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Predicting Pathogenicity of Missense Variants with Weakly Supervised Regression
Quickly growing genetic variation data of unknown clinical significance demand computational methods that can reliably predict clinical phenotypes and deeply unravel molecular mechanisms. On the platform enabled by CAGI (Critical Assessment of Genome Interpretation), we develop a novel “weakly super...
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| Publicado no: | Hum Mutat |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6744350/ https://ncbi.nlm.nih.gov/pubmed/31144781 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/humu.23826 |
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