Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Su...
Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility
About this item
Full title
Author / Creator
Publisher
United States: American Society for Microbiology
Journal title
Language
English
Formats
Publication information
Publisher
United States: American Society for Microbiology
Subjects
More information
Scope and Contents
Contents
antibiotic susceptibility testing often fails to accurately predict
drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia co...
Alternative Titles
Full title
Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_220d392333e94177905596f8b6ded2e1
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_220d392333e94177905596f8b6ded2e1
Other Identifiers
ISSN
2379-5042
E-ISSN
2379-5042
DOI
10.1128/mSphere.00443-21
