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

New Results

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

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for Josh Cuperus

Benjamin Groves

2Department of Electrical Engineering, University of Washington

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Anna Kuchina

2Department of Electrical Engineering, University of Washington

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Alexander B. Rosenberg

2Department of Electrical Engineering, University of Washington

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Nebojsa Jojic

3Microsoft Research

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site

Stanley Fields

1Department of Genome Sciences, University of Washington

5Department of Medicine, University of Washington

6Howard Hughes Medical Institute, University of Washington

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
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

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
For correspondence: gseelig@uw.edu fields@uw.edu

Abstract
Full Text
Info/History
Metrics
Supplementary material
Preview PDF

Supplemental Figures

View the discussion thread.

PreviousNext

Posted May 12, 2017.

Download PDF

Supplementary Material

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Your Email *

Your Name *

Send To *

Enter multiple addresses on separate lines or separate them with commas.

You are going to email the following Deep learning of the regulatory grammar of yeast 5’ untranslated regions from 500,000 random sequences

Message Subject (Your Name) has forwarded a page to you from bioRxiv

Message Body (Your Name) thought you would like to see this page from the bioRxiv website.

Your Personal Message

CAPTCHA

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

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

Share This Article:

Citation Tools

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

Citation Manager Formats

BibTeX
Bookends
EasyBib
EndNote (tagged)
EndNote 8 (xml)
Medlars
Mendeley
Papers
RefWorks Tagged
Ref Manager
RIS
Zotero

Tweet Widget
Facebook Like
Google Plus One

Subject Area

Synthetic Biology

Subject Areas

All Articles

Animal Behavior and Cognition (3073)
Biochemistry (6246)
Bioengineering (4469)
Bioinformatics (17971)
Biophysics (8593)
Cancer Biology (6615)
Cell Biology (9636)
Clinical Trials (138)
Developmental Biology (5566)
Ecology (8783)
Epidemiology (2063)
Evolutionary Biology (11960)
Genetics (8590)
Genomics (11375)
Immunology (6406)
Microbiology (16433)
Molecular Biology (6398)
Neuroscience (35842)
Paleontology (258)
Pathology (1061)
Pharmacology and Toxicology (1811)
Physiology (2673)
Plant Biology (5951)
Scientific Communication and Education (1151)
Synthetic Biology (1642)
Systems Biology (4762)
Zoology (939)