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Deep learning of the regulatory grammar of yeast 5’ untranslated regions from 500,000 random sequences

Josh Cuperus, Benjamin Groves, Anna Kuchina, Alexander B. Rosenberg, Nebojsa Jojic, Stanley Fields, Georg Seelig
doi: https://doi.org/10.1101/137547

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doi 
https://doi.org/10.1101/137547
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  • May 12, 2017.

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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-NC-ND 4.0 International license.

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  1. Josh Cuperus1,6*,
  2. Benjamin Groves2*,
  3. Anna Kuchina2*,
  4. Alexander B. Rosenberg2*,
  5. Nebojsa Jojic3,
  6. Stanley Fields1,5,6,$ and
  7. Georg Seelig2,4,$
  1. 1Department of Genome Sciences, University of Washington
  2. 2Department of Electrical Engineering, University of Washington
  3. 3Microsoft Research
  4. 4Department of Computer Science & Engineering, University of Washington
  5. 5Department of Medicine, University of Washington
  6. 6Howard Hughes Medical Institute, University of Washington
  1. ↵$correspondence: gseelig{at}uw.edu, fields{at}uw.edu
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Posted May 12, 2017.
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Deep learning of the regulatory grammar of yeast 5’ untranslated regions from 500,000 random sequences
Josh Cuperus, Benjamin Groves, Anna Kuchina, Alexander B. Rosenberg, Nebojsa Jojic, Stanley Fields, Georg Seelig
bioRxiv 137547; doi: https://doi.org/10.1101/137547
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