Predicting the impact of sequence motifs on gene regulation using single-cell data
Abstract The binding of transcription factors at proximal promoters and distal enhancers is central to gene regulation. Identifying regulatory motifs and quantifying their impact on expression remains challenging. Using a convolutional neural network trained on single-cell data, we infer putative re...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-08-01
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| Series: | Genome Biology |
| Online Access: | https://doi.org/10.1186/s13059-023-03021-9 |