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DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier

View ORCID ProfileMaxat Kulmanov, View ORCID ProfileRobert Hoehndorf
doi: https://doi.org/10.1101/839332
Maxat Kulmanov
1Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
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Robert Hoehndorf
1Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
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  • For correspondence: robert.hoehndorf@kaust.edu.sa
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Article Information

doi 
https://doi.org/10.1101/839332
History 
  • March 25, 2020.

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  • Version 1 (November 13, 2019 - 07:46).
  • You are viewing Version 2, the most recent version of this article.
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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 4.0 International license.

Author Information

  1. Maxat Kulmanov1 and
  2. Robert Hoehndorf1,*
  1. 1Computational Bioscience Research Center, Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
  1. ↵*To whom correspondence should be addressed. email: robert.hoehndorf{at}kaust.edu.sa
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Posted March 25, 2020.
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DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
Maxat Kulmanov, Robert Hoehndorf
bioRxiv 839332; doi: https://doi.org/10.1101/839332
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DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
Maxat Kulmanov, Robert Hoehndorf
bioRxiv 839332; doi: https://doi.org/10.1101/839332

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