Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Erol S. Kavvas; Edward Catoiu; Nathan Mih; James T. Yurkovich; Yara Seif; Nicholas Dillon; David Heckmann; Amitesh Anand; Laurence Yang; Victor Nizet; Jonathan M. Monk; Bernhard O. Palsson

doi:10.1038/s41467-018-06634-y

Nature Communications (Oct 2018)

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Erol S. Kavvas,
Edward Catoiu,
Nathan Mih,
James T. Yurkovich,
Yara Seif,
Nicholas Dillon,
David Heckmann,
Amitesh Anand,
Laurence Yang,
Victor Nizet,
Jonathan M. Monk,
Bernhard O. Palsson

Affiliations

Erol S. Kavvas: Department of Bioengineering, University of California
Edward Catoiu: Department of Bioengineering, University of California
Nathan Mih: Department of Bioengineering, University of California
James T. Yurkovich: Department of Bioengineering, University of California
Yara Seif: Department of Bioengineering, University of California
Nicholas Dillon: Department of Pediatrics, University of California
David Heckmann: Department of Bioengineering, University of California
Amitesh Anand: Department of Bioengineering, University of California
Laurence Yang: Department of Bioengineering, University of California
Victor Nizet: Department of Pediatrics, University of California
Jonathan M. Monk: Department of Bioengineering, University of California
Bernhard O. Palsson: Department of Bioengineering, University of California

DOI: https://doi.org/10.1038/s41467-018-06634-y
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 9

Abstract

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Mycobacterium tuberculosis exhibits complex evolution of antimicrobial resistance (AMR). Here, the authors perform machine learning and structural analysis to identify signatures of AMR evolution to 13 antibiotics.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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