A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning

BACKGROUND: Selecting and prioritizing candidate disease genes is necessary before conducting laboratory studies as identifying disease genes from a large number of candidate genes using laboratory methods, is a very costly and time-consuming task. There are many machine learning-based gene prioriti...

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Detalles Bibliográficos
Autores principales: Azadifar, Saeid, Ahmadi, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9563530/
https://www.ncbi.nlm.nih.gov/pubmed/36241966
http://dx.doi.org/10.1186/s12859-022-04954-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9563530/
https://www.ncbi.nlm.nih.gov/pubmed/36241966
http://dx.doi.org/10.1186/s12859-022-04954-x

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