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Journal article

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data

Abstract:

Motivation

Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence of any well-studied single nucleotide polymorphisms is sufficient to cause resistance, which yields low sensitivity for resistance classification.

Methods

Compared to previous rules-based approach, the sensitivities from...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/bioinformatics/btx801

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM; NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM; Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
ORCID:
0000-0002-0412-8509
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K.C. Wong Education Foundation More from this funder
Rhodes Trust More from this funder
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Publisher:
Oxford University Press Publisher's website
Journal:
Bioinformatics Journal website
Volume:
36
Issue:
10
Pages:
1666–1671
Publication date:
2017-12-12
Acceptance date:
2017-12-05
DOI:
EISSN:
1460-2059
ISSN:
1367-4811
Source identifiers:
810388
Pubs id:
pubs:810388
UUID:
uuid:405f6035-30b9-4670-98ee-423436e42b8b
Local pid:
pubs:810388
Deposit date:
2017-12-11

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