Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosis Article Swipe
Sanjana G. Kulkarni
,
Sacha Laurent
,
Paolo Miotto
,
A Sarah Walker
,
Leonid Chindelevitch
,
Carl‐Michael Nathanson
,
Nazir Ismail
,
Timothy C. Rodwell
,
Maha Farhat
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41467-025-57174-1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41467-025-57174-1
Rapid genotype-based drug susceptibility testing for the Mycobacterium tuberculosis complex (MTBC) relies on a comprehensive knowledgebase of the genetic determinants of resistance. Here we present a catalogue of resistance-associated mutations using a regression-based approach and benchmark it against the 2nd edition of the World Health Organisation (WHO) mutation catalogue. We train multivariate logistic regression models on over 52,000 MTBC isolates to associate binary resistance phenotypes for 15 antitubercular drugs with variants extracted from candidate resistance genes. Regression detects 450/457 (98%) resistance-associated variants identified using the existing method (a.k.a, SOLO method) and grades 221 (29%) more total variants than SOLO. The regression-based catalogue achieves higher sensitivity on average (+3.2 percentage points, pp) than SOLO with smaller average decreases in specificity (-1.0 pp) and positive predictive value (-1.6 pp). Sensitivity gains are highest for ethambutol, clofazimine, streptomycin, and ethionamide as regression graded considerably more resistance-associated variants than SOLO for these drugs. There is no difference between SOLO and regression with regards to meeting the target product profiles set by the WHO for genetic drug susceptibility testing, except for rifampicin, for which regression specificity is below the threshold of 98% at 97%. The regression pipeline also detects isoniazid resistance compensatory mutations in ahpC and variants linked to bedaquiline and aminoglycoside hypersusceptibility. These results inform the continued development of targeted next generation sequencing, whole genome sequencing, and other commercial molecular assays for diagnosing resistance in the MTBC.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41467-025-57174-1
- https://www.nature.com/articles/s41467-025-57174-1.pdf
- OA Status
- gold
- Cited By
- 6
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408110940
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4408110940Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41467-025-57174-1Digital Object Identifier
- Title
-
Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-03-03Full publication date if available
- Authors
-
Sanjana G. Kulkarni, Sacha Laurent, Paolo Miotto, A Sarah Walker, Leonid Chindelevitch, Carl‐Michael Nathanson, Nazir Ismail, Timothy C. Rodwell, Maha FarhatList of authors in order
- Landing page
-
https://doi.org/10.1038/s41467-025-57174-1Publisher landing page
- PDF URL
-
https://www.nature.com/articles/s41467-025-57174-1.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.nature.com/articles/s41467-025-57174-1.pdfDirect OA link when available
- Concepts
-
Mycobacterium tuberculosis, Tuberculosis, Antibiotics, Antibiotic resistance, Multivariable calculus, Microbiology, Regression, Medicine, Biology, Pathology, Statistics, Mathematics, Control engineering, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 6Per-year citation counts (last 5 years)
- References (count)
-
37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4408110940 |
|---|---|
| doi | https://doi.org/10.1038/s41467-025-57174-1 |
| ids.doi | https://doi.org/10.1038/s41467-025-57174-1 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/40032816 |
| ids.openalex | https://openalex.org/W4408110940 |
| fwci | 27.60810298 |
| mesh[0].qualifier_ui | Q000235 |
| mesh[0].descriptor_ui | D009169 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | genetics |
| mesh[0].descriptor_name | Mycobacterium tuberculosis |
| mesh[1].qualifier_ui | Q000187 |
| mesh[1].descriptor_ui | D009169 |
| mesh[1].is_major_topic | True |
| mesh[1].qualifier_name | drug effects |
| mesh[1].descriptor_name | Mycobacterium tuberculosis |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D009154 |
| mesh[2].is_major_topic | True |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Mutation |
| mesh[3].qualifier_ui | Q000494 |
| mesh[3].descriptor_ui | D000995 |
| mesh[3].is_major_topic | True |
| mesh[3].qualifier_name | pharmacology |
| mesh[3].descriptor_name | Antitubercular Agents |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D008826 |
| mesh[4].is_major_topic | True |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Microbial Sensitivity Tests |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D006801 |
| mesh[5].is_major_topic | False |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Humans |
| mesh[6].qualifier_ui | Q000235 |
| mesh[6].descriptor_ui | D024881 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | genetics |
| mesh[6].descriptor_name | Drug Resistance, Bacterial |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D016015 |
| mesh[7].is_major_topic | False |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Logistic Models |
| mesh[8].qualifier_ui | Q000382 |
| mesh[8].descriptor_ui | D018088 |
| mesh[8].is_major_topic | False |
| mesh[8].qualifier_name | microbiology |
| mesh[8].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[9].qualifier_ui | Q000235 |
| mesh[9].descriptor_ui | D018088 |
| mesh[9].is_major_topic | False |
| mesh[9].qualifier_name | genetics |
| mesh[9].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[10].qualifier_ui | Q000188 |
| mesh[10].descriptor_ui | D018088 |
| mesh[10].is_major_topic | False |
| mesh[10].qualifier_name | drug therapy |
| mesh[10].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[11].qualifier_ui | |
| mesh[11].descriptor_ui | D005838 |
| mesh[11].is_major_topic | False |
| mesh[11].qualifier_name | |
| mesh[11].descriptor_name | Genotype |
| mesh[12].qualifier_ui | Q000235 |
| mesh[12].descriptor_ui | D009169 |
| mesh[12].is_major_topic | True |
| mesh[12].qualifier_name | genetics |
| mesh[12].descriptor_name | Mycobacterium tuberculosis |
| mesh[13].qualifier_ui | Q000187 |
| mesh[13].descriptor_ui | D009169 |
| mesh[13].is_major_topic | True |
| mesh[13].qualifier_name | drug effects |
| mesh[13].descriptor_name | Mycobacterium tuberculosis |
| mesh[14].qualifier_ui | |
| mesh[14].descriptor_ui | D009154 |
| mesh[14].is_major_topic | True |
| mesh[14].qualifier_name | |
| mesh[14].descriptor_name | Mutation |
| mesh[15].qualifier_ui | Q000494 |
| mesh[15].descriptor_ui | D000995 |
| mesh[15].is_major_topic | True |
| mesh[15].qualifier_name | pharmacology |
| mesh[15].descriptor_name | Antitubercular Agents |
| mesh[16].qualifier_ui | |
| mesh[16].descriptor_ui | D008826 |
| mesh[16].is_major_topic | True |
| mesh[16].qualifier_name | |
| mesh[16].descriptor_name | Microbial Sensitivity Tests |
| mesh[17].qualifier_ui | |
| mesh[17].descriptor_ui | D006801 |
| mesh[17].is_major_topic | False |
| mesh[17].qualifier_name | |
| mesh[17].descriptor_name | Humans |
| mesh[18].qualifier_ui | Q000235 |
| mesh[18].descriptor_ui | D024881 |
| mesh[18].is_major_topic | False |
| mesh[18].qualifier_name | genetics |
| mesh[18].descriptor_name | Drug Resistance, Bacterial |
| mesh[19].qualifier_ui | |
| mesh[19].descriptor_ui | D016015 |
| mesh[19].is_major_topic | False |
| mesh[19].qualifier_name | |
| mesh[19].descriptor_name | Logistic Models |
| mesh[20].qualifier_ui | Q000382 |
| mesh[20].descriptor_ui | D018088 |
| mesh[20].is_major_topic | False |
| mesh[20].qualifier_name | microbiology |
| mesh[20].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[21].qualifier_ui | Q000235 |
| mesh[21].descriptor_ui | D018088 |
| mesh[21].is_major_topic | False |
| mesh[21].qualifier_name | genetics |
| mesh[21].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[22].qualifier_ui | Q000188 |
| mesh[22].descriptor_ui | D018088 |
| mesh[22].is_major_topic | False |
| mesh[22].qualifier_name | drug therapy |
| mesh[22].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[23].qualifier_ui | |
| mesh[23].descriptor_ui | D005838 |
| mesh[23].is_major_topic | False |
| mesh[23].qualifier_name | |
| mesh[23].descriptor_name | Genotype |
| mesh[24].qualifier_ui | Q000235 |
| mesh[24].descriptor_ui | D009169 |
| mesh[24].is_major_topic | True |
| mesh[24].qualifier_name | genetics |
| mesh[24].descriptor_name | Mycobacterium tuberculosis |
| mesh[25].qualifier_ui | Q000187 |
| mesh[25].descriptor_ui | D009169 |
| mesh[25].is_major_topic | True |
| mesh[25].qualifier_name | drug effects |
| mesh[25].descriptor_name | Mycobacterium tuberculosis |
| mesh[26].qualifier_ui | |
| mesh[26].descriptor_ui | D009154 |
| mesh[26].is_major_topic | True |
| mesh[26].qualifier_name | |
| mesh[26].descriptor_name | Mutation |
| mesh[27].qualifier_ui | Q000494 |
| mesh[27].descriptor_ui | D000995 |
| mesh[27].is_major_topic | True |
| mesh[27].qualifier_name | pharmacology |
| mesh[27].descriptor_name | Antitubercular Agents |
| mesh[28].qualifier_ui | |
| mesh[28].descriptor_ui | D008826 |
| mesh[28].is_major_topic | True |
| mesh[28].qualifier_name | |
| mesh[28].descriptor_name | Microbial Sensitivity Tests |
| mesh[29].qualifier_ui | |
| mesh[29].descriptor_ui | D006801 |
| mesh[29].is_major_topic | False |
| mesh[29].qualifier_name | |
| mesh[29].descriptor_name | Humans |
| mesh[30].qualifier_ui | Q000235 |
| mesh[30].descriptor_ui | D024881 |
| mesh[30].is_major_topic | False |
| mesh[30].qualifier_name | genetics |
| mesh[30].descriptor_name | Drug Resistance, Bacterial |
| mesh[31].qualifier_ui | |
| mesh[31].descriptor_ui | D016015 |
| mesh[31].is_major_topic | False |
| mesh[31].qualifier_name | |
| mesh[31].descriptor_name | Logistic Models |
| mesh[32].qualifier_ui | Q000382 |
| mesh[32].descriptor_ui | D018088 |
| mesh[32].is_major_topic | False |
| mesh[32].qualifier_name | microbiology |
| mesh[32].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[33].qualifier_ui | Q000235 |
| mesh[33].descriptor_ui | D018088 |
| mesh[33].is_major_topic | False |
| mesh[33].qualifier_name | genetics |
| mesh[33].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[34].qualifier_ui | Q000188 |
| mesh[34].descriptor_ui | D018088 |
| mesh[34].is_major_topic | False |
| mesh[34].qualifier_name | drug therapy |
| mesh[34].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[35].qualifier_ui | |
| mesh[35].descriptor_ui | D005838 |
| mesh[35].is_major_topic | False |
| mesh[35].qualifier_name | |
| mesh[35].descriptor_name | Genotype |
| mesh[36].qualifier_ui | Q000235 |
| mesh[36].descriptor_ui | D009169 |
| mesh[36].is_major_topic | True |
| mesh[36].qualifier_name | genetics |
| mesh[36].descriptor_name | Mycobacterium tuberculosis |
| mesh[37].qualifier_ui | Q000187 |
| mesh[37].descriptor_ui | D009169 |
| mesh[37].is_major_topic | True |
| mesh[37].qualifier_name | drug effects |
| mesh[37].descriptor_name | Mycobacterium tuberculosis |
| mesh[38].qualifier_ui | |
| mesh[38].descriptor_ui | D009154 |
| mesh[38].is_major_topic | True |
| mesh[38].qualifier_name | |
| mesh[38].descriptor_name | Mutation |
| mesh[39].qualifier_ui | Q000494 |
| mesh[39].descriptor_ui | D000995 |
| mesh[39].is_major_topic | True |
| mesh[39].qualifier_name | pharmacology |
| mesh[39].descriptor_name | Antitubercular Agents |
| mesh[40].qualifier_ui | |
| mesh[40].descriptor_ui | D008826 |
| mesh[40].is_major_topic | True |
| mesh[40].qualifier_name | |
| mesh[40].descriptor_name | Microbial Sensitivity Tests |
| mesh[41].qualifier_ui | |
| mesh[41].descriptor_ui | D006801 |
| mesh[41].is_major_topic | False |
| mesh[41].qualifier_name | |
| mesh[41].descriptor_name | Humans |
| mesh[42].qualifier_ui | Q000235 |
| mesh[42].descriptor_ui | D024881 |
| mesh[42].is_major_topic | False |
| mesh[42].qualifier_name | genetics |
| mesh[42].descriptor_name | Drug Resistance, Bacterial |
| mesh[43].qualifier_ui | |
| mesh[43].descriptor_ui | D016015 |
| mesh[43].is_major_topic | False |
| mesh[43].qualifier_name | |
| mesh[43].descriptor_name | Logistic Models |
| mesh[44].qualifier_ui | Q000382 |
| mesh[44].descriptor_ui | D018088 |
| mesh[44].is_major_topic | False |
| mesh[44].qualifier_name | microbiology |
| mesh[44].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[45].qualifier_ui | Q000235 |
| mesh[45].descriptor_ui | D018088 |
| mesh[45].is_major_topic | False |
| mesh[45].qualifier_name | genetics |
| mesh[45].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[46].qualifier_ui | Q000188 |
| mesh[46].descriptor_ui | D018088 |
| mesh[46].is_major_topic | False |
| mesh[46].qualifier_name | drug therapy |
| mesh[46].descriptor_name | Tuberculosis, Multidrug-Resistant |
| mesh[47].qualifier_ui | |
| mesh[47].descriptor_ui | D005838 |
| mesh[47].is_major_topic | False |
| mesh[47].qualifier_name | |
| mesh[47].descriptor_name | Genotype |
| mesh[48].qualifier_ui | Q000235 |
| mesh[48].descriptor_ui | D009169 |
| mesh[48].is_major_topic | True |
| mesh[48].qualifier_name | genetics |
| mesh[48].descriptor_name | Mycobacterium tuberculosis |
| mesh[49].qualifier_ui | Q000187 |
| mesh[49].descriptor_ui | D009169 |
| mesh[49].is_major_topic | True |
| mesh[49].qualifier_name | drug effects |
| mesh[49].descriptor_name | Mycobacterium tuberculosis |
| type | article |
| title | Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosis |
| awards[0].id | https://openalex.org/G4547358731 |
| awards[0].funder_id | https://openalex.org/F4320332161 |
| awards[0].display_name | |
| awards[0].funder_award_id | R01AI155765 |
| awards[0].funder_display_name | National Institutes of Health |
| awards[1].id | https://openalex.org/G3487817322 |
| awards[1].funder_id | https://openalex.org/F4320306076 |
| awards[1].display_name | |
| awards[1].funder_award_id | DGE 2140743 |
| awards[1].funder_display_name | National Science Foundation |
| biblio.issue | 1 |
| biblio.volume | 16 |
| biblio.last_page | 2149 |
| biblio.first_page | 2149 |
| topics[0].id | https://openalex.org/T11316 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9987999796867371 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2713 |
| topics[0].subfield.display_name | Epidemiology |
| topics[0].display_name | Mycobacterium research and diagnosis |
| topics[1].id | https://openalex.org/T10038 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9987000226974487 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2725 |
| topics[1].subfield.display_name | Infectious Diseases |
| topics[1].display_name | Tuberculosis Research and Epidemiology |
| topics[2].id | https://openalex.org/T13114 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9376000165939331 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2214 |
| topics[2].subfield.display_name | Media Technology |
| topics[2].display_name | Image Processing Techniques and Applications |
| funders[0].id | https://openalex.org/F4320306076 |
| funders[0].ror | https://ror.org/021nxhr62 |
| funders[0].display_name | National Science Foundation |
| funders[1].id | https://openalex.org/F4320332161 |
| funders[1].ror | https://ror.org/01cwqze88 |
| funders[1].display_name | National Institutes of Health |
| is_xpac | False |
| apc_list.value | 3920 |
| apc_list.currency | GBP |
| apc_list.value_usd | 4808 |
| apc_paid.value | 3920 |
| apc_paid.currency | GBP |
| apc_paid.value_usd | 4808 |
| concepts[0].id | https://openalex.org/C2777975735 |
| concepts[0].level | 3 |
| concepts[0].score | 0.794489860534668 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q130971 |
| concepts[0].display_name | Mycobacterium tuberculosis |
| concepts[1].id | https://openalex.org/C2781069245 |
| concepts[1].level | 2 |
| concepts[1].score | 0.651374340057373 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q12204 |
| concepts[1].display_name | Tuberculosis |
| concepts[2].id | https://openalex.org/C501593827 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6002206206321716 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q12187 |
| concepts[2].display_name | Antibiotics |
| concepts[3].id | https://openalex.org/C94665300 |
| concepts[3].level | 3 |
| concepts[3].score | 0.5577377676963806 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q63391344 |
| concepts[3].display_name | Antibiotic resistance |
| concepts[4].id | https://openalex.org/C117312493 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5506821870803833 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2035437 |
| concepts[4].display_name | Multivariable calculus |
| concepts[5].id | https://openalex.org/C89423630 |
| concepts[5].level | 1 |
| concepts[5].score | 0.4804953336715698 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7193 |
| concepts[5].display_name | Microbiology |
| concepts[6].id | https://openalex.org/C83546350 |
| concepts[6].level | 2 |
| concepts[6].score | 0.41160088777542114 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1139051 |
| concepts[6].display_name | Regression |
| concepts[7].id | https://openalex.org/C71924100 |
| concepts[7].level | 0 |
| concepts[7].score | 0.39698898792266846 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[7].display_name | Medicine |
| concepts[8].id | https://openalex.org/C86803240 |
| concepts[8].level | 0 |
| concepts[8].score | 0.37005487084388733 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[8].display_name | Biology |
| concepts[9].id | https://openalex.org/C142724271 |
| concepts[9].level | 1 |
| concepts[9].score | 0.12754130363464355 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7208 |
| concepts[9].display_name | Pathology |
| concepts[10].id | https://openalex.org/C105795698 |
| concepts[10].level | 1 |
| concepts[10].score | 0.1217978298664093 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[10].display_name | Statistics |
| concepts[11].id | https://openalex.org/C33923547 |
| concepts[11].level | 0 |
| concepts[11].score | 0.0905909538269043 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[11].display_name | Mathematics |
| concepts[12].id | https://openalex.org/C133731056 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q4917288 |
| concepts[12].display_name | Control engineering |
| concepts[13].id | https://openalex.org/C127413603 |
| concepts[13].level | 0 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[13].display_name | Engineering |
| keywords[0].id | https://openalex.org/keywords/mycobacterium-tuberculosis |
| keywords[0].score | 0.794489860534668 |
| keywords[0].display_name | Mycobacterium tuberculosis |
| keywords[1].id | https://openalex.org/keywords/tuberculosis |
| keywords[1].score | 0.651374340057373 |
| keywords[1].display_name | Tuberculosis |
| keywords[2].id | https://openalex.org/keywords/antibiotics |
| keywords[2].score | 0.6002206206321716 |
| keywords[2].display_name | Antibiotics |
| keywords[3].id | https://openalex.org/keywords/antibiotic-resistance |
| keywords[3].score | 0.5577377676963806 |
| keywords[3].display_name | Antibiotic resistance |
| keywords[4].id | https://openalex.org/keywords/multivariable-calculus |
| keywords[4].score | 0.5506821870803833 |
| keywords[4].display_name | Multivariable calculus |
| keywords[5].id | https://openalex.org/keywords/microbiology |
| keywords[5].score | 0.4804953336715698 |
| keywords[5].display_name | Microbiology |
| keywords[6].id | https://openalex.org/keywords/regression |
| keywords[6].score | 0.41160088777542114 |
| keywords[6].display_name | Regression |
| keywords[7].id | https://openalex.org/keywords/medicine |
| keywords[7].score | 0.39698898792266846 |
| keywords[7].display_name | Medicine |
| keywords[8].id | https://openalex.org/keywords/biology |
| keywords[8].score | 0.37005487084388733 |
| keywords[8].display_name | Biology |
| keywords[9].id | https://openalex.org/keywords/pathology |
| keywords[9].score | 0.12754130363464355 |
| keywords[9].display_name | Pathology |
| keywords[10].id | https://openalex.org/keywords/statistics |
| keywords[10].score | 0.1217978298664093 |
| keywords[10].display_name | Statistics |
| keywords[11].id | https://openalex.org/keywords/mathematics |
| keywords[11].score | 0.0905909538269043 |
| keywords[11].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.1038/s41467-025-57174-1 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S64187185 |
| locations[0].source.issn | 2041-1723 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2041-1723 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Nature Communications |
| locations[0].source.host_organization | https://openalex.org/P4310319908 |
| locations[0].source.host_organization_name | Nature Portfolio |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319908, https://openalex.org/P4310319965 |
| locations[0].source.host_organization_lineage_names | Nature Portfolio, Springer Nature |
| locations[0].license | |
| locations[0].pdf_url | https://www.nature.com/articles/s41467-025-57174-1.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Nature Communications |
| locations[0].landing_page_url | https://doi.org/10.1038/s41467-025-57174-1 |
| locations[1].id | pmid:40032816 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Nature communications |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/40032816 |
| locations[2].id | pmh:oai:doaj.org/article:23e670b5b0914742bd448c1afafa5f30 |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Nature Communications, Vol 16, Iss 1, Pp 1-12 (2025) |
| locations[2].landing_page_url | https://doaj.org/article/23e670b5b0914742bd448c1afafa5f30 |
| locations[3].id | pmh:oai:escholarship.org:ark:/13030/qt9cw6d5rf |
| locations[3].is_oa | True |
| locations[3].source | |
| locations[3].license | cc-by-nc-nd |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | article |
| locations[3].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Nature Communications, vol 16, iss 1 |
| locations[3].landing_page_url | https://escholarship.org/uc/item/9cw6d5rf |
| locations[4].id | pmh:oai:pubmedcentral.nih.gov:11876447 |
| locations[4].is_oa | True |
| locations[4].source.id | https://openalex.org/S2764455111 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | False |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | PubMed Central |
| locations[4].source.host_organization | https://openalex.org/I1299303238 |
| locations[4].source.host_organization_name | National Institutes of Health |
| locations[4].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[4].license | other-oa |
| locations[4].pdf_url | |
| locations[4].version | submittedVersion |
| locations[4].raw_type | Text |
| locations[4].license_id | https://openalex.org/licenses/other-oa |
| locations[4].is_accepted | False |
| locations[4].is_published | False |
| locations[4].raw_source_name | Nat Commun |
| locations[4].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/11876447 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5036540449 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-9883-610X |
| authorships[0].author.display_name | Sanjana G. Kulkarni |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I136199984 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA |
| authorships[0].institutions[0].id | https://openalex.org/I136199984 |
| authorships[0].institutions[0].ror | https://ror.org/03vek6s52 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I136199984 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Harvard University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Sanjana G. Kulkarni |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA |
| authorships[1].author.id | https://openalex.org/A5009798279 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-0734-8902 |
| authorships[1].author.display_name | Sacha Laurent |
| authorships[1].countries | CH |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I1281389954 |
| authorships[1].affiliations[0].raw_affiliation_string | Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland |
| authorships[1].institutions[0].id | https://openalex.org/I1281389954 |
| authorships[1].institutions[0].ror | https://ror.org/05tcsqz68 |
| authorships[1].institutions[0].type | nonprofit |
| authorships[1].institutions[0].lineage | https://openalex.org/I1281389954 |
| authorships[1].institutions[0].country_code | CH |
| authorships[1].institutions[0].display_name | Foundation for Innovative New Diagnostics |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Sacha Laurent |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Foundation for Innovative New Diagnostics (FIND), Geneva, Switzerland |
| authorships[2].author.id | https://openalex.org/A5088302359 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-4610-2427 |
| authorships[2].author.display_name | Paolo Miotto |
| authorships[2].countries | IT |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I154387261, https://openalex.org/I4210153126, https://openalex.org/I4387155925 |
| authorships[2].affiliations[0].raw_affiliation_string | IRCCS San Raffaele Scientific Institute, Milano, Italy |
| authorships[2].institutions[0].id | https://openalex.org/I4387155925 |
| authorships[2].institutions[0].ror | https://ror.org/006x48140 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210153126, https://openalex.org/I4387155925 |
| authorships[2].institutions[0].country_code | |
| authorships[2].institutions[0].display_name | Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele |
| authorships[2].institutions[1].id | https://openalex.org/I4210153126 |
| authorships[2].institutions[1].ror | https://ror.org/04tfzc498 |
| authorships[2].institutions[1].type | healthcare |
| authorships[2].institutions[1].lineage | https://openalex.org/I4210153126 |
| authorships[2].institutions[1].country_code | IT |
| authorships[2].institutions[1].display_name | Istituti di Ricovero e Cura a Carattere Scientifico |
| authorships[2].institutions[2].id | https://openalex.org/I154387261 |
| authorships[2].institutions[2].ror | https://ror.org/01gmqr298 |
| authorships[2].institutions[2].type | education |
| authorships[2].institutions[2].lineage | https://openalex.org/I154387261 |
| authorships[2].institutions[2].country_code | IT |
| authorships[2].institutions[2].display_name | Vita-Salute San Raffaele University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Paolo Miotto |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | IRCCS San Raffaele Scientific Institute, Milano, Italy |
| authorships[3].author.id | https://openalex.org/A5046626888 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-0421-9264 |
| authorships[3].author.display_name | A Sarah Walker |
| authorships[3].countries | GB, VN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I40120149 |
| authorships[3].affiliations[0].raw_affiliation_string | Nuffield Department of Medicine, University of Oxford, Oxford, UK |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I4210150114 |
| authorships[3].affiliations[1].raw_affiliation_string | Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam |
| authorships[3].institutions[0].id | https://openalex.org/I40120149 |
| authorships[3].institutions[0].ror | https://ror.org/052gg0110 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I40120149 |
| authorships[3].institutions[0].country_code | GB |
| authorships[3].institutions[0].display_name | University of Oxford |
| authorships[3].institutions[1].id | https://openalex.org/I4210150114 |
| authorships[3].institutions[1].ror | https://ror.org/05rehad94 |
| authorships[3].institutions[1].type | facility |
| authorships[3].institutions[1].lineage | https://openalex.org/I40120149, https://openalex.org/I4210150114, https://openalex.org/I87048295 |
| authorships[3].institutions[1].country_code | VN |
| authorships[3].institutions[1].display_name | Oxford University Clinical Research Unit |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Timothy M. Walker |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Nuffield Department of Medicine, University of Oxford, Oxford, UK, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam |
| authorships[4].author.id | https://openalex.org/A5065939739 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-6619-6013 |
| authorships[4].author.display_name | Leonid Chindelevitch |
| authorships[4].countries | GB |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I47508984, https://openalex.org/I90344618 |
| authorships[4].affiliations[0].raw_affiliation_string | Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK |
| authorships[4].institutions[0].id | https://openalex.org/I47508984 |
| authorships[4].institutions[0].ror | https://ror.org/041kmwe10 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I47508984 |
| authorships[4].institutions[0].country_code | GB |
| authorships[4].institutions[0].display_name | Imperial College London |
| authorships[4].institutions[1].id | https://openalex.org/I90344618 |
| authorships[4].institutions[1].ror | https://ror.org/03x94j517 |
| authorships[4].institutions[1].type | government |
| authorships[4].institutions[1].lineage | https://openalex.org/I4210087105, https://openalex.org/I90344618 |
| authorships[4].institutions[1].country_code | GB |
| authorships[4].institutions[1].display_name | Medical Research Council |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Leonid Chindelevitch |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK |
| authorships[5].author.id | https://openalex.org/A5110158678 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Carl‐Michael Nathanson |
| authorships[5].countries | CH |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210105654 |
| authorships[5].affiliations[0].raw_affiliation_string | Global Tuberculosis Programme, World Health Organization (WHO), Geneva, Switzerland |
| authorships[5].institutions[0].id | https://openalex.org/I4210105654 |
| authorships[5].institutions[0].ror | https://ror.org/01f80g185 |
| authorships[5].institutions[0].type | government |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210105654 |
| authorships[5].institutions[0].country_code | CH |
| authorships[5].institutions[0].display_name | World Health Organization |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Carl-Michael Nathanson |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Global Tuberculosis Programme, World Health Organization (WHO), Geneva, Switzerland |
| authorships[6].author.id | https://openalex.org/A5022980689 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-7696-3776 |
| authorships[6].author.display_name | Nazir Ismail |
| authorships[6].countries | CH |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210105654 |
| authorships[6].affiliations[0].raw_affiliation_string | Global Tuberculosis Programme, World Health Organization (WHO), Geneva, Switzerland |
| authorships[6].institutions[0].id | https://openalex.org/I4210105654 |
| authorships[6].institutions[0].ror | https://ror.org/01f80g185 |
| authorships[6].institutions[0].type | government |
| authorships[6].institutions[0].lineage | https://openalex.org/I4210105654 |
| authorships[6].institutions[0].country_code | CH |
| authorships[6].institutions[0].display_name | World Health Organization |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Nazir Ismail |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Global Tuberculosis Programme, World Health Organization (WHO), Geneva, Switzerland |
| authorships[7].author.id | https://openalex.org/A5008722114 |
| authorships[7].author.orcid | https://orcid.org/0000-0003-2779-3197 |
| authorships[7].author.display_name | Timothy C. Rodwell |
| authorships[7].countries | US |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I2803209242, https://openalex.org/I36258959 |
| authorships[7].affiliations[0].raw_affiliation_string | Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, CA, USA |
| authorships[7].institutions[0].id | https://openalex.org/I2803209242 |
| authorships[7].institutions[0].ror | https://ror.org/00pjdza24 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I2803209242 |
| authorships[7].institutions[0].country_code | US |
| authorships[7].institutions[0].display_name | University of California System |
| authorships[7].institutions[1].id | https://openalex.org/I36258959 |
| authorships[7].institutions[1].ror | https://ror.org/0168r3w48 |
| authorships[7].institutions[1].type | education |
| authorships[7].institutions[1].lineage | https://openalex.org/I36258959 |
| authorships[7].institutions[1].country_code | US |
| authorships[7].institutions[1].display_name | University of California, San Diego |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Timothy C. Rodwell |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Division of Pulmonary, Critical Care and Sleep Medicine, University of California, San Diego, CA, USA |
| authorships[8].author.id | https://openalex.org/A5056381174 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-3871-5760 |
| authorships[8].author.display_name | Maha Farhat |
| authorships[8].countries | US |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I4210087915 |
| authorships[8].affiliations[0].raw_affiliation_string | Division of Pulmonary & Critical Care, Massachusetts General Hospital, Boston, MA, USA |
| authorships[8].institutions[0].id | https://openalex.org/I4210087915 |
| authorships[8].institutions[0].ror | https://ror.org/002pd6e78 |
| authorships[8].institutions[0].type | healthcare |
| authorships[8].institutions[0].lineage | https://openalex.org/I4210087915, https://openalex.org/I48633490 |
| authorships[8].institutions[0].country_code | US |
| authorships[8].institutions[0].display_name | Massachusetts General Hospital |
| authorships[8].author_position | last |
| authorships[8].raw_author_name | Maha R. Farhat |
| authorships[8].is_corresponding | True |
| authorships[8].raw_affiliation_strings | Division of Pulmonary & Critical Care, Massachusetts General Hospital, Boston, MA, USA |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.nature.com/articles/s41467-025-57174-1.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Multivariable regression models improve accuracy and sensitive grading of antibiotic resistance mutations in Mycobacterium tuberculosis |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T11316 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9987999796867371 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2713 |
| primary_topic.subfield.display_name | Epidemiology |
| primary_topic.display_name | Mycobacterium research and diagnosis |
| related_works | https://openalex.org/W2972094210, https://openalex.org/W4308058527, https://openalex.org/W2110949356, https://openalex.org/W4210506554, https://openalex.org/W1538374398, https://openalex.org/W2050407936, https://openalex.org/W2042252940, https://openalex.org/W2411061500, https://openalex.org/W3160640465, https://openalex.org/W2394233015 |
| cited_by_count | 6 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 6 |
| locations_count | 5 |
| best_oa_location.id | doi:10.1038/s41467-025-57174-1 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S64187185 |
| best_oa_location.source.issn | 2041-1723 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2041-1723 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Nature Communications |
| best_oa_location.source.host_organization | https://openalex.org/P4310319908 |
| best_oa_location.source.host_organization_name | Nature Portfolio |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319908, https://openalex.org/P4310319965 |
| best_oa_location.source.host_organization_lineage_names | Nature Portfolio, Springer Nature |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://www.nature.com/articles/s41467-025-57174-1.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Nature Communications |
| best_oa_location.landing_page_url | https://doi.org/10.1038/s41467-025-57174-1 |
| primary_location.id | doi:10.1038/s41467-025-57174-1 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S64187185 |
| primary_location.source.issn | 2041-1723 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2041-1723 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Nature Communications |
| primary_location.source.host_organization | https://openalex.org/P4310319908 |
| primary_location.source.host_organization_name | Nature Portfolio |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319908, https://openalex.org/P4310319965 |
| primary_location.source.host_organization_lineage_names | Nature Portfolio, Springer Nature |
| primary_location.license | |
| primary_location.pdf_url | https://www.nature.com/articles/s41467-025-57174-1.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Nature Communications |
| primary_location.landing_page_url | https://doi.org/10.1038/s41467-025-57174-1 |
| publication_date | 2025-03-03 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W2990312921, https://openalex.org/W2952463453, https://openalex.org/W2779510789, https://openalex.org/W1863711781, https://openalex.org/W3210823154, https://openalex.org/W3028329270, https://openalex.org/W2943862789, https://openalex.org/W4390790879, https://openalex.org/W4221007313, https://openalex.org/W3196454029, https://openalex.org/W4388558072, https://openalex.org/W4283592223, https://openalex.org/W2118846262, https://openalex.org/W3198738851, https://openalex.org/W2566396342, https://openalex.org/W2110150994, https://openalex.org/W3012436983, https://openalex.org/W2103512536, https://openalex.org/W2725230000, https://openalex.org/W2129852031, https://openalex.org/W1995016187, https://openalex.org/W2126621628, https://openalex.org/W1969870555, https://openalex.org/W2284576719, https://openalex.org/W2788327314, https://openalex.org/W2237956683, https://openalex.org/W4382932063, https://openalex.org/W4283781398, https://openalex.org/W3206129759, https://openalex.org/W2012473911, https://openalex.org/W2915026237, https://openalex.org/W2123171788, https://openalex.org/W2464417828, https://openalex.org/W4385667404, https://openalex.org/W2563852803, https://openalex.org/W4229012181, https://openalex.org/W4225324547 |
| referenced_works_count | 37 |
| abstract_inverted_index.a | 13, 25, 31 |
| abstract_inverted_index.15 | 66 |
| abstract_inverted_index.We | 49 |
| abstract_inverted_index.as | 137 |
| abstract_inverted_index.at | 187 |
| abstract_inverted_index.by | 166 |
| abstract_inverted_index.in | 117, 198, 230 |
| abstract_inverted_index.is | 150, 181 |
| abstract_inverted_index.it | 36 |
| abstract_inverted_index.no | 151 |
| abstract_inverted_index.of | 16, 20, 27, 41, 185, 214 |
| abstract_inverted_index.on | 12, 55, 105 |
| abstract_inverted_index.to | 60, 159, 203 |
| abstract_inverted_index.we | 23 |
| abstract_inverted_index.221 | 92 |
| abstract_inverted_index.2nd | 39 |
| abstract_inverted_index.98% | 186 |
| abstract_inverted_index.The | 99, 189 |
| abstract_inverted_index.WHO | 168 |
| abstract_inverted_index.and | 34, 90, 121, 135, 155, 200, 205, 222 |
| abstract_inverted_index.are | 129 |
| abstract_inverted_index.for | 5, 65, 131, 146, 169, 175, 177, 227 |
| abstract_inverted_index.pp) | 110, 120 |
| abstract_inverted_index.set | 165 |
| abstract_inverted_index.the | 6, 17, 38, 42, 84, 161, 167, 183, 211, 231 |
| abstract_inverted_index.97%. | 188 |
| abstract_inverted_index.Here | 22 |
| abstract_inverted_index.MTBC | 58 |
| abstract_inverted_index.SOLO | 88, 112, 145, 154 |
| abstract_inverted_index.ahpC | 199 |
| abstract_inverted_index.also | 192 |
| abstract_inverted_index.drug | 2, 171 |
| abstract_inverted_index.from | 72 |
| abstract_inverted_index.more | 94, 141 |
| abstract_inverted_index.next | 216 |
| abstract_inverted_index.over | 56 |
| abstract_inverted_index.pp). | 126 |
| abstract_inverted_index.than | 97, 111, 144 |
| abstract_inverted_index.with | 69, 113, 157 |
| abstract_inverted_index.(+3.2 | 107 |
| abstract_inverted_index.(-1.0 | 119 |
| abstract_inverted_index.(-1.6 | 125 |
| abstract_inverted_index.(29%) | 93 |
| abstract_inverted_index.(98%) | 79 |
| abstract_inverted_index.(WHO) | 46 |
| abstract_inverted_index.MTBC. | 232 |
| abstract_inverted_index.Rapid | 0 |
| abstract_inverted_index.SOLO. | 98 |
| abstract_inverted_index.There | 149 |
| abstract_inverted_index.These | 208 |
| abstract_inverted_index.World | 43 |
| abstract_inverted_index.below | 182 |
| abstract_inverted_index.drugs | 68 |
| abstract_inverted_index.gains | 128 |
| abstract_inverted_index.other | 223 |
| abstract_inverted_index.these | 147 |
| abstract_inverted_index.total | 95 |
| abstract_inverted_index.train | 50 |
| abstract_inverted_index.using | 30, 83 |
| abstract_inverted_index.value | 124 |
| abstract_inverted_index.which | 178 |
| abstract_inverted_index.whole | 219 |
| abstract_inverted_index.(MTBC) | 10 |
| abstract_inverted_index.52,000 | 57 |
| abstract_inverted_index.Health | 44 |
| abstract_inverted_index.assays | 226 |
| abstract_inverted_index.binary | 62 |
| abstract_inverted_index.drugs. | 148 |
| abstract_inverted_index.except | 174 |
| abstract_inverted_index.genes. | 75 |
| abstract_inverted_index.genome | 220 |
| abstract_inverted_index.graded | 139 |
| abstract_inverted_index.grades | 91 |
| abstract_inverted_index.higher | 103 |
| abstract_inverted_index.inform | 210 |
| abstract_inverted_index.linked | 202 |
| abstract_inverted_index.method | 86 |
| abstract_inverted_index.models | 54 |
| abstract_inverted_index.relies | 11 |
| abstract_inverted_index.target | 162 |
| abstract_inverted_index.(a.k.a, | 87 |
| abstract_inverted_index.450/457 | 78 |
| abstract_inverted_index.against | 37 |
| abstract_inverted_index.average | 106, 115 |
| abstract_inverted_index.between | 153 |
| abstract_inverted_index.complex | 9 |
| abstract_inverted_index.detects | 77, 193 |
| abstract_inverted_index.edition | 40 |
| abstract_inverted_index.genetic | 18, 170 |
| abstract_inverted_index.highest | 130 |
| abstract_inverted_index.meeting | 160 |
| abstract_inverted_index.method) | 89 |
| abstract_inverted_index.points, | 109 |
| abstract_inverted_index.present | 24 |
| abstract_inverted_index.product | 163 |
| abstract_inverted_index.regards | 158 |
| abstract_inverted_index.results | 209 |
| abstract_inverted_index.smaller | 114 |
| abstract_inverted_index.testing | 4 |
| abstract_inverted_index.achieves | 102 |
| abstract_inverted_index.approach | 33 |
| abstract_inverted_index.existing | 85 |
| abstract_inverted_index.isolates | 59 |
| abstract_inverted_index.logistic | 52 |
| abstract_inverted_index.mutation | 47 |
| abstract_inverted_index.pipeline | 191 |
| abstract_inverted_index.positive | 122 |
| abstract_inverted_index.profiles | 164 |
| abstract_inverted_index.targeted | 215 |
| abstract_inverted_index.testing, | 173 |
| abstract_inverted_index.variants | 70, 81, 96, 143, 201 |
| abstract_inverted_index.associate | 61 |
| abstract_inverted_index.benchmark | 35 |
| abstract_inverted_index.candidate | 73 |
| abstract_inverted_index.catalogue | 26, 101 |
| abstract_inverted_index.continued | 212 |
| abstract_inverted_index.decreases | 116 |
| abstract_inverted_index.extracted | 71 |
| abstract_inverted_index.isoniazid | 194 |
| abstract_inverted_index.molecular | 225 |
| abstract_inverted_index.mutations | 29, 197 |
| abstract_inverted_index.threshold | 184 |
| abstract_inverted_index.Regression | 76 |
| abstract_inverted_index.catalogue. | 48 |
| abstract_inverted_index.commercial | 224 |
| abstract_inverted_index.diagnosing | 228 |
| abstract_inverted_index.difference | 152 |
| abstract_inverted_index.generation | 217 |
| abstract_inverted_index.identified | 82 |
| abstract_inverted_index.percentage | 108 |
| abstract_inverted_index.phenotypes | 64 |
| abstract_inverted_index.predictive | 123 |
| abstract_inverted_index.regression | 53, 138, 156, 179, 190 |
| abstract_inverted_index.resistance | 63, 74, 195, 229 |
| abstract_inverted_index.Sensitivity | 127 |
| abstract_inverted_index.bedaquiline | 204 |
| abstract_inverted_index.development | 213 |
| abstract_inverted_index.ethambutol, | 132 |
| abstract_inverted_index.ethionamide | 136 |
| abstract_inverted_index.resistance. | 21 |
| abstract_inverted_index.rifampicin, | 176 |
| abstract_inverted_index.sensitivity | 104 |
| abstract_inverted_index.sequencing, | 218, 221 |
| abstract_inverted_index.specificity | 118, 180 |
| abstract_inverted_index.Organisation | 45 |
| abstract_inverted_index.clofazimine, | 133 |
| abstract_inverted_index.compensatory | 196 |
| abstract_inverted_index.considerably | 140 |
| abstract_inverted_index.determinants | 19 |
| abstract_inverted_index.multivariate | 51 |
| abstract_inverted_index.tuberculosis | 8 |
| abstract_inverted_index.Mycobacterium | 7 |
| abstract_inverted_index.comprehensive | 14 |
| abstract_inverted_index.knowledgebase | 15 |
| abstract_inverted_index.streptomycin, | 134 |
| abstract_inverted_index.aminoglycoside | 206 |
| abstract_inverted_index.antitubercular | 67 |
| abstract_inverted_index.genotype-based | 1 |
| abstract_inverted_index.susceptibility | 3, 172 |
| abstract_inverted_index.regression-based | 32, 100 |
| abstract_inverted_index.hypersusceptibility. | 207 |
| abstract_inverted_index.resistance-associated | 28, 80, 142 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5056381174 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I4210087915 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5699999928474426 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.98783109 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |