Detection of DNA base modifications by deep recurrent neural network on Oxford Nanopore sequencing data
DNA modification generates unique electric signals in Oxford Nanopore sequencing data but the signals can be complicated to decipher. Here, the authors develop a deep learning framework, DeepMod, to detect DNA base modifications including 5mC and 6mA using Nanopore sequencing data
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/2a64c8015b9e434c94ff1733e2720d34 |
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| Sumario: | DNA modification generates unique electric signals in Oxford Nanopore sequencing data but the signals can be complicated to decipher. Here, the authors develop a deep learning framework, DeepMod, to detect DNA base modifications including 5mC and 6mA using Nanopore sequencing data |
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