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Robust Neural Networks are More Interpretable for Genomics

Peter K. Koo, Sharon Qian, Gal Kaplun, Verena Volf, Dimitris Kalimeris
doi: https://doi.org/10.1101/657437
Peter K. Koo
1Howard Hughes Medical Institute, Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
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  • For correspondence: peter_koo@harvard.edu
Sharon Qian
2Department of Computer Science, Harvard University, Cambridge, MA, USA
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Gal Kaplun
2Department of Computer Science, Harvard University, Cambridge, MA, USA
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Verena Volf
3Department of Genetics, Harvard Medical School, Boston, MA, USA
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Dimitris Kalimeris
2Department of Computer Science, Harvard University, Cambridge, MA, USA
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Article Information

doi 
https://doi.org/10.1101/657437
History 
  • June 3, 2019.
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-NC-ND 4.0 International license.

Author Information

  1. Peter K. Koo1,*,
  2. Sharon Qian2,
  3. Gal Kaplun2,
  4. Verena Volf3 and
  5. Dimitris Kalimeris2
  1. 1Howard Hughes Medical Institute, Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
  2. 2Department of Computer Science, Harvard University, Cambridge, MA, USA
  3. 3Department of Genetics, Harvard Medical School, Boston, MA, USA
  1. ↵*Correspondence to: Peter K. Koo <peter_koo{at}harvard.edu>.
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Posted June 03, 2019.
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Robust Neural Networks are More Interpretable for Genomics
Peter K. Koo, Sharon Qian, Gal Kaplun, Verena Volf, Dimitris Kalimeris
bioRxiv 657437; doi: https://doi.org/10.1101/657437
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Robust Neural Networks are More Interpretable for Genomics
Peter K. Koo, Sharon Qian, Gal Kaplun, Verena Volf, Dimitris Kalimeris
bioRxiv 657437; doi: https://doi.org/10.1101/657437

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