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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...
Shranjeno v:
| izdano v: | Pac Symp Biocomput |
|---|---|
| Main Authors: | , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
2018
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| Teme: | |
| Online dostop: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5728678/ https://ncbi.nlm.nih.gov/pubmed/29218871 |
| Oznake: |
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