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A pan-genome-based machine learning approach for predicting antimicrobial resistance activities of the Escherichia coli strains

机译:基于泛基因组的机器学习方法,用于预测大肠杆菌菌株的抗微生物活性

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Motivation: Antimicrobial resistance (AMR) is becoming a huge problem in both developed and developing countries, and identifying strains resistant or susceptible to certain antibiotics is essential in fighting against antibiotic-resistant pathogens. Whole-genome sequences have been collected for different microbial strains in order to identify crucial characteristics that allow certain strains to become resistant to antibiotics; however, a global inspection of the gene content responsible for AMR activities remains to be done.
机译:动机:抗微生物抗性(AMR)在发达国家和发展中国家成为一个巨大的问题,并且鉴定抗性或易受某些抗生素的菌株对抗抗生素抗性病原体是必不可少的。 针对不同的微生物菌株收集全基因组序列,以鉴定允许某些菌株对抗生素抵抗的关键特征; 然而,全球检查负责AMR活动的基因内容仍有待完成。

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