Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Más filtros

Bases de datos
Tipo del documento
Intervalo de año de publicación
1.
Exp Mol Med ; 55(8): 1734-1742, 2023 08.
Artículo en Inglés | MEDLINE | ID: mdl-37524869

RESUMEN

The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing depth remains a daunting challenge despite numerous attempts to address this problem. In this study, we constructed a substantially extended set of actual positive variants originating from a wide range of tumor purities and sequencing depths, as well as actual negative variants derived from sequencer-specific sequencing errors. A deep learning model named AIVariant, trained on this extended dataset, outperforms previously reported methods when tested under various tumor purities and sequencing depths, especially low tumor purity and sequencing depth.


Asunto(s)
Aprendizaje Profundo , Neoplasias , Humanos , Frecuencia de los Genes , Biología Computacional/métodos , Algoritmos , Neoplasias/genética , Neoplasias/diagnóstico , Mutación
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA