A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis
Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution to multi-drug resistance diagnosis. Here, the authors present two deep convolutional neural networks that predict the antibiotic resistance phenotypes of M. tuberculosis isolates.
Main Authors: | Anna G. Green, Chang Ho Yoon, Michael L. Chen, Yasha Ektefaie, Mack Fina, Luca Freschi, Matthias I. Gröschel, Isaac Kohane, Andrew Beam, Maha Farhat |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-07-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-022-31236-0 |
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