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An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data
BACKGROUND: The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed to predict human essential genes from population ge...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10506225/ https://www.ncbi.nlm.nih.gov/pubmed/37723435 http://dx.doi.org/10.1186/s12859-023-05481-z |