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Genome-wide prediction of bacterial effectors across six secretion system types using a feature-based supervised learning framework
Andi Dhroso, Samantha Eidson, Dmitry Korkin
doi: https://doi.org/10.1101/255604
Andi Dhroso
1Department of Computer Science, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
Samantha Eidson
Dmitry Korkin
1Department of Computer Science, and Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
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Posted January 29, 2018.
Genome-wide prediction of bacterial effectors across six secretion system types using a feature-based supervised learning framework
Andi Dhroso, Samantha Eidson, Dmitry Korkin
bioRxiv 255604; doi: https://doi.org/10.1101/255604
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