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A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations
BACKGROUND: Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed to predict their functional impact. However, the intrinsic...
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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8171027/ https://ncbi.nlm.nih.gov/pubmed/34078253 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-021-03999-8 |
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