CI-SpliceAI-Improving machine learning predictions of disease causing splicing variants using curated alternative splice sites.
<h4>Background</h4>It is estimated that up to 50% of all disease causing variants disrupt splicing. Due to its complexity, our ability to predict which variants disrupt splicing is limited, meaning missed diagnoses for patients. The emergence of machine learning for targeted medicine holds great pot...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science (PLoS)
2022-01-01
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| coleção: | PLoS ONE |
| Acesso em linha: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0269159&type=printable |
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