AIMC Topic: Genes, Bacterial

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Dynamic Bayesian network structure learning based on an improved bacterial foraging optimization algorithm.

Scientific reports
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
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
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 ...

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Bio Systems
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...

Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models.

Water research
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...

HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes.

Microbiome
BACKGROUND: The spread of antibiotic resistance has become one of the most urgent threats to global health, which is estimated to cause 700,000 deaths each year globally. Its surrogates, antibiotic resistance genes (ARGs), are highly transmittable be...

pcPromoter-CNN: A CNN-Based Prediction and Classification of Promoters.

Genes
A promoter is a small region within the DNA structure that has an important role in initiating transcription of a specific gene in the genome. Different types of promoters are recognized by their different functions. Due to the importance of promoter...

Temporal variation and sharing of antibiotic resistance genes between water and wild fish gut in a peri-urban river.

Journal of environmental sciences (China)
Antibiotic resistance genes (ARGs) as emergence contaminations have spread widely in the water environment. Wild fish may be recipients and communicators of ARGs in the water environment, however, the distribution and transmission of ARGs in the wild...

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.

Scientific reports
It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a ...

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium.

Risk analysis : an official publication of the Society for Risk Analysis
Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the ...