Mining biology for antibiotic discovery.

Journal: PLoS biology

PMID: 39591471

Abstract

The rise of antibiotic resistance calls for innovative solutions. The realization that biology can be mined digitally using artificial intelligence has revealed a new paradigm for antibiotic discovery, offering hope in the fight against superbugs.

Authors

Cesar de la Fuente-Nunez

Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Keywords

Anti-Bacterial Agents Artificial Intelligence Data Mining Drug Discovery Drug Resistance, Bacterial Drug Resistance, Microbial Humans

External Resources

View on PubMed Access via DOI PubMed (39591471)

Mining biology for antibiotic discovery.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals