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SeqEnhDL: sequence-based classification of cell type-specific enhancers using deep learning models
OBJECTIVE: To address the challenge of computational identification of cell type-specific regulatory elements on a genome-wide scale. RESULTS: We propose SeqEnhDL, a deep learning framework for classifying cell type-specific enhancers based on sequence features. DNA sequences of “strong enhancer” ch...
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| Veröffentlicht in: | BMC Res Notes |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
BioMed Central
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7980595/ https://ncbi.nlm.nih.gov/pubmed/33741075 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13104-021-05518-7 |
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