AIMC Topic: Genome, Bacterial

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DeLUCS: Deep learning for unsupervised clustering of DNA sequences.

PloS one Jan 21, 2022
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of prim...
Humans Neural Networks, Computer Base Sequence Genome, Viral Genome, Mitochondrial Genome, Bacterial Animals Deep Learning Sequence Analysis, DNA Cluster Analysis
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Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

International journal of molecular sciences Dec 2, 2021
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...
Pseudomonas aeruginosa Genome, Bacterial Escherichia coli Mutation Whole Genome Sequencing Machine Learning Drug Resistance, Bacterial Anti-Infective Agents Genomics
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GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

Genome medicine Aug 30, 2021
BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly...
Humans Machine Learning Software Drug Resistance, Bacterial Tuberculosis, Multidrug-Resistant Genomics Reproducibility of Results Workflow Computational Biology Microbial Sensitivity Tests Genome, Bacterial Databases, Genetic ROC Curve Web Browser Antitubercular Agents
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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 ...
Streptococcal Infections Genetic Variation Streptococcus pyogenes Genes, Bacterial Evolution, Molecular Bacterial Proteins Alleles Bacterial Outer Membrane Proteins Antigens, Bacterial Genome, Bacterial Regulon Humans Machine Learning Algorithms Carrier Proteins
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Detecting operons in bacterial genomes via visual representation learning.

Scientific reports Jan 22, 2021
Contiguous genes in prokaryotes are often arranged into operons. Detecting operons plays a critical role in inferring gene functionality and regulatory networks. Human experts annotate operons by visually inspecting gene neighborhoods across pileups ...
Genomics Computational Biology Models, Genetic Escherichia coli Bacillus subtilis Humans Gene Expression Regulation, Bacterial Algorithms Genome, Bacterial Reproducibility of Results Operon Deep Learning
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Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

Trends in microbiology Jan 14, 2021
The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. This wealth of information has revealed an unanticipated degree of strain-to-strain genetic diversity w...
Virulence Genetic Variation Genome, Bacterial Genomics Genotype Bacteria Virulence Factors Machine Learning Phylogeny Genome-Wide Association Study
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Predicting antimicrobial resistance using conserved genes.

PLoS computational biology Oct 19, 2020
A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features de...
Machine Learning Algorithms Anti-Bacterial Agents Drug Resistance, Bacterial Phenotype Bacteria Genomics Genome, Bacterial Conserved Sequence
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Keeping up with the genomes: efficient learning of our increasing knowledge of the tree of life.

BMC bioinformatics Sep 21, 2020
BACKGROUND: It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequencing projects, such as the exponentially-growing NCBI RefSeq bacterial genome database. When new ref...
Metagenome Sequence Analysis, DNA Bayes Theorem Metagenomics Genome, Bacterial Humans Algorithms Machine Learning Bacteria Gastrointestinal Microbiome
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A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

mBio Aug 25, 2020
Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of isolates based on their genomic content. We applied a m...
Animals Mice Genomics Bacteremia Algorithms Machine Learning Phenotype Female Pseudomonas Infections Genome, Bacterial Mice, Inbred BALB C Virulence Pseudomonas aeruginosa Proof of Concept Study
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Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping.

Nature communications Jul 15, 2020
Predicting effects of gene regulatory elements (GREs) is a longstanding challenge in biology. Machine learning may address this, but requires large datasets linking GREs to their quantitative function. However, experimental methods to generate such d...
Molecular Sequence Annotation Escherichia coli Genome, Bacterial Binding Sites Sequence Analysis, DNA Phenotype Gene Knockout Techniques Ribosomes Deep Learning High-Throughput Nucleotide Sequencing Computational Biology Regulatory Sequences, Nucleic Acid Datasets as Topic
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