Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility
Antibiotic resistance is an imminent threat to global health. Patient treatment regimens are often selected based on results from standardized antibiotic susceptibility testing (AST) in the clinical microbiology lab, but these in vitro
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Society for Microbiology
2021-08-01
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| Series: | mSphere |
| Online Access: | https://journals.asm.org/doi/10.1128/mSphere.00443-21 |
| _version_ | 1818882591512592384 |
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| author | Anand V. Sastry Nicholas Dillon Amitesh Anand Saugat Poudel Ying Hefner Sibei Xu Richard Szubin Adam M. Feist Victor Nizet Bernhard Palsson |
| author_facet | Anand V. Sastry Nicholas Dillon Amitesh Anand Saugat Poudel Ying Hefner Sibei Xu Richard Szubin Adam M. Feist Victor Nizet Bernhard Palsson |
| author_sort | Anand V. Sastry |
| collection | DOAJ |
| description | Antibiotic resistance is an imminent threat to global health. Patient treatment regimens are often selected based on results from standardized antibiotic susceptibility testing (AST) in the clinical microbiology lab, but these
in vitro |
| first_indexed | 2024-12-19T15:20:12Z |
| format | Article |
| id | doaj.art-220d392333e94177905596f8b6ded2e1 |
| institution | Directory Open Access Journal |
| issn | 2379-5042 |
| language | English |
| last_indexed | 2024-12-19T15:20:12Z |
| publishDate | 2021-08-01 |
| publisher | American Society for Microbiology |
| record_format | Article |
| series | mSphere |
| spelling | doaj.art-220d392333e94177905596f8b6ded2e12022-12-21T20:16:01ZengAmerican Society for MicrobiologymSphere2379-50422021-08-016410.1128/mSphere.00443-21Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic SusceptibilityAnand V. Sastry0Nicholas Dillon1https://orcid.org/0000-0003-2351-0700Amitesh Anand2Saugat Poudel3Ying Hefner4Sibei Xu5Richard Szubin6Adam M. Feist7Victor Nizet8Bernhard Palsson9https://orcid.org/0000-0003-2357-6785Department of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Pediatrics, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USADepartment of Pediatrics, University of California—San Diego, La Jolla, California, USADepartment of Bioengineering, University of California—San Diego, La Jolla, California, USAAntibiotic resistance is an imminent threat to global health. Patient treatment regimens are often selected based on results from standardized antibiotic susceptibility testing (AST) in the clinical microbiology lab, but these in vitrohttps://journals.asm.org/doi/10.1128/mSphere.00443-21 |
| spellingShingle | Anand V. Sastry Nicholas Dillon Amitesh Anand Saugat Poudel Ying Hefner Sibei Xu Richard Szubin Adam M. Feist Victor Nizet Bernhard Palsson Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility mSphere |
| title | Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility |
| title_full | Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility |
| title_fullStr | Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility |
| title_full_unstemmed | Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility |
| title_short | Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility |
| title_sort | machine learning of bacterial transcriptomes reveals responses underlying differential antibiotic susceptibility |
| url | https://journals.asm.org/doi/10.1128/mSphere.00443-21 |
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