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Extracting a Biologically Relevant Latent Space from Cancer Transcriptomes with Variational Autoencoders

View ORCID ProfileGregory P. Way, View ORCID ProfileCasey S. Greene
doi: https://doi.org/10.1101/174474
Gregory P. Way
1Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, PA 19104, USA E-mail:
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  • For correspondence: gregway@mail.med.upenn.edu
Casey S. Greene
2Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania, Philadelphia, PA 19104, USA E-mail:
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  • For correspondence: csgreene@mail.med.upenn.edu
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Posted October 02, 2017.
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Extracting a Biologically Relevant Latent Space from Cancer Transcriptomes with Variational Autoencoders
Gregory P. Way, Casey S. Greene
bioRxiv 174474; doi: https://doi.org/10.1101/174474
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Extracting a Biologically Relevant Latent Space from Cancer Transcriptomes with Variational Autoencoders
Gregory P. Way, Casey S. Greene
bioRxiv 174474; doi: https://doi.org/10.1101/174474

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