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:10.1101/137547

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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

Department of Genome Sciences, University of WashingtonHoward Hughes Medical Institute, University of Washington

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ORCID record for Josh Cuperus

Benjamin Groves

Department of Electrical Engineering, University of Washington

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Anna Kuchina

Department of Electrical Engineering, University of Washington

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Alexander B. Rosenberg

Department of Electrical Engineering, University of Washington

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Nebojsa Jojic

Microsoft Research

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Stanley Fields

Department of Genome Sciences, University of WashingtonDepartment of Medicine, University of WashingtonHoward Hughes Medical Institute, University of Washington

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For correspondence: gseelig@uw.edu fields@uw.edu

Georg Seelig

Department of Electrical Engineering, University of WashingtonDepartment 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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