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Multi-scale deep tensor factorization learns a latent representation of the human epigenome

Jacob Schreiber, Timothy Durham, Jeffrey Bilmes, William Stafford Noble
doi: https://doi.org/10.1101/364976
Jacob Schreiber
1Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, USA
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Timothy Durham
2Department of Genome Sciences, University of Washington, Seattle, USA
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Jeffrey Bilmes
1Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, USA
3Department of Electrical Engineering, University of Washington, Seattle, USA
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William Stafford Noble
1Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, USA
2Department of Genome Sciences, University of Washington, Seattle, USA
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  • For correspondence: wnoble@uw.edu
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Article Information

doi 
https://doi.org/10.1101/364976
History 
  • April 11, 2019.

Article Versions

  • Version 1 (July 8, 2018 - 19:21).
  • You are viewing Version 2, the most recent version of this article.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.

Author Information

  1. Jacob Schreiber1,
  2. Timothy Durham2,
  3. Jeffrey Bilmes1,3 and
  4. William Stafford Noble1,2,*
  1. 1Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, USA
  2. 2Department of Genome Sciences, University of Washington, Seattle, USA
  3. 3Department of Electrical Engineering, University of Washington, Seattle, USA
  1. ↵*Corresponding author; email: wnoble{at}uw.edu
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Posted April 11, 2019.
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Multi-scale deep tensor factorization learns a latent representation of the human epigenome
Jacob Schreiber, Timothy Durham, Jeffrey Bilmes, William Stafford Noble
bioRxiv 364976; doi: https://doi.org/10.1101/364976
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Multi-scale deep tensor factorization learns a latent representation of the human epigenome
Jacob Schreiber, Timothy Durham, Jeffrey Bilmes, William Stafford Noble
bioRxiv 364976; doi: https://doi.org/10.1101/364976

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