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

View ORCID ProfileJosh Cuperus, Benjamin Groves, Anna Kuchina, Alexander B. Rosenberg, Nebojsa Jojic, Stanley Fields, Georg Seelig
doi: https://doi.org/10.1101/137547
Josh Cuperus
1Department of Genome Sciences, University of Washington
6Howard Hughes Medical Institute, University of Washington
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  • ORCID record for Josh Cuperus
Benjamin Groves
2Department of Electrical Engineering, University of Washington
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Anna Kuchina
2Department of Electrical Engineering, University of Washington
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Alexander B. Rosenberg
2Department of Electrical Engineering, University of Washington
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Nebojsa Jojic
3Microsoft Research
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Stanley Fields
1Department of Genome Sciences, University of Washington
5Department of Medicine, University of Washington
6Howard Hughes Medical Institute, University of Washington
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  • For correspondence: gseelig@uw.edu fields@uw.edu
Georg Seelig
2Department of Electrical Engineering, University of Washington
4Department of Computer Science & Engineering, University of Washington
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  • For correspondence: gseelig@uw.edu fields@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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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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