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NCNet: Deep Learning Network Models for Predicting Function of Non-coding DNA
The human genome consists of 98.5% non-coding DNA sequences, and most of them have no known function. However, a majority of disease-associated variants lie in these regions. Therefore, it is critical to predict the function of non-coding DNA. Hence, we propose the NCNet, which integrates deep resid...
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| Publicado no: | Front Genet |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6549219/ https://ncbi.nlm.nih.gov/pubmed/31191597 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2019.00432 |
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