.
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2017
|
| Subjects: | |
| Online Access: | https://doaj.org/article/967a554eed1a48ca89b012f67075b3c9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|