Cargando…
Performance evaluation of pathogenicity-computation methods for missense variants
With expanding applications of next-generation sequencing in medical genetics, increasing computational methods are being developed to predict the pathogenicity of missense variants. Selecting optimal methods can accelerate the identification of candidate genes. However, the performances of differen...
Autores principales: | Li, Jinchen, Zhao, Tingting, Zhang, Yi, Zhang, Kun, Shi, Leisheng, Chen, Yun, Wang, Xingxing, Sun, Zhongsheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125674/ https://www.ncbi.nlm.nih.gov/pubmed/30060008 http://dx.doi.org/10.1093/nar/gky678 |
Ejemplares similares
-
VarCards: an integrated genetic and clinical database for coding variants in the human genome
por: Li, Jinchen, et al.
Publicado: (2018) -
Comprehensive evaluation of computational methods for predicting cancer driver genes
por: Shi, Xiaohui, et al.
Publicado: (2022) -
Genetic evidence of gender difference in autism spectrum disorder supports the female-protective effect
por: Zhang, Yi, et al.
Publicado: (2020) -
MVP predicts the pathogenicity of missense variants by deep learning
por: Qi, Hongjian, et al.
Publicado: (2021) -
Rhapsody: predicting the pathogenicity of human missense variants
por: Ponzoni, Luca, et al.
Publicado: (2020)