WGS to predict antibiotic MICs for Neisseria gonorrhoeae
Background<br/> Tracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. <br/><br/>Objectives<br/> We investigate whether WGS and simultaneous analysis of multiple resistance determinants can be used to pre...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Oxford University Press
2017
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