Journal article
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
- Abstract:
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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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(Version of record, pdf, 1.1MB)
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(Version of record, zip, 14.8MB)
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- Publisher copy:
- 10.1093/bioinformatics/btz067
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Authors
Bibliographic Details
- 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:
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1460-2059
- ISSN:
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1367-4803
Item Description
- Pubs id:
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pubs:965434
- UUID:
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uuid:3b1a36ea-ee7f-4d41-a862-bb8ebb7fac4a
- Local pid:
- pubs:965434
- Deposit date:
- 2019-01-21
Terms of use
- Copyright holder:
- Yang et al
- Copyright date:
- 2019
- Notes:
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Copyright © 2019 The Authors. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited
- Licence:
- CC Attribution (CC BY)
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