Cargando…
Evaluation of Machine Learning Models for Predicting Antimicrobial Resistance of Actinobacillus pleuropneumoniae From Whole Genome Sequences
Antimicrobial resistance (AMR) is becoming a huge problem in countries all over the world, and new approaches to identifying strains resistant or susceptible to certain antibiotics are essential in fighting against antibiotic-resistant pathogens. Genotype-based machine learning methods showed great...
Autores principales: | Liu, Zhichang, Deng, Dun, Lu, Huijie, Sun, Jian, Lv, Luchao, Li, Shuhong, Peng, Guanghui, Ma, Xianyong, Li, Jiazhou, Li, Zhenming, Rong, Ting, Wang, Gang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016212/ https://www.ncbi.nlm.nih.gov/pubmed/32117101 http://dx.doi.org/10.3389/fmicb.2020.00048 |
Ejemplares similares
-
Whole Genome Sequencing for Surveillance of Antimicrobial Resistance in Actinobacillus pleuropneumoniae
por: Bossé, Janine T., et al.
Publicado: (2017) -
The SapA Protein Is Involved in Resistance to Antimicrobial Peptide PR-39 and Virulence of Actinobacillus pleuropneumoniae
por: Xie, Fang, et al.
Publicado: (2017) -
Global Effects of Catecholamines on Actinobacillus pleuropneumoniae Gene Expression
por: Li, Lu, et al.
Publicado: (2012) -
Actinobacillus pleuropneumoniae Interaction With Swine Endothelial Cells
por: Plasencia-Muñoz, Berenice, et al.
Publicado: (2020) -
Novel DNA Markers for Identification of Actinobacillus pleuropneumoniae
por: Srijuntongsiri, Gun, et al.
Publicado: (2022)