The advantage of intergenic regions as genomic features for machine-learning-based host attribution of <i>Salmonella</i> Typhimurium from the USA.

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第一作者： Antonia,Chalka

第一单位： The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK.

作者： Antonia,Chalka ^[1] ; Tim J,Dallman ^[2] ; Prerna,Vohra ^[1] ; Mark P,Stevens ^[1] ; David L,Gally ^[1]

作者单位： The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, UK. ^[1] Institute for Risk Assessment Sciences (IRAS), University of Utrecht, Heidelberglaan, Utrecht, Netherlands. ^[2]

关键词 Salmonella Typhimurium host prediction intergenic regions machine learning phylogeny random forest

主题词动物(Animals);牛(Cattle);人类(Humans);猪(Swine);鼠伤寒沙门菌(Salmonella typhimurium);沙门菌感染, 动物(Salmonella Infections, Animal);种系发生(Phylogeny);DNA, 基因间(DNA, Intergenic);基因组, 细菌(Genome, Bacterial);基因组学(Genomics);哺乳动物(Mammals)

DOI 10.1099/mgen.0.001116

PMID 37843883

发布时间 2023-11-11

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Microbial genomics

2023年9卷10期

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The advantage of intergenic regions as genomic features for machine-learning-based host attribution of <i>Salmonella</i> Typhimurium from the USA.

Microbial genomics

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The advantage of intergenic regions as genomic features for machine-learning-based host attribution of <i>Salmonella</i> Typhimurium from the USA.

Microbial genomics

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Microbial genomics

相关期刊

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