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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2022
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| 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 |