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Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders
The Cancer Genome Atlas (TCGA) has profiled over 10,000 tumors across 33 different cancer-types for many genomic features, including gene expression levels. Gene expression measurements capture substantial information about the state of each tumor. Certain classes of deep neural network models are c...
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| Publicado en: | Pac Symp Biocomput |
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| Autores principales: | , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5728678/ https://ncbi.nlm.nih.gov/pubmed/29218871 |
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