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StartLink+: Prediction of Gene Starts in Prokaryotic Genomes by an Algorithm Integrating Independent Sources of Evidence

Karl Gemayel, Alexandre Lomsadze, Mark Borodovsky
doi: https://doi.org/10.1101/2020.10.25.352625
Karl Gemayel
1School of Computational Science and Engineering, Georgia Tech, Atlanta, GA 30332, USA
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Alexandre Lomsadze
2Wallace H Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA 30332, USA
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Mark Borodovsky
1School of Computational Science and Engineering, Georgia Tech, Atlanta, GA 30332, USA
2Wallace H Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA 30332, USA
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  • For correspondence: borodovsky@gatech.edu
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Article Information

doi 
https://doi.org/10.1101/2020.10.25.352625
History 
  • October 26, 2020.
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. Karl Gemayel1,
  2. Alexandre Lomsadze2 and
  3. Mark Borodovsky1,2,^
  1. 1School of Computational Science and Engineering, Georgia Tech, Atlanta, GA 30332, USA
  2. 2Wallace H Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA 30332, USA
  1. ↵^corresponding author borodovsky{at}gatech.edu
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Posted October 26, 2020.
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StartLink+: Prediction of Gene Starts in Prokaryotic Genomes by an Algorithm Integrating Independent Sources of Evidence
Karl Gemayel, Alexandre Lomsadze, Mark Borodovsky
bioRxiv 2020.10.25.352625; doi: https://doi.org/10.1101/2020.10.25.352625
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StartLink+: Prediction of Gene Starts in Prokaryotic Genomes by an Algorithm Integrating Independent Sources of Evidence
Karl Gemayel, Alexandre Lomsadze, Mark Borodovsky
bioRxiv 2020.10.25.352625; doi: https://doi.org/10.1101/2020.10.25.352625

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