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Efficient feature extraction from highly sparse binary genotype data for cancer prognosis prediction using an auto-encoder
Genomics involving tens of thousands of genes is a complex system determining phenotype. An interesting and vital issue is how to integrate highly sparse genetic genomics data with a mass of minor effects into a prediction model for improving prediction power. We find that the deep learning method c...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872139/ https://www.ncbi.nlm.nih.gov/pubmed/36703783 http://dx.doi.org/10.3389/fonc.2022.1091767 |