AIMC Topic: Genes, Bacterial

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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...
Humans Machine Learning Anti-Bacterial Agents Metagenomics Genes, Bacterial Metagenome Drug Resistance, Bacterial Bacteria Computational Biology
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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 ...
Genes, Bacterial Genome, Bacterial Mannheimia haemolytica Phenotype Animals Microbial Sensitivity Tests Drug Resistance, Multiple, Bacterial Cattle Genotype Machine Learning Anti-Bacterial Agents Drug Resistance, Bacterial
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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...
Genes, Essential Genes, Bacterial Codon Machine Learning Bacteria Escherichia coli Genome, Bacterial Codon Usage
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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...
Drug Resistance, Microbial High-Throughput Nucleotide Sequencing Genes, Bacterial Bacteria Computational Biology Humans Neural Networks, Computer Anti-Bacterial Agents Drug Resistance, Bacterial Deep Learning
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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...
Stress, Physiological Gene Expression Regulation, Bacterial Synechocystis Bacterial Proteins Light Genes, Bacterial Machine Learning Algorithms Gene Expression Profiling Transcriptome Computational Biology Support Vector Machine
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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...
Genes, Bacterial Algorithms Artificial Intelligence Learning Bayes Theorem
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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 ...
Anti-Bacterial Agents Lakes Genes, Bacterial Deep Learning Bacteriophages Water
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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 ...
Genome, Bacterial Regulon Genes, Bacterial Bacterial Outer Membrane Proteins Antigens, Bacterial Genetic Variation Streptococcus pyogenes Humans Machine Learning Algorithms Bacterial Proteins Carrier Proteins Alleles Evolution, Molecular Streptococcal Infections
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A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Bio Systems Mar 20, 2021
Tolerance to stress conditions is vital for organismal survival, including bacteria under specific environmental conditions, antibiotics, and other perturbations. Some studies have described common modulation and shared genes during stress response t...
Models, Biological Pseudomonas aeruginosa Transcriptome Genes, Bacterial Stress, Physiological Genomics Principal Component Analysis Machine Learning Algorithms
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Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models.

Water research Mar 3, 2021
Antibiotic resistance genes (ARGs) have been reported to threaten the public health of beachgoers worldwide. Although ARG monitoring and beach guidelines are necessary, substantial efforts are required for ARG sampling and analysis. Accordingly, in t...
Genes, Bacterial Republic of Korea Deep Learning Drug Resistance, Microbial Neural Networks, Computer Anti-Bacterial Agents
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