AIMC Topic: Genes, Bacterial
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HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes.
Microbiome
Feb 8, 2021
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
Dec 21, 2020
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)
Oct 24, 2020
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
Sep 14, 2020
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
Jun 8, 2020
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 ...
Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis.
Scientific reports
Mar 26, 2020
Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (M.tb), causes highest number of deaths globally for any bacterial disease necessitating novel diagnosis and treatment strategies. High-throughput sequencing methods genera...
Mycobacterium tuberculosis
Genes, Bacterial
Genes, MDR
Polymorphism, Single Nucleotide
Bayes Theorem
Bacterial Proteins
Mutation
Tuberculosis, Multidrug-Resistant
Molecular Dynamics Simulation
Algorithms
Molecular Docking Simulation
Drug Resistance, Multiple, Bacterial
Humans
Artificial Intelligence
Machine Learning
Genome-scale transcriptional dynamics and environmental biosensing.
Proceedings of the National Academy of Sciences of the United States of America
Jan 23, 2020
Genome-scale technologies have enabled mapping of the complex molecular networks that govern cellular behavior. An emerging theme in the analyses of these networks is that cells use many layers of regulatory feedback to constantly assess and precisel...
Fate of pirlimycin and antibiotic resistance genes in dairy manure slurries in response to temperature and pH adjustment.
The Science of the total environment
Dec 26, 2019
Quantifying the fate of antibiotics and antibiotic resistance genes (ARGs) in response to physicochemical factors during storage of manure slurries will aid in efforts to reduce the spread of resistance when manure is land-applied. The objectives of ...
Biomedical event extraction based on GRU integrating attention mechanism.
BMC bioinformatics
Aug 13, 2018
BACKGROUND: Biomedical event extraction is a crucial task in biomedical text mining. As the primary forum for international evaluation of different biomedical event extraction technologies, BioNLP Shared Task represents a trend in biomedical text min...
Gene Prediction in Metagenomic Fragments with Deep Learning.
BioMed research international
Nov 8, 2017
Next generation sequencing technologies used in metagenomics yield numerous sequencing fragments which come from thousands of different species. Accurately identifying genes from metagenomics fragments is one of the most fundamental issues in metagen...
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