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Predicting the impact of sequence motifs on gene regulation using single-cell data
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 regulatory...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10426127/ https://www.ncbi.nlm.nih.gov/pubmed/37582793 http://dx.doi.org/10.1186/s13059-023-03021-9 |