Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing

The Sequence Alignment/Map format and SAMtools

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Stampy: A statistical algorithm for sensitive and fast mapping of Illumina sequence reads

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Feasibility, diagnostic accuracy, and effectiveness of decentralised use of the Xpert MTB/RIF test for diagnosis of tuberculosis and multidrug resistance: a multicentre implementation study

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De novo assembly and genotyping of variants using colored de Bruijn graphs

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Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study

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Evolution and transmission of drug-resistant tuberculosis in a Russian population

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Same-Day Diagnostic and Surveillance Data for Tuberculosis via Whole-Genome Sequencing of Direct Respiratory Samples

Votintseva, A. A., Bradley, P., Pankhurst, L. J., Elías, C. D. O., Loose, M., Nilgiriwala, K. S., Chatterjee, A., Smith, E. G., Sanderson, N. D., Walker, T. M., et al. (2017) · Journal of Clinical Microbiology · doi:10.1128/jcm.02483-16 · Cited by 344

A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis

Miotto, P., Tessema, B., Tagliani, E., Chindelevitch, L., Starks, A. M., Emerson, C., Hanna, D. L., Kim, P. S., Liwski, R., Zignol, M., et al. (2017) · European Respiratory Journal · doi:10.1183/13993003.01354-2017 · Cited by 343

Ethambutol resistance in Mycobacterium tuberculosis: critical role of embB mutations

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Rapid, comprehensive, and affordable mycobacterial diagnosis with whole-genome sequencing: a prospective study

Pankhurst, L. J., Elías, C. D. O., Votintseva, A. A., Walker, T. M., Cole, K., Davies, J., Fermont, J. M., Gascoyne‐Binzi, D., Kohl, T. A., Kong, C., et al. (2015) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(15)00466-x · Cited by 327

Contemporary Concise Review 2018: Respiratory infections and tuberculosis

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Contrasting approaches to genome-wide association studies impact the detection of resistance mechanisms in Staphylococcus aureusPreprint

Wheeler, N. E., Reuter, S., Chewapreecha, C., Lees, J. A., Blane, B., Horner, C., Enoch, D., Brown, N. M., Török, M. E., Aanensen, D. M., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/758144 · Cited by 8

A data compendium of Mycobacterium tuberculosis antibiotic resistancePreprint

Brankin, A. E., & Malone, K. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.14.460274 · Cited by 7

Heteroresistance in tuberculosis: are we missing drug-resistant bacteria hiding in plain sight?

Park, M., Satta, G., & Haldar, P. (2024) · Thorax · doi:10.1136/thorax-2024-221409 · Cited by 6

Evolution, Phylogenetics, and Phylogeography of Mycobacterium tuberculosis complex

Sola, C., Владиславович, М. И., Sahal, M. R., La, K., Senelle, G., Guyeux, C., Refrégier, G., & Cambau, E. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-28818-0.00025-2 · Cited by 6

TBtypeR: Sensitive detection and sublineage classification of Mycobacterium tuberculosis complex mixed-strain infections

Munro, J. E., Coussens, A. K., & Bahlo, M. (2025) · Communications Biology · doi:10.1038/s42003-025-07705-9 · Cited by 6

A comprehensive evaluation of a novel targeted-sequencing workflow for Mycobacterium species identification and anti-tuberculosis drug-resistance detection

Ou, X., Pei, S., Li, H., Qin, Z., Anthony, R. M., Wang, J., Song, Z., Xing, R., Zhang, L., Teng, C., et al. (2025) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2025.1584237 · Cited by 6

Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for Staphylococcus aureus via metagenomic sequencing

Jia, X., Xiong, Y., Xu, Y., Chen, F., Han, P., Qu, J., He, Q., & Rao, G. (2025) · Microbiology Spectrum · doi:10.1128/spectrum.00556-25 · Cited by 6

Application of Next-Generation Sequencing in Public Health Epidemiology and Outbreak Investigation

Tran, A., & Rowlinson, M. (2019) · Advances in Molecular Pathology · doi:10.1016/j.yamp.2019.07.007 · Cited by 6

Complexities and benefits of adopting next-generation sequencing-based tuberculosis diagnostics: a qualitative study among stakeholders in low and high-income countries

Lapierre, S. G., Nouvet, É., Boutin, C.-A., Rabodoarivelo, M. S., Mahboob, O., Smith, M. J., & Rakotosamimanana, N. (2023) · BMJ Open · doi:10.1136/bmjopen-2022-066651 · Cited by 6

Mycobacterium tuberculosis complex whole-genome sequencing in New York State: Implementation of a reduced phenotypic drug susceptibility testing algorithm

Shea, J., Halse, T. A., Modestil, H., Kearns, C., Fowler, R. C., Costa-Carter, C.-A. D., Siemetzki-Kapoor, U., Leisner, M., Lapierre, P., Kohlerschmidt, D. J., et al. (2023) · Tuberculosis · doi:10.1016/j.tube.2023.102380 · Cited by 6

Mycoplasma hominis infections in solid organ transplant recipients: Clinical characteristics, treatment outcomes, and comparison of phenotypic and genotypic susceptibility profiles

Chang, S. Y., Price, T. K., Beaird, O. E., Gaynor, P. T., Schaenman, J. M. D., Carlson, M., Kubak, B., Yang, S., & Multani, A. (2022) · Transplant Infectious Disease · doi:10.1111/tid.13822 · Cited by 6

MycoVarP: Mycobacterium Variant and Drug Resistance Prediction Pipeline for Whole-Genome Sequence Data Analysis

Swargam, S., Kumari, I., Kumar, A., Pradhan, D., Alam, A., Singh, H., Jain, A., Devi, K. R., Trivedi, V., Sarma, J., et al. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2021.805338 · Cited by 6

Evaluation of the broth microdilution plate methodology for susceptibility testing of Mycobacterium tuberculosis in Peru

Puyén, Z. M., Santos-Lázaro, D., Vigo, A. N., Coronel, J., Alarcón, M. J., Cotrina, V. V., & Moore, D. (2022) · BMC Infectious Diseases · doi:10.1186/s12879-022-07677-9 · Cited by 6

How quickly can we predict trimethoprim resistance using alchemical free energy methods?

Fowler, P. W. (2020) · Interface Focus · doi:10.1098/rsfs.2019.0141 · Cited by 6

Bridging the TB data gap: in silico extraction of rifampicin-resistant tuberculosis diagnostic test results from whole genome sequence data

Ng, K. C. S., Ngabonziza, J. C. S., Lempens, P., de Jong, B. C., van Leth, F., & Meehan, C. J. (2019) · PeerJ · doi:10.7717/peerj.7564 · Cited by 6

Rapid Pyrazinamide Drug Susceptibility Testing using a Closed-Tube PCR Assay of the Entire pncA gene

Whitfield, M. G., Marras, S. A. E., Warren, R. M., Rie, A. V., Rice, J., Wangh, L. J., & Kreiswirth, B. N. (2020) · Scientific Reports · doi:10.1038/s41598-020-61286-7 · Cited by 6

Whole-genome sequencing reveals transmission pattern and drug resistance of Mycobacterium tuberculosis intra- or inter-hosts

Ding, F., Liu, W., Wu, C., Zhang, W., Chen, S., Lai, W., Qu, J., Lin, Q., Lu, S., & Qu, J. (2025) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2024.1488547 · Cited by 5

Impact of sublineage diversity on intrinsic susceptibility of Beijing genotype Mycobacterium tuberculosis

Li, H., Zhang, G., Ma, Z., Guo, H., Shang, Y., Yao, C., Li, S., Pang, Y., & Pan, J. (2025) · Annals of Clinical Microbiology and Antimicrobials · doi:10.1186/s12941-025-00807-6 · Cited by 5

How Artificial Intelligence Assists in Overcoming Drug Resistance?

Ndikuryayo, F., Gong, X., Hao, G., & Yang, W. (2025) · Medicinal Research Reviews · doi:10.1002/med.70002 · Cited by 5

A Persistent Tuberculosis Outbreak in the UK Is Characterized by Hydrophobic fadB4 -Deficient Mycobacterium tuberculosis That Replicates Rapidly in Macrophages

Farzand, R., Haigh, R., Monk, P., Haldar, P., Patel, H., Pareek, M., Verma, R., Barer, M. R., Woltmann, G., Ahyow, L., et al. (2022) · mBio · doi:10.1128/mbio.02656-22 · Cited by 5

An integrated method for targeted Oxford Nanopore sequencing and automated bioinformatics for the simultaneous detection of bacteria, fungi, and ARG

Kuruwa, S., Zade, A., Shah, S., Rameez, M. J., Lad, S. B., Chande, C., Joshi, A., Hirani, N., Nikam, C., Bhattacharya, S., et al. (2024) · Journal of Applied Microbiology · doi:10.1093/jambio/lxae037 · Cited by 5

Genetic diversity and transmission pattern of multidrug-resistant tuberculosis based on whole-genome sequencing in Wuhan, China

Wei, L., Chen, J., Deng, Z., Zhang, Z., Zhang, Z., & Duan, Q. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1442987 · Cited by 5

Next-Generation Sequencing Approaches to Predicting Antimicrobial Susceptibility Testing Results

Yee, R., & Simner, P. J. (2019) · Advances in Molecular Pathology · doi:10.1016/j.yamp.2019.07.008 · Cited by 5

Die neuen WHO-Empfehlungen für schnelle Diagnostik und Therapie resistenter Tuberkulose in Deutschland, Österreich und der Schweiz

Otto-Knapp, R., Knappik, M., Häcker, B., Starzacher, K., Bauer, T. T., Lange, C. G., Maurer, F. P., Schaberg, T., & Günther, G. (2020) · Pneumologie · doi:10.1055/a-1266-5207 · Cited by 5

Profiling and identification of novel rpoB mutations in rifampicin-resistant Mycobacterium tuberculosis clinical isolates from Pakistan

Qadir, M., Tahseen, S., McHugh, T. D., Hussain, A., Masood, F., Ahmed, N., & Faryal, R. (2021) · Journal of Infection and Chemotherapy · doi:10.1016/j.jiac.2021.06.020 · Cited by 5

The crucial need for tuberculosis translational research in the time of COVID-19

Loh, F. K., Thong, P. M., & Ong, C. W. M. (2022) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(22)00099-6 · Cited by 5

Characterization of Polymorphisms Associated with Multidrug-Resistant Tuberculosis by Whole Genomic Sequencing: A Preliminary Report from Mexico

Zenteno‐Cuevas, R., Fernandez, E., Viveros, D., Madrazo-Moya, C. F., Cancino‐Muñoz, I., Comas, I., González-Covarrubias, V., Barbosa-Amezcua, M., & Cuevas-Córdoba, B. (2019) · Microbial Drug Resistance · doi:10.1089/mdr.2019.0054 · Cited by 5

Combination of Xpert MTB/RIF and MTBDRplus for Diagnosing Tuberculosis in a Chinese District

Lv, C., Wu, J., Pierre-Audigier, C., Lu, L., Emane, A. K. A., Takiff, H. E., Xu, Y., Wang, J., Gicquel, B., & Liu, S. (2020) · Medical Science Monitor · doi:10.12659/msm.923508 · Cited by 5

DNA Thermo-Protection Facilitates Whole Genome Sequencing of Mycobacteria Direct from Clinical Samples by the Nanopore PlatformPreprint

George, S. A., Xu, Y., Rodger, G., Morgan, M. R., Sanderson, N. D., Hoosdally, S., Thulborn, S., Robinson, E., Rathod, P., Walker, A. S., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.05.026864 · Cited by 5

Characterising the performance of an antibiotic resistance prediction tool, gnomonicus, using a diverse testset of 2,663 Mycobacterium tuberculosis samplesPreprint

Westhead, J., Baker, C. S., Brouard, M. J., Colpus, M., Constantinides, B., Hall, A., Knaggs, J., Alves, M. L., Spies, R., Thai, H., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.08.622466 · Cited by 5

Diagnostic algorithms for tuberculosis in Europe: insights from the European Reference Laboratory Network for Tuberculosis (ERLTB-Net)

Saluzzo, F., Cabibbe, A. M., Anthony, R. M., Aubry, A., Drobniewski, F. A., Holicka, Y., Lillebæk, T., Macedo, R., Mansjö, M., Szél, V., et al. (2025) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2025.101516 · Cited by 4

Research progress on the current status of respiratory pathogen infections and their detection methods

Zhu, F., Peng, M., Chen, A., & Zhu, Q.-Y. (2026) · Frontiers in Microbiology · doi:10.3389/fmicb.2026.1712752 · Cited by 5

A comparison of phenotypic and WGS drug susceptibility testing in Mycobacterium tuberculosis isolates from the Republic of Korea

Lee, S. H., Ferran, E., Witney, A. A., Ryu, S., Kang, H., Storey, N., McHugh, T. D., & Satta, G. (2023) · JAC-Antimicrobial Resistance · doi:10.1093/jacamr/dlad056 · Cited by 4

Unveiling the complexity of rifampicin drug susceptibility testing in Mycobacterium tuberculosis: comparative analysis with next-generation sequencing

Qadir, M., Khan, M. T., Khan, S. A., Akram, M., Canseco, J. O., Faryal, R., Wei, D. Q., & Tahseen, S. (2024) · Journal of Medical Microbiology · doi:10.1099/jmm.0.001884 · Cited by 4

Mycobacterium tuberculosis uses intrinsically disordered, fast evolving proteins to interact with conserved host factors

Pozzoli, U., Forni, D., Arrigoni, F., Cagliani, R., GIOIA, L. D., & Sironi, M. (2025) · Genome biology · doi:10.1186/s13059-025-03854-6 · Cited by 4

Bringing tuberculosis genomics to the clinic: development and validation of a comprehensive pipeline to predict antimicrobial susceptibility from genomic data, accredited to ISO standards

Horan, K., Viberg, L. T., Ballard, S. A., Globan, M., Wirth, W., Bond, K. A., Webb, J. R., Dorji, T., Williamson, D. A., Sait, M. L., et al. (2025) · The Lancet Digital Health · doi:10.1016/j.landig.2025.100939 · Cited by 4

Molecular diagnostic tests for isoniazid-resistant tuberculosis: a scoping review

Nguyen, M., MacLean, E. L.-H., Zhang, X., Georghiou, S. B., Xia, H., Beardsley, J., Sheel, M., Nguyen, T.-A. T., Marais, B. J., & Fox, G. J. (2026) · The Lancet Microbe · doi:10.1016/j.lanmic.2026.101362 · Cited by 4

Case Report: Disseminated, rifampicin resistant Mycobacterium bovis (BCG) infection in an immunocompromised child

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Galaxy ASIST: A web-based platform for mapping and assessment of global standards of antimicrobial susceptibility: A case study in Acinetobacter baumannii genomes

Sharma, T., Kumar, R., Kalra, J. S., Singh, S., Bhalla, G. S., & Bhardwaj, A. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.1041847 · Cited by 4

Introduction to Tuberculosis: Integrated Studies for a Complex Disease

Rezaei, N., Hosseini, N., & Saghazadeh, A. (2023) · Integrated science · doi:10.1007/978-3-031-15955-8_1 · Cited by 4

Genetic factors associated with acquired phenotypic drug resistance and its compensatory evolution during tuberculosis treatment

Zhang, G., Sun, X., Fleming, J., Ran, F., Luo, J., Chen, H., Ju, H., Wang, Z., Zhao, H., Wang, C., et al. (2024) · Clinical Microbiology and Infection · doi:10.1016/j.cmi.2024.01.016 · Cited by 4

Universal Lineage-Independent Markers of Multidrug Resistance in Mycobacterium tuberculosis

Hlanze, H., Mutshembele, A., & Reva, O. N. (2024) · Microorganisms · doi:10.3390/microorganisms12071340 · Cited by 4

Drugs against Mycobacterium tuberculosis

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Chapter 11: Tuberculosis contact investigation and outbreak management

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Diversity and novel mutations in membrane transporters ofMycobacterium tuberculosis

Khan, M. T., Khan, T. A., Ahmad, I., Muhammad, S., & Wei, D. (2022) · Briefings in Functional Genomics · doi:10.1093/bfgp/elac018 · Cited by 4

The case for including microbial sequences in the electronic health record

Sintchenko, V., & Coiera, E. W. (2023) · Nature Medicine · doi:10.1038/s41591-022-02157-8 · Cited by 4

Highly Sensitive Detection of Complicated Mutations of Drug Resistance in Mycobacterium tuberculosis Using a Simple, Accurate, Rapid, and Low‐Cost Tailored‐Design Competitive Wild‐Type Blocking Assay

Yan, M., Zhao, Z., Wu, T., Liu, T., Xu, G., Xu, H. Y., & Ying, B. (2023) · Small Methods · doi:10.1002/smtd.202201322 · Cited by 4

Clinical Evaluation of the XDR-LFC Assay for the Molecular Detection of Isoniazid, Rifampin, Fluoroquinolone, Kanamycin, Capreomycin, and Amikacin Drug Resistance in a Prospective Cohort

Syed, R. R., Catanzaro, D. G., Colman, R. E., Cooney, C. G., Linger, Y., Kukhtin, A. V., Holmberg, R. C., Norville, R., Crudu, V., Ciobanu, N., et al. (2023) · Journal of Clinical Microbiology · doi:10.1128/jcm.01478-22 · Cited by 4

Co-resistance to isoniazid and second-line anti-tuberculosis drugs in isoniazid-resistant tuberculosis at a tertiary care hospital in Thailand

Prommi, A., Wongjarit, K., Petsong, S., Somsukpiroh, U., Faksri, K., Kawkitinarong, K., Payungporn, S., & Rotcheewaphan, S. (2024) · Microbiology Spectrum · doi:10.1128/spectrum.03462-23 · Cited by 4

The 2021 WHO Catalogue of Mycobacterium Tuberculosis Complex Mutations Associated with Drug Resistance: A New Global Standard for Molecular DiagnosticsPreprint

Walker, T. M., Miotto, P., Köser, C. U., Fowler, P. W., Knaggs, J., Iqbal, Z., Hunt, M., Chindelevitch, L., Farhat, M. R., Cirillo, D. M., et al. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3923444 · Cited by 4

A chemical-genetic map of the pathways controlling drug potency in Mycobacterium tuberculosisPreprint

Li, S., Poulton, N. C., Chang, J. S., Azadian, Z. A., DeJesus, M. A., Ruecker, N., Zimmerman, M. D., Eckartt, K. A., Bosch, B., Engelhart, C. A., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.27.469863 · Cited by 4

Predicting MmpR-based bedaquiline resistance using sequence- and structure-based featuresPreprint

Rivière, E., Safarpour, M., Meysman, P., Cuypers, B., Meehan, C. J., Laukens, K., & Rie, A. V. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.19.521152 · Cited by 3

Evaluation of the Roche cobas MTB and MTB-RIF/INH for detecting Mycobacterium tuberculosis complex and resistance to isoniazid and rifampicin: A prospective, multicenter diagnostic accuracy study

Hsueh, S.-C., Chen, C., Lin, C.-R., Lin, H.-H., Lee, T.-F., Tseng, K.-H., Chu, H.-W., Lee, C.-L., Hsu, W.-Y., Huang, Y., et al. (2025) · International Journal of Antimicrobial Agents · doi:10.1016/j.ijantimicag.2025.107605 · Cited by 3

Bacterial Systematic Genetics and Integrated Multi-Omics: Beyond Static Genomics Toward Predictive Models

Sakaguchi, T., Irifune, Y., Kamada, R., & Sakaguchi, K. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26199326 · Cited by 7

Characteristic exploration of Mycobacterium tuberculosis isolated from patients with linezolid-treated multidrug-resistant tuberculosis

Kim, Y., Lee, D., Bae, J., Jung, J., Jeon, H., Chung, M., Park, J., Ahn, K., Mun, J.-W., Jang, Y., et al. (2025) · European Journal of Clinical Microbiology & Infectious Diseases · doi:10.1007/s10096-025-05319-x · Cited by 3

Characterizing the performance of an antibiotic resistance prediction tool, gnomonicus, using a diverse test set of 2,663 Mycobacterium tuberculosis samples

Westhead, J., Baker, C. S., Brouard, M. J., Colpus, M., Constantinides, B., Hall, A., Knaggs, J., Alves, M. L., Spies, R., Thai, H., et al. (2025) · Microbial Genomics · doi:10.1099/mgen.0.001592 · Cited by 3

Phenotypic and genotypic characterization of Mycobacterium tuberculosis pyrazinamide resistance—India, 2018–2020

Tamilzhalagan, S., Justin, E. S., Selvaraj, A., Venkateswaran, K., Sivakumar, A. K., Chittibabu, S., McLaughlin, H. P., Moonan, P. K., Smith, J. P., Sakthi, S., et al. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1515627 · Cited by 3

Enhancing diagnostic efficiency of pyrazinamide resistance in Mycobacterium tuberculosis via modified MGIT assay and genotypic correlation

Rajendran, A., Refaya, A. K., Subramanyam, B., Karunaianantham, R., Ravikumar, D., Haribabu, H., Gopalaswamy, R., Golla, R., Senthildevi, V., Sivaramakrishnan, G. N., et al. (2025) · Current Research in Microbial Sciences · doi:10.1016/j.crmicr.2025.100462 · Cited by 3

Application of engineered CRISPR/Cas12a variants with altered protospacer adjacent motif specificities for the detection of isoniazid resistance mutations in Mycobacterium tuberculosis

Liu, P., Zhang, J., Gong, Y., Liu, W., Xiao, G., Liang, J. B., Wang, X., Bi, J., & Zhang, G. (2025) · Microbiology Spectrum · doi:10.1128/spectrum.00165-25 · Cited by 3

Identification and Characterization of Mycobacterial Species Using Whole-Genome Sequences

Riojas, M. A., Frank, A. M., Greenfield, S. R., King, S. P., Meehan, C. J., Strong, M., Wattam, A. R., & Hazbón, M. H. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1460-0_19 · Cited by 3

Utilization of whole genome sequencing for resolution of discrepant Mycobacterium tuberculosis drug susceptibility results: A case report

Realegeno, S. E., Adeyiga, O. B., Winston, D. J., Beaird, O. E., Garner, O. B., & Yang, S. (2021) · IDCases · doi:10.1016/j.idcr.2021.e01308 · Cited by 3

Quantitative 1 H Nuclear Magnetic Resonance Assay for the Rapid Detection of Pyrazinamide Resistance in Mycobacterium tuberculosis from Sputum Samples

Lopez, J. M., Zimic, M., Vallejos-Sánchez, K., Sevilla, D., Quispe-Carbajal, M., Roncal, E., Rodríguez, J., Rodríguez, J., Antiparra, R., Arteaga, H., et al. (2023) · Journal of Clinical Microbiology · doi:10.1128/jcm.01522-22 · Cited by 3

Ability of the MeltPro MTB/PZA Assay to Detect Susceptibility to Pyrazinamide in Rifampin-Resistant Tuberculosis Patients

Li, R., Li, Y., Chen, X., Jia, L., Yu, H., Huang, Y., Wu, Q., Xiao, M., Ge, S., Zhang, Y., et al. (2023) · Microbiology Spectrum · doi:10.1128/spectrum.04836-22 · Cited by 3

Droplet based whole genome amplification for sequencing minute amounts of purified Mycobacterium tuberculosis DNA

Dippenaar, A., Ismail, N. A., Heupink, T. H., Grobbelaar, M., Loubser, J., Rie, A. V., & Warren, R. M. (2024) · Scientific Reports · doi:10.1038/s41598-024-60545-1 · Cited by 3

Pan-lineage Mycobacterium tuberculosis reference genome for enhanced molecular diagnosis

Bahk, K., Sung, J., Seki, M., Kim, K., Kim, J., Choi, H., Whang, J., & Mitarai, S. (2024) · DNA Research · doi:10.1093/dnares/dsae023 · Cited by 3

Identification of inflammatory protein biomarkers for predicting the different subtype of adult with tuberculosis: an Olink proteomic study

Song, Y., Abuduaini, B., Yang, X., Zhang, J., Wang, G., & Lu, X. (2025) · Inflammation Research · doi:10.1007/s00011-025-02020-9 · Cited by 3

Data types and resources

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Using Genomics to Understand the Epidemiology of Infectious Diseases in the Northern Territory of Australia

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A rare case of disseminated genitourinary tract tuberculosis complicated by emphysematous prostatitis and seminal vesicle abscess

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