挖掘生物学以发现抗生素。
Mining biology for antibiotic discovery.
作者信息
de la Fuente-Nunez Cesar
机构信息
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, Pennsylvania, United States of America.
Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
出版信息
PLoS Biol. 2024 Nov 26;22(11):e3002946. doi: 10.1371/journal.pbio.3002946. eCollection 2024 Nov.
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.
抗生素耐药性的上升需要创新的解决方案。利用人工智能对生物学进行数字挖掘这一认识揭示了抗生素发现的新范式，为对抗超级细菌带来了希望。
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