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1
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Front Bioinform. 2024 Aug 9;4:1458237. doi: 10.3389/fbinf.2024.1458237. eCollection 2024.
2
Novel antimicrobial peptide discovery using machine learning and biophysical selection of minimal bacteriocin domains.利用机器学习和最小细菌素结构域的生物物理选择发现新型抗菌肽。
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Machine Learning Prediction of Antimicrobial Peptides.机器学习预测抗菌肽。
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Learning From Limited Data: Towards Best Practice Techniques for Antimicrobial Resistance Prediction From Whole Genome Sequencing Data.从有限数据中学习:从全基因组测序数据预测抗生素耐药性的最佳实践技术。
Front Cell Infect Microbiol. 2021 Feb 15;11:610348. doi: 10.3389/fcimb.2021.610348. eCollection 2021.
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Staphylococcal-Produced Bacteriocins and Antimicrobial Peptides: Their Potential as Alternative Treatments for Infections.葡萄球菌产生的细菌素和抗菌肽:它们作为感染替代治疗方法的潜力
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本文引用的文献

1
Deep-learning-enabled antibiotic discovery through molecular de-extinction.通过分子复活实现基于深度学习的抗生素发现。
Nat Biomed Eng. 2024 Jul;8(7):854-871. doi: 10.1038/s41551-024-01201-x. Epub 2024 Jun 11.
2
Discovery of antimicrobial peptides in the global microbiome with machine learning.利用机器学习在全球微生物组中发现抗菌肽。
Cell. 2024 Jul 11;187(14):3761-3778.e16. doi: 10.1016/j.cell.2024.05.013. Epub 2024 Jun 5.
3
Bacteriocin diversity, function, discovery and application as antimicrobials.细菌素的多样性、功能、发现及其作为抗菌剂的应用。
Nat Rev Microbiol. 2024 Sep;22(9):556-571. doi: 10.1038/s41579-024-01045-x. Epub 2024 May 10.
4
Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning.机器学习助力古老抗菌肽的分子复活。
Cell Host Microbe. 2023 Aug 9;31(8):1260-1274.e6. doi: 10.1016/j.chom.2023.07.001. Epub 2023 Jul 28.
5
Leveraging artificial intelligence in the fight against infectious diseases.利用人工智能对抗传染病。
Science. 2023 Jul 14;381(6654):164-170. doi: 10.1126/science.adh1114. Epub 2023 Jul 13.
6
Evolution of Resistance to Antibiotics: A Topic of Increasing Concern.抗生素耐药性的演变:一个日益受到关注的话题。
Antibiotics (Basel). 2023 Feb 4;12(2):332. doi: 10.3390/antibiotics12020332.
7
Mining for encrypted peptide antibiotics in the human proteome.在人类蛋白质组中挖掘加密的肽抗生素。
Nat Biomed Eng. 2022 Jan;6(1):67-75. doi: 10.1038/s41551-021-00801-1. Epub 2021 Nov 4.
8
Encouraging the Development of New Antibiotics: Are Financial Incentives the Right Way Forward? A Systematic Review and Case Study.鼓励新型抗生素的研发:经济激励措施是正确的前进方向吗?一项系统评价与案例研究。
Infect Drug Resist. 2021 Feb 5;14:415-434. doi: 10.2147/IDR.S287792. eCollection 2021.
9
PARGT: a software tool for predicting antimicrobial resistance in bacteria.PARGT:一种用于预测细菌对抗菌药物耐药性的软件工具。
Sci Rep. 2020 Jul 3;10(1):11033. doi: 10.1038/s41598-020-67949-9.
10
Insights into : A Review of Microbiological, Virulence, and Resistance Traits in a Threatening Nosocomial Pathogen.深入剖析:一种威胁性医院病原体的微生物学、毒力和耐药特性综述
Antibiotics (Basel). 2020 Mar 12;9(3):119. doi: 10.3390/antibiotics9030119.

Editorial: Machine learning approaches to antimicrobials: discovery and resistance.

作者信息

Broschat Shira L, Siu Shirley W I, de la Fuente-Nunez Cesar

机构信息

School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, United States.

Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, United States.

出版信息

Front Bioinform. 2024 Aug 9;4:1458237. doi: 10.3389/fbinf.2024.1458237. eCollection 2024.

DOI:10.3389/fbinf.2024.1458237
PMID:39184338
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11341447/
Abstract
摘要