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Representation Learning of Genomic Sequence Motifs with Convolutional Neural Networks

Peter K. Koo, Sean R. Eddy
doi: https://doi.org/10.1101/362756
Peter K. Koo
1Howard Hughes Medical Institute, Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA
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  • For correspondence: koo@cshl.edu seaneddy@fas.harvard.edu
Sean R. Eddy
1Howard Hughes Medical Institute, Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA
2John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
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  • For correspondence: koo@cshl.edu seaneddy@fas.harvard.edu
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Article Information

doi 
https://doi.org/10.1101/362756
History 
  • October 18, 2019.

Article Versions

  • Version 1 (July 8, 2018 - 19:12).
  • Version 2 (April 11, 2019 - 07:43).
  • Version 3 (July 26, 2019 - 13:20).
  • You are viewing Version 4, 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. Peter K. Koo1,* and
  2. Sean R. Eddy1,2,*
  1. 1Howard Hughes Medical Institute, Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA
  2. 2John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
  1. ↵*Corresponding Authors: koo{at}cshl.edu & seaneddy{at}fas.harvard.edu.
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Posted October 18, 2019.
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Representation Learning of Genomic Sequence Motifs with Convolutional Neural Networks
Peter K. Koo, Sean R. Eddy
bioRxiv 362756; doi: https://doi.org/10.1101/362756
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Representation Learning of Genomic Sequence Motifs with Convolutional Neural Networks
Peter K. Koo, Sean R. Eddy
bioRxiv 362756; doi: https://doi.org/10.1101/362756

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