Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae-Reference-Cited by-同舟云学术

Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae

Published:2018-01-11 Issue:1 Volume:8 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Nguyen Marcus,Brettin Thomas,Long S. Wesley^ORCID,Musser James M.,Olsen Randall J.,Olson Robert,Shukla Maulik,Stevens Rick L.,Xia Fangfang,Yoo Hyunseung,Davis James J.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41598-017-18972-w.pdf

Reference61 articles.

1. Chen, L., Todd, R., Kiehlbauch, J., Walters, M. & Kallen, A. Notes from the Field: Pan-Resistant New Delhi Metallo-Beta-Lactamase-Producing Klebsiella pneumoniae –” Washoe County, Nevada, 2016. MMWR Morb Mortal Wkly Rep 66 (2017).

2. Navon-Venezia, S., Kondratyeva, K. & Carattoli, A. Klebsiella pneumoniae: a major worldwide source and shuttle for antibiotic resistance. FEMS Microbiology Reviews 41, 252, https://doi.org/10.1093/femsre/fux013 (2017).

3. Long, S. W. et al. Population Genomic Analysis of 1,777 Extended-Spectrum Beta-Lactamase-Producing Klebsiella pneumoniae Isolates, Houston, Texas: Unexpected Abundance of Clonal Group 307. mBio 8, e00489–17, https://doi.org/10.1128/mBio.00489-17 (2017).

4. Snitkin, E. S. et al. Tracking a hospital outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome sequencing. Science translational medicine 4, 148ra116–148ra116, https://doi.org/10.1126/scitranslmed.3004129 (2012).

5. Endimiani, A. et al. Emergence of blakpc-containing Klebsiella pneumoniae in a long-term acute care hospital: a new challenge to our healthcare system. Journal of Antimicrobial Chemotherapy 64, 1102–1110, https://doi.org/10.1093/jac/dkp327 (2009).

Cited by 150 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring the synergy of artificial intelligence in microbiology: Advancements, challenges, and future prospects;Computational and Structural Biotechnology Reports;2024-12

2. Holistic understanding of trimethoprim resistance in Streptococcus pneumoniae using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning;mBio;2024-09-11

3. Reliable machine learning models in genomic medicine using conformal prediction;2024-09-10

4. Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra;mSystems;2024-08-16

5. Artificial intelligence applications in the diagnosis and treatment of bacterial infections;Frontiers in Microbiology;2024-08-06