BRCA1-specific machine learning model predicts variant pathogenicity with high accuracy

Identification of novel BRCA1 variants outpaces their clinical annotation which highlights the importance of developing accurate computational methods for risk assessment. Therefore our aim was to develop a BRCA1-specific machine learning model to predict the pathogenicity of all types of BRCA1 vari...

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Detalles Bibliográficos
Autores principales: Khandakji, Mohannad, Habish, Hind Hassan Ahmed, Abdulla, Nawal Bakheet Salem, Kusasi, Sitti Apsa Albani, Abdou, Nema Mahmoud Ghobashy, Al-Mulla, Hajer Mahmoud M. A., Al Sulaiman, Reem Jawad A. A., Bu Jassoum, Salha M., Mifsud, Borbala
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Physiological Society 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393322/
https://www.ncbi.nlm.nih.gov/pubmed/37335020
http://dx.doi.org/10.1152/physiolgenomics.00033.2023

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393322/
https://www.ncbi.nlm.nih.gov/pubmed/37335020
http://dx.doi.org/10.1152/physiolgenomics.00033.2023

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