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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...

詳細記述

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書誌詳細
出版年:Pac Symp Biocomput
主要な著者: Way, Gregory P., Greene, Casey S.
フォーマット: Artigo
言語:Inglês
出版事項: 2018
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC5728678/
https://ncbi.nlm.nih.gov/pubmed/29218871
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