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A comprehensive evaluation of long read error correction methods

View ORCID ProfileHaowen Zhang, Chirag Jain, Srinivas Aluru
doi: https://doi.org/10.1101/519330
Haowen Zhang
1School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
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  • ORCID record for Haowen Zhang
Chirag Jain
1School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Srinivas Aluru
1School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
2Institute for Data Engineering and Science, Georgia Institute of Technology, Atlanta, GA 30332, USA
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  • For correspondence: aluru@cc.gatech.edu
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Article Information

doi 
https://doi.org/10.1101/519330
History 
  • May 29, 2019.

Article Versions

  • Version 1 (January 13, 2019 - 15:44).
  • You are viewing Version 2, 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 4.0 International license.

Author Information

  1. Haowen Zhang1,
  2. Chirag Jain1 and
  3. Srinivas Aluru1,2,*
  1. 1School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
  2. 2Institute for Data Engineering and Science, Georgia Institute of Technology, Atlanta, GA 30332, USA
  1. ↵*Correspondence: aluru{at}cc.gatech.edu
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Posted May 29, 2019.
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A comprehensive evaluation of long read error correction methods
Haowen Zhang, Chirag Jain, Srinivas Aluru
bioRxiv 519330; doi: https://doi.org/10.1101/519330
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A comprehensive evaluation of long read error correction methods
Haowen Zhang, Chirag Jain, Srinivas Aluru
bioRxiv 519330; doi: https://doi.org/10.1101/519330

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