AIMC Topic: Genes, Bacterial
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Synergistic effect of horizontal transfer of antibiotic resistance genes between bacteria exposed to microplastics and per/polyfluoroalkyl substances: An explanation from theoretical methods.
Journal of hazardous materials
Apr 8, 2025
Microplastics (MPs) and per/polyfluoroalkyl substances (PFASs), as emerging pollutants widely present in aquatic environments, pose a significant threat to human health through the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs)....
A framework predicting removal efficacy of antibiotic resistance genes during disinfection processes with machine learning.
Journal of hazardous materials
Apr 3, 2025
Disinfection has been applied widely for the removal of antibiotic resistance genes (ARGs) to curb the spread of antibiotic resistance. Quantitative polymerase chain reaction (qPCR) is the most used method to quantify the damage of DNA thus calculati...
DRAMMA: a multifaceted machine learning approach for novel antimicrobial resistance gene detection in metagenomic data.
Microbiome
Mar 7, 2025
BACKGROUND: Antibiotics are essential for medical procedures, food security, and public health. However, ill-advised usage leads to increased pathogen resistance to antimicrobial substances, posing a threat of fatal infections and limiting the benefi...
Phenotypic antibiotic resistance prediction using antibiotic resistance genes and machine learning models in Mannheimia haemolytica.
Veterinary microbiology
Jan 8, 2025
Mannheimia haemolytica is one of the most common causative agents of bovine respiratory disease (BRD); however, antibiotic resistance in this species is increasing, making treatment more difficult. Integrative-conjugative elements (ICE), a subset of ...
Differentially used codons among essential genes in bacteria identified by machine learning-based analysis.
Molecular genetics and genomics : MGG
Jul 27, 2024
Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-express...
ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.
Microbiome
May 9, 2024
BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identific...
Novel candidate genes for environmental stresses response in Synechocystis sp. PCC 6803 revealed by machine learning algorithms.
Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
May 6, 2024
Cyanobacteria have developed acclimation strategies to adapt to harsh environments, making them a model organism. Understanding the molecular mechanisms of tolerance to abiotic stresses can help elucidate how cells change their gene expression patter...
Dynamic Bayesian network structure learning based on an improved bacterial foraging optimization algorithm.
Scientific reports
Apr 9, 2024
With the rapid development of artificial intelligence and data science, Dynamic Bayesian Network (DBN), as an effective probabilistic graphical model, has been widely used in many engineering fields. And swarm intelligence algorithm is an optimizatio...
Identifying ARG-carrying bacteriophages in a lake replenished by reclaimed water using deep learning techniques.
Water research
Nov 11, 2023
As important mobile genetic elements, phages support the spread of antibiotic resistance genes (ARGs). Previous analyses of metaviromes or metagenome-assembled genomes (MAGs) failed to assess the extent of ARGs transferred by phages, particularly in ...
Application of the random forest algorithm to Streptococcus pyogenes response regulator allele variation: from machine learning to evolutionary models.
Scientific reports
Jun 16, 2021
Group A Streptococcus (GAS) is a globally significant bacterial pathogen. The GAS genotyping gold standard characterises the nucleotide variation of emm, which encodes a surface-exposed protein that is recombinogenic and under immune-based selection ...
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