Enhancing predictions of antimicrobial resistance of pathogens by expanding the potential resistance gene repertoire using a pan-genome-based feature selection …
Background Predicting which pathogens might exhibit antimicrobial resistance (AMR) based
on genomics data is one of the promising ways to swiftly and precisely identify AMR …
on genomics data is one of the promising ways to swiftly and precisely identify AMR …
Using bacterial pan-genome-based feature selection approach to improve the prediction of minimum inhibitory concentration (MIC)
Background: Predicting the resistance profiles of antimicrobial resistance (AMR) pathogens
is becoming more and more important in treating infectious diseases. Various attempts have …
is becoming more and more important in treating infectious diseases. Various attempts have …
A pan-genome-based machine learning approach for predicting antimicrobial resistance activities of the Escherichia coli strains
Motivation Antimicrobial resistance (AMR) is becoming a huge problem in both developed
and developing countries, and identifying strains resistant or susceptible to certain …
and developing countries, and identifying strains resistant or susceptible to certain …
[HTML][HTML] Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains
In current genomic research, the widely used methods for predicting antimicrobial resistance
(AMR) often rely on prior knowledge of known AMR genes or reference genomes. However …
(AMR) often rely on prior knowledge of known AMR genes or reference genomes. However …
[HTML][HTML] A Cross-Validated Feature Selection (CVFS) approach for extracting the most parsimonious feature sets and discovering potential antimicrobial resistance …
Understanding genes and their underlying mechanisms is critical in deciphering how
antimicrobial-resistant (AMR) bacteria withstand detrimental effects of antibiotic drugs. At the …
antimicrobial-resistant (AMR) bacteria withstand detrimental effects of antibiotic drugs. At the …
Parmap: A pan-genome-based computational framework for predicting antimicrobial resistance
X Li, J Lin, Y Hu, J Zhou - Frontiers in microbiology, 2020 - frontiersin.org
Antimicrobial resistance (AMR) has emerged as one of the most urgent global threats to
public health. Accurate detection of AMR phenotypes is critical for reducing the spread of …
public health. Accurate detection of AMR phenotypes is critical for reducing the spread of …
A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains
Recently, the frequency of observing bacterial strains without known genetic components
underlying phenotypic resistance to antibiotics has increased. There are several strains of …
underlying phenotypic resistance to antibiotics has increased. There are several strains of …
[HTML][HTML] PanKA: Leveraging population pangenome to predict antibiotic resistance
Machine learning has the potential to be a powerful tool in the fight against antimicrobial
resistance (AMR), a critical global health issue. Machine learning can identify resistance …
resistance (AMR), a critical global health issue. Machine learning can identify resistance …
Antimicrobial resistance prediction for gram-negative bacteria via game theory-based feature evaluation
AS Chowdhury, DR Call, SL Broschat - Scientific reports, 2019 - nature.com
The increasing prevalence of antimicrobial-resistant bacteria drives the need for advanced
methods to identify antimicrobial-resistance (AMR) genes in bacterial pathogens. With the …
methods to identify antimicrobial-resistance (AMR) genes in bacterial pathogens. With the …
Predicting antimicrobial resistance using conserved genes
A growing number of studies are using machine learning models to accurately predict
antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these …
antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these …