Last Posted: Oct 07, 2019
- Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians.
Luo Yang et al. Nature communications 2019 Aug (1) 3765
- Machine Learning Predicts Accurately Mycobacterium tuberculosis Drug Resistance From Whole Genome Sequencing Data
Deelder W, et al. Front Genet, Sep 26, 2019.
- Resolving a clinical tuberculosis outbreak using palaeogenomic genome reconstruction methodologies.
Jones Rhys et al. Tuberculosis (Edinburgh, Scotland) 2019 Sep 101865
- Targeted Sequencing Workflows for Comprehensive Drug Resistance Profiling of Mycobacterium tuberculosis cultures using Illumina MiSeq and Nanopore MinION: Comparison of analytical and diagnostic performance, turnaround time and cost
Tafess K, bioRxiv, Sep 8, 2019.
- Tuberculosis drug discovery in the CRISPR era.
Rock Jeremy et al. PLoS pathogens 2019 Sep (9) e1007975
- Machine learning for clinical decision support in infectious diseases: A narrative review of current applications.
Peiffer-Smadja Nathan et al. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases 2019 Sep
- A novel Ancestral Beijing sublineage of Mycobacterium tuberculosis suggests the transition site to Modern Beijing sublineages.
Ajawatanawong Pravech et al. Scientific reports 2019 Sep (1) 13718
- A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis.
Harris Miriam et al. PloS one 2019 14(9) e0221339
- Comparing QuantiFERON-TB Gold Plus with other tests to diagnose Mycobacterium tuberculosis infection.
Venkatappa Thara K et al. Journal of clinical microbiology 2019 Aug
- The molecular clock of Mycobacterium tuberculosis.
Menardo Fabrizio et al. PLoS pathogens 2019 Sep (9) e1008067
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