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Journal article

DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis

Abstract:

Motivation Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages.

Results We used a large cohort of TB patients from 16 countrie...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1093/bioinformatics/btz067

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Kellogg College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
ORCID:
0000-0002-0412-8509
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
Expand authors...
Publisher:
Oxford University Press Publisher's website
Journal:
Bioinformatics Journal website
Volume:
35
Issue:
18
Pages:
3240–3249
Publication date:
2019-01-28
Acceptance date:
2019-01-19
DOI:
EISSN:
1460-2059
ISSN:
1367-4803
Pubs id:
pubs:965434
UUID:
uuid:3b1a36ea-ee7f-4d41-a862-bb8ebb7fac4a
Local pid:
pubs:965434
Deposit date:
2019-01-21

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